In eastern part of Ethiopia groundnut is very commonly intercropped with sorghum. Even though intercropping of sorghum with groundnut is practiced in the eastern part of Ethiopia the population density at what ratio should not be known. Therefore determining the population ratio is found to be crucial to draw management options. The study was conducted at two locations at Fadis (on station) and Babile (sub- station). Sorghum variety (Teshale) and groundnut (Fetene) were used as planting materials. All agronomic data were collected and analyzed by using GenStat software. Significant different were obtained among the treatments. The research result showed that, there were significance difference for both sorghum and ground nut yield per hectare in the years (2014 and 2015) among treatments. The result over time(in 2014 and 2015) at Fadis and Erer showed that the highest sorghum and groundnut yield per hectare were obtained/harvested from the intra row spacing of 25cmx20cm and 30cmx20cm intercropping sorghum with ground nut system with (1.27 and 1.31) respectively. The highest LER (1.31) and highest GMV (10218.00 ETBr/ha) were obtained from the intercropping of 30cmx20cm (Sorghum & groundnut). Clearly showed that, with intercropping of sorghum and Groundnut, it is possible to produce additional yield of sorghum without significant reduction in groundnut yield. As a result of this, the intra spacing of the main crop (sorghum) 25cm and 30cm and for the subsidiary crop (groundnut) 20cm was recommended for further production in the study areas of eastern Harerghe zone and similar agro-ecologies.

Rice, as a staple crop feeding billions, faces constant threats from various diseases jeopardizing global food security. Precise understanding of disease resistance mechanisms is crucial for developing resilient rice varieties. Traditional genetic mapping methods, such as QTL mapping, provide valuable insights into the genetic basis of diseases. However, the complex nature of rice diseases demands a holistic approach to gain accurate knowledge of it. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, enable a comprehensive analysis of biological molecules, uncovering intricate molecular interactions within the rice plant. Integration of various mapping techniques using multi-omics data has revolutionized our understanding of rice disease resistance. By overlaying genetic maps with high-throughput omics datasets, researchers can pinpoint specific genes, proteins, or metabolites associated with disease resistance. This integration enhances the precision of disease-related biomarkers with better understanding of their functional roles in disease resistance. Improvement of rice breeding for disease resistance through this integration represents a significant stride in agricultural science because better understanding of the molecular intricacies and interactions underlying disease resistance architecture leads to more precise and efficient development of resilient and productive rice varieties. In this review, we explore how the integration of mapping and omics data can give a transformative impact on rice breeding for enhancing disease resistance.

Powdery mildew is a severe disease causing substantial yield losses in wheat production worldwide. The Chinese wheat landrace Changanhongmai (CAHM) exhibits high resistance to the physiological race E09 of powdery mildew. This study aims to characterize the powdery mildew resistance gene in CAHM, and develop molecular markers for marker-assisted selection of wheat. To investigate the genetic characteristics of this resistant gene, we developed F1 plants, F2 generation population, and F2:3 families from a cross between CAHM and SY225. Genetic analysis demonstrated that all F1 plants were resistant to the disease, while the ratio of resistant to susceptible plants was 3: 1 in both the F2 population and F2:3 families, indicating that CAHM is inherited in a manner of single dominant powdery mildew resistance gene, which was tentatively designated as PmCAHM. By using bulk segregation analysis, we constructed a genetic map encompassing Xgwm273, Xwmc626, Xgwm11, Xgwm18, Xgdm28, Xgpw7812, Xgpw5195, Xwmc694 and PmCAHM. Among these markers, Xgpw7812 and Xgpw5195 were flanking markers tightly linked to PmCAHM at a genetic distance of 2.5 cM and 8.4 cM, respectively. Furthermore, nullisomic-tetrasomic analysis revealed that PmCAHM is located on chromosome 1B. These results indicate that PmCAHM differs from the internationally recognized powdery mildew resistance genes in both location and source. In addition, a new germplasm/line NW1748 with large seeds and powdery mildew resistance was developed from the cross and back cross populations of Fengyou 1718 (FY1718)/CAHM//FY 1718. Therefore, PmCAHM can serve as a novel powdery mildew resistance source for breeding of wheat by using NW1748 as the donor in the future.

Climate change is challenging the agricultural sector worldwide. The pressure exerted by the altered thermal conditions drives the zonal shift for various cultivations. This study presents the multiyear analysis of the Growing Degree Days (GDD) index over the Northern Mediterranean Basin (NMB), focused on the high-value vine cultivation derived from the E-OBS dataset. To handle this extensive environmental dataset, R-language scripts and packages were applied, along with the capabilities of the GIS software. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas of GDD exceeding 2000 heat units. The extracted results specify the viticultural areas where the GDD index surpasses the suitable values for vine cultivation, owing to the increase of the thermal stress risk. In addition to mapping areas with GDD ≥ 2000, spatial calculations of the surface of areas meeting this criterion per country in the study area were made. In the northern parts of the NMB, the rise of the GDD index values indicates the establishment of vine plantations in the future.

A comparative study of organic and conventional farming systems was conducted in almond orchards to determine the effect of management practices on their fungal and bacterial communities. Soils from two orchards under organic (OM) and conventional (CM), and nearby nonmanaged soil (NM) were analyzed and compared. Several biochemical and biological parameters were measured (soil pH, electrical conductivity, total nitrogen, organic material, total phosphorous, total DNA, and fungal and bacterial DNA copies). Massive parallel sequencing of regions from fungal ITS rRNA and bacterial 16S genes was done to characterize their diversity in the soil. We report a larger abundance of bacteria and fungi in soils under OM, with a more balanced fungi:bacteria ratio, compared to bacteria-skewed proportions under CM and NM. The fungal phylum Ascomycota corresponded to around the 75% relative abundance in the soil, whereas for bacteria, the phyla Proteobacteria, Acidobacteriota and Bacteroidota integrated around 50% of their diversity. Alpha diversity was similar across practices, but beta diversity was highly clustered by soil management. Linear discriminant analysis effect size (LEfSE) identified bacterial and fungal taxa associated to each type of soil management. Analyses of fungal functional guilds revealed 3-4 times larger abundance of pathogenic fungi under CM compared to OM and NM treatments. Among them, the genus Cylindrocarpon was more abundant under CM and Fusarium under OM.

Adlay seed samples were collected from 3 adlay growing regions (Yeoncheon, Jeonnam and Eumseong regions) in Korea during 2012. Among all the samples collected, 400 seeds were tested for fungal occurrence by standard blotter and test tube agar methods and different taxonomic groups of fungal genera were detected. The most predominant fungal genera encountered were Fusarium, Phoma, Alternaria, Cladosporium, Curvularia, Cochliobolus and Leptosphaerulina. The occurrence of Fusarium species were 45.6% and based on the combined sequences of two protein coding genes, EF-1a, Beta-tubulin and phylogenetic analysis, 10 species were characterized as F. incarnatum (11.67%), F. kyushense (10.33%), F. fujikuroi (8.67%), F. concentricum (6.00%), F. asiaticum (5.67%), F. graminearum (1.67%), F. miscanthi (0.67%), F. polyphialidiom (0.33%), F. armeniacum (0.33%) and F. thapsinum (0.33%). The ability of these isolates to produce mycotoxins fumonisin (FUM) and zeralenone (ZEN) were tested by ELISA quantitative analysis method. The result revealed that fumonisin (FUM) was produced only by F. fujikuroi and zeralenone (ZEN) by F. asiaticum & F. graminearum. Mycotoxigenic species were then examined for their morphological characteristics to confirm their identity. Morphological observations of the species correlated well with their molecular identification and confirmed as F. asiaticum, F. fujikuroi and F. graminearum.

Effective agricultural management in maize production operations starts with the early quantification of seedlings. Accurately determining plant presence allows growers to optimize planting density, allocate resources, and detect potential growth issues early on. This study presents an in-depth analysis of multiple object detection models used by drones to count maize seedlings, while concurrently investigating the influence of planting density, flight altitude, and plant growth stage. The findings of this study demonstrate that one-stage models are able to more accurately detect maize seedlings than two-stage models. In particular, YOLOv8n exhibits outstanding performance, achieving an F1-score of over 0.92 under various density conditions and maintaining a stable performance, especially under densities below 105,000 plants/ha. Additionally, planting density and growth stage were observed to significantly affect detection accuracy, with performance declining as density and growth stage increased. Image resolution and detection were impacted by flight altitude, with lower flights producing higher-quality results. Ultimately, YOLOv8n displays optimal performance under various conditions, providing crucial data to support intelligent decision-making. This research offers valuable insights into the application of object detection technology and provides a basis for the future development of precision agriculture.

Emulsifiers like egg yolk (EY) are necessary for the formation of mayonnaise, which is an oil-in-water type colloid. This study aimed to assess the potential of defatted soybean powder treated with supercritical carbon dioxide (DSF-SC) in enhancing the quality of plant-based may-onnaise as plant-based alternatives gain popularity. This study involved producing DSF-SC and comparing its quality attributes to those of mayonnaise made with varying amounts of control soy flour (CSF), DSF-SC, and EY. It was found that mayonnaise made with DSF-SC, with increased emulsifier quantity, showed better emulsion stability, viscosity, and smaller, more uniform particle size compared with CSF mayonnaise. Additionally, DSF-SC mayonnaise was overall rated higher in sensory evaluation. The addition of approximately 2% DSF-SC positively influenced the emul-sion and sensory properties of the vegan mayonnaise, making DSF-SC a promising plant-based alternative emulsifier for replacing animal ingredients.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

During choriogenesis in insects, chorion (eggshell) is formed by surrounding follicular epithelial cells in ovarioles. However, the regulatory endocrine factor(s) activating choriogenesis and the chemical components on eggshell deserve further exploration. In two representative Coleopterans, a Coccinellid Henosepilachna vigintioctopunctata and a Chrysomelid Leptinotarsa decemlineata, genes encoding the 20-hydroxyecdysone (20E) receptor heterodimer, ecdysone receptor (EcR) and ultraspiracle (USP), and two chitin biosynthesis enzymes UDP-N-acetylglucosamine pyrophosphorylase (UAP) and chitin synthase (ChS1), were highly expressed in ovaries of the young females. RNA interference (RNAi)-aided knockdown of either HvEcR or Hvusp in H. vigintioctopunctata inhibited oviposition, suppressed the expression of HvChS1, and lessened the positive signal of Calcofluor staining on the chorions, which suggests the reduction of a chitin-like substance (CLS) deposited on eggshells. Similarly, RNAi of LdEcR or Ldusp in L. decemlineata constrained oviposition, decreased the expression of LdUAP1 and LdChS1, and declined CLS contents in the resultant ovaries. Knockdown of LdUAP1 or LdChS1 caused similar defective phenotypes, i.e., reduced oviposition and CLS contents in the L. decemlineata ovaries. These results, for the first time, indicate that 20E signaling activates choriogenesis in two Coleopteran species. Moreover, our findings propose the deposition of a CLS on the chorions.

As the global arid climate intensifies and the groundwater becomes increasingly scarce, drought stress has become a major challenge to plant growth and development worldwide, especially causing yield reduction and extinction of cultivated crops. In a large number of drought resistance studies, DNA methylation has been found dynamically associated with response to drought stress in plants by regulating gene expression and developments in plants, but the specific mechanisms are not yet clear. In this article, the current advances of research have been summarized on DNA methylation response to drought stress in various plant species, in terms of methylation detection methods, mechanisms of pattern changes (DNA de novo methylation, DNA maintenance methylation, and DNA demethylation), and its response to drought stress. With Most of the studies showed significant changes in genome or gene promoter methylation levels in plants subjected to drought stress, but the identification of the genes and pathways involved is still in the minority. The aim is to provide references for in-depth research on the response of plants to drought stress through epigenetics, and to uncover drought resistance genes regulated by DNA methylation, specific signaling pathways, and molecular mechanisms of action.

Plants can utilize the different forms of nitrogen (N), including inorganic and organic N nutrients, and show the great difference in the utilizing efficiency of N-form among species and genotypes within a species. In our previous study, we found that Tibetan wild barley (XZ16) was better in utilization of organic nitrogen in comparison with cultivated barley (Hua30). In this study, metabolite profiles of the two barley genotypes were comprehensively compared in their response to four N forms, including nitrate (NO3-), ammonium (NH4+), urea and glycine. Macro-and micro-nutrient concentrations in shoots were mostly found higher in nitrate and urea treatments than in ammonium and glycine in both the genotypes. XZ16 had higher concentrations of nutrient ions in glycine treatment, but Hua30 accumulated more nutrients in ammonium treatment. Among the total 163 differentially expressed metabolites, highest up-regulation and highest down-regulation was found in XZ16 in glycine and urea treatments respectively. Some important metabolites such as proline, glutamine, serine, asparagine, L-homoserine, aspartic acid, putrescine, ornithine, 4-aminobutyrate were up-regulated in glycine treatment in both the genotypes with higher fold change in XZ16 than in Hua30. Similarly, fructose-6-PO4, aconitic acid and isocitrate were only up-regulated in XZ16 in glycine treatment. Here, we concluded that the genotype XZ16 exhibited higher response to glycine treatment, while Hua30 showed higher response to NH4+ treatment which is attributed to their better utilization of glycine-N and NH4+-N, respectively. .

This paper presents the PEnsemble 4 model, a sophisticated machine learning framework that integrates IoT-based environmental data to accurately forecast maize yield. With the projected significant growth in global maize demand over the next decade, the inherent risks posed by the crop’s dependence on weather conditions necessitate improved prediction capabilities. The PEnsemble 4 model, developed with high accuracy, incorporates comprehensive datasets encompassing soil attributes, nutrient composition, weather conditions, and UAV-captured vegetation imagery. By employing a combination of Huber and M estimates, the PEnsemble 4 model effectively analyzes temporal patterns in vegetation indices, specifically CIre and NDRE, which serve as reliable indicators of canopy density and plant height. In addition, this research significantly contributes to precision agriculture by offering an efficient and sustainable alternative to conventional farming practices through precise yield predictions. Notably, the PEnsemble 4 model enables earlier estimation, advancing the timeline for yield prediction from the conventional day 100 in the R6 stage to day 79 in the R2 stage. This improvement enhances decision-making processes in farming operations. The remarkable accuracy rate of 91% underscores the importance of adopting a multifaceted data approach that harnesses IoT-derived environmental insights. Additionally, the PEnsemble 4 model extends its benefits beyond yield prediction, facilitating the detection of water and crop stress, as well as disease monitoring in broader agricultural contexts. Ultimately, the PEnsemble 4 model establishes a new standard in maize yield prediction, revolutionizing crop management and protection through the synergistic utilization of IoT and machine learning technologies.

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

The aim of this work was to describe the physiological limitations induced under drought conditions in young sweet orange trees, including the crop capability to recuperate its physiological status once re-watering, and after a water withholding. The trial was conducted during two consecutive months (July and August) in two-years old sweet orange trees. Three irrigation treatments were arranged: A full irrigation treatment; (FI); a low-frequency deficit-irrigation treatment (LFDI); and a sustained-deficit irrigation (SDI) treatment. The obtained results showed that for Stem values below -1.5 MPa, significant decreases in gas exchange rates, evidencing diffusive limitations to drought stress. Additionally, there was evidence of increased osmolyte synthesis, compatible as a defensive response to prevent oxidative damage. Likewise, the isohydric behaviour observed also resulted in significant decreases in gs even for moderate stress situations. In addition, it was observed that in the LFDI treatment, the stress levels reached caused a significant increase in the levels of Pro and MDA, which were not equal to those detected in FI during the recovery periods, which leads us to assume that potential values below -1.8 MPa would be causing significant oxidative damage with no capacity for subsequent recovery, and probably affecting the final yield.

Precise monitoring of individual crop growth and health status is crucial for precision agriculture practices. However, traditional manual inspection methods are time-consuming, labor-intensive, and often lack the spatial resolution required for detailed analysis. This research addresses the need for efficient and high-resolution crop monitoring by leveraging Unmanned Aerial Vehicle (UAV) imagery and advanced computational techniques. The primary objective was to develop a methodology for precise identification, extraction, and monitoring of individual corn crops throughout their growth cycle. This was achieved by integrating UAV-derived data with image processing, computational geometry, and machine learning techniques. UAV imagery was ac-quired bi-weekly at altitudes of 40m and 70m, capturing the entire growth cycle of a corn crop from planting to harvest. A time-series Canopy Height Model (CHM) was generated by analyzing the differences between the Digital Terrain Model (DTM) and the Digital Surface Model (DSM) derived from the UAV data. Local spatial analysis and image processing techniques were em-ployed to determine the local maximum height of each crop. Subsequently, a Voronoi data model was developed to delineate individual crop canopies, successfully identifying 13,000 out of 13,050 corn crops in the study area. For enhanced accuracy in canopy size delineation, vegetation indices were incorporated into the Voronoi model segmentation, refining the initial canopy area esti-mates by eliminating interference from soil and shadows. The proposed methodology enables precise estimation and monitoring of crop canopy size, height, biomass reduction, lodging, and stunted growth over time, providing valuable insights for precision agriculture practices. This work contributes to the scientific community by demonstrating the potential of integrating UAV technology, computational geometry, and machine learning for accurate and efficient crop mon-itoring at the individual plant level.

Floods are among the most serious natural disasters worldwide; they cause enormous crop losses every year and threaten world food security. There are many studies focused on flood impact assessments for administrative districts but fewer on postdisaster impact assessments for specific crops. Therefore, this study used remote sensing data, including the normalized difference vegetation index (NDVI), elevation data, slope data, and rainfall data, combined with crop growing season data to construct a crop flood damage assessment index (CFAI). First, an analytic hierarchy process (AHP) was used to assign weights to the impact factors; then, the weighted composite score method was used to calculate the CFAI; and finally, the impact was classified as slight, moderate, or severe based on the magnitude of the CFAI . This method was used for the Missouri River floods of 2019 in the U.S. Due to the lack of measured data, the disaster vegetation damage index (DVDI) was used to validate the results. The combined approach achieved a high degree of consistency in spatial distribution. The CFAI can respond well to the degree of crop impact after flooding, providing new ideas and reference standards for agriculture-related departments.

The maintenance of traditional agricultural practices in protected small islands is closely linked to the preservation of the land, the protection of natural resources, and the conservation of local traditions. For this purpose, the Tuscan Archipelago National Park promoted the census of ancient horticultural varieties preserved by some farmers on the island of Elba. The survey revealed a deep-rooted historical, cultural, social, and economic link between this germplasm and the island’s territory. A scientific characterization of the landrace under ethnobotanical, morphological, and genetic aspects was carried out. Among these local varieties, two landraces of the Brassica species and three landraces of the Phaseolus species were identified and analyzed in this study. To ascertain their distinguishability and uniqueness, similar varieties were also identified based on morpho-physiological characteristics or territorial proximity and compared with the Elban landraces. Morpho-phenological data were collected, and molecular analyses were carried out using Simple Sequence Repeats (SSR) markers. Ten different SSR loci were considered for the Phaseolus species and nine for the Brassica species. The Tuscan Archipelago landraces showed a high level of internal variability but were clearly distinct from each other and from the analyzed varieties, as shown by AMOVA (Analysis of Molecular Variance). Their distinctness was further highlighted by the UPGMA dendrogram obtained from the genetic distance matrix. The same results were confirmed by Principal Coordinate Analysis (PCoA). This study confirms the peculiarity of the Elban landraces, their biodiversity is a heritage to be safeguarded, which can also be used in future breeding programs. These ancient Elban landraces were allocated to local farmers (most were young farmers) to protect them from extinction and to promote more resilient varieties cultivation compared to commercial hybrids widely spread in the area. Local farmhouses also play a strategic role in safeguarding the germplasm and dissemination of sustainable agricultural practices. There is high demand for ancient Elban landraces, this has led to the development of a new local economy balanced between agricultural tradition and innovation.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

Familial Alzheimer’s disease (FAD) can be caused by mutations in PSEN1 that encodes presenilin-1, a component of the gamma-secretase complex that cleaves amyloid precursor protein. Alterations in calcium (Ca2+) homeostasis and glutamate signaling are implicated in the pathogenesis of FAD, however it has been difficult to assess in humans whether or not these phenotypes are the result of amyloid or tau pathology. This study aimed to assess early calcium and glutamate phenotypes of FAD by measuring the Ca2+ response of induced pluripotent stem cell (iPSC)-derived neurons bearing PSEN1 mutations to glutamate and the ionotropic glutamate receptor agonists NMDA, AMPA and kainate compared to isogenic control and healthy lines. The data shows that in early neurons, even in the absence of amyloid and tau phenotypes, FAD neurons exhibit increased Ca2+ responses to glutamate and AMPA, but not NMDA or kainate. Together this suggests that PSEN1 mutations alter Ca2+ and glutamate signaling as an early phenotype of FAD.

Germplasm is a long-term resource management mission and investment for civilization. For both food and nutritional health, the present changing environmental scenario has become an urgent universal concern. Multiple excellent studies have been previously performed, although the advancement and innovation of practices will require the exploration of the potentiality of crop germplasm. In this study, we emphasized (i) germplasm activates, current challenges and ongoing trends of the crop germplasm, and (ii) how the system biology will be helpful to understand the complex traits such as water use efficiency (WUE), and nitrogen use efficiency (NUE) to mitigate challenges for sustainable development under growing food requirement and climate change conditions. We focused on a vision for transforming PGR into a bio-digital resource system, for the development of climate-smart crops for sustainable food production. Moreover, this review attempted to address current challenges, research gaps and describe the advanced integrated strategies that could provide a platform for future crop improvement research.

Green manure could improve soil nutrients and crop production, playing a significant role in sustainable agriculture. However, the impacts of green manure on crop health and the roles soil microbial communities play in the process haven’t been clarified clearly yet. In this study, we investigated soil microbial community composition and structure in four tobacco farmlands, which were treated with different green manure (control, ryegrass, pea and rape), using 16S rRNA gene amplicons sequencing. Results showed that green manure had significant impacts on soil properties, microbial communities and tobacco health. First, soil total C, N and Ca content increased significantly in groups treated with green manure than control. Second, soil community diversity was significantly higher in groups treated with green manure. Third, green manure especially ryegrass, decreased tobacco disease (bacterial wilt) rate dramatically, and the process might be mediated by soil microbial communities. On the one hand, several microbial populations were found to be potentially disease inducible or suppressive. For example, the abundances of Dokdonella and Rhodanobacter were positively correlated to tobacco disease rate, while Acidobacteira_Gp4 and Gp6 had negative correlations with tobacco disease. On the other hand, soil microbial communities were shaped by soil properties (e.g., pH, C and N content). In conclusion, our research showed that green manure could increase soil nutrients directly, and further improve tobacco health mediated by soil microorganisms, which may shed light on revealing interactions among soil properties, microorganisms and plants.

This study aimed at testing the effectiveness of novel combinations of chemical and physical methods to control Prosopis juliflora, an invasive weed in the Moshi and Simanjiro districts of Nothern Tan-zania. Six different treatments including manual uprooting, glyphosate, bark chop with chemical application, two separate chemical mixtures and control were tested in a total of 32 plots, which represented two land use types (grazing land and farmland) found in the two districts. Each plot covered 20m×30m plot area. Two response variables (stem count and tree volume) were recorded to compare weed population density before and after treatment six months later. An analysis of the untreated control plots, showed that the inherent growth potential of P. juliflora was higher in Moshi than in Simanjiro district. The number of stems increased during the experiment for all six treatments showing that the P. juliflora population had not yet reached the local carrying capacity. For the manual control treatment, the increase was reduced compared to the untreated control. For all other treatments, the increase in stem count was on par with that in the untreated control or even higher. Thus, we conclude that only manual uprooting had a controlling effect but not to the extent that it eradicated P. juliflora. Thus, it is for P. juliflora as for weed control in general: weed control must be an ongoing effort.

Alternative fertilizations are essential to minimize the deteriorating effects of chemical fertilizers on soil and water quality/health. Accordingly, the present work investigated the effects of combined organic-inorganic fertilization (COIF) on wheat and rice yields, soil nutrients, and soil Cd accumulation. Hence, seven different treatments were set up: control (CK); conventional fertilization (CF); optimized fertilization (OF); organic fertilizer replacing 25% (T1) and 50% (T2) of OF; and organic nitrogen (N) replacing 25% (M1) and 50% (M2) of OF-N. Overall, significant increases occurred in the yields of COIF crops. Compared with the CF, the highest wheat and rice yields happened in M1 treatment (approximately by18.5%) (P < 0.05). COIF slightly alleviated soil acidification, and improved the cation exchange capacity (CEC) of the study soils. Besides, COIF treatments significantly increased the contents of total phosphorus, total potassium, available phosphorus, and available potassium by 6.35 to 16.9 %, 3.17 to 10.9 %, 5.53 to 28.7 %, and 2.6 to 12 %, respectively (P <0.05). Nevertheless, negligible increases took place in Cd content of COIF soils compared with the CK. Altogether, our results concluded on 25% replacement of OF-N by organic N (M1) to effectively improve the fertility/ecological sustainability of the study soils.

Diacylglycerol kinase (DGK) is a lipid kinase that phosphorylates diacylglycerol (DAG) to generate phosphatidic acid (PA). Based on converting one important signaling molecule (DAG) to another (PA), DGK plays an important role in plant responses to abiotic stress including waterlogging stress. However, no studies have been reported on the characterization of the DGK gene family in the waterlogging-tolerant kiwifruit germplasm, Actinidia valvata Dunn. Here, we identified 18 AvDGK genes in the A. valvata genome. The phylogenetic analysis showed that AvDGKs can be classified into three clusters, and members within the same cluster have similar domain distribution, exon-intron structures and conserved motif compositions. Chromosome localization analysis revealed that all the AvDGK genes are located across 18 different chromosomes. There were 29 duplicated gene pairs in kiwifruit and all had undergone purifying selection during evolution. Promoter cis-element analysis revealed that the cis-elements within AvDGK genes are associated with multiple functions, including phytohormone signal transduction, stress response, and plant growth and development. The expression pattern analyses indicated that AvDGK play an important role in the fruit development and plant response to waterlogging stress. AvDGKs gene family in the tetraploid A. valvata genome might promote PA synthesis and subsequent signal transduction both under short-term and long-term waterlogging stress. These results provide information regarding the structural characteristics and potential function of DGK genes within kiwifruit and lay a fundamental basis for further research into breeding for enhancing the kiwifruit’s tolerance to waterlogging stress.

The importance of irrigation in boosting agricultural production and productivity is widely understood. Proper planning and effective and efficient management and operation of irrigation system require crop and site-specific data. Since the last few years, Ethiopia has embarked on expansion of irrigated wheat. However, crop-specific data useful for irrigation planning and management for wheat crop is limited. The objective of this research was to determine water requirements and crop coefficients for wheat crops based on field measurements. The research was carried out at the Debre Zeit Agricultural Research Center in central Ethiopia during the dry season (Bega) of 2021/22. The crop considered for the experiment was durum wheat of the Utuba variety. Two non-weighing lysimeter units were employed to measure the water balance components. The soil moisture was monitored using gravimetric method on daily basis conducted both before and after each irrigation event at various depth intervals. The crop required a total of 115 days to fully mature. The length of the growth of initial, development, mid, and late stages were about 20, 30, 42, and 23 days, respectively. Microsoft Excel was used for the data analysis and the CropWAT8.0 model to estimate the reference evapotranspiration. Crop evapotranspiration (ETc) was determined using the water balance equation, and crop coefficients were computed from ETc and reference evapotranspiration (ETo). The results indicate that the total seasonal water requirement of the crop was 392.75mm. The growth stage-based water requirement was 40.35 mm, 82.44 mm, 238.66 mm, and 31.3 mm during the initial, development, mid, and late growing stages, respectively. For the initial, development, mid, and late stages of wheat growth, the crop coefficient was calculated to be 0.51, 0.83, 1.29, and 0.52, respectively. It was found that a fourth-degree polynomial equation fits well and explains the relationship between day of growth stage and kc of the crop. Although a one-season measurement, the results generated here could be useful for crop-specific data in scarce areas.

Meningitis is a severe disease associated with death in children under five with highest rates of infections under age of one. Vaccines for Neisseria meningitides and Haemophilus influenza are used to prevent the main causative agents of meningitis. Administration of H. influenzae type b (Hib) vaccine is recommended at 2, 4 and 6 months with a booster dose at 18 months. N. meningitidis has two commercially available vaccines, the pure polysaccharide is recommended at 24 months meanwhile the protein-conjugated vaccines at 12 months. We sought in this study to examine if coadministering the vaccines for the two main meningitis causing bacteria might be synergistic as a preliminary step towards the possibility of shuffling immunization schedule. So, we coadministered Hib vaccine with commercially available vaccines either quadrate (ACWY) polysaccharide meningococcal (Men) or conjugated meningococcal (Nim) vaccines in Balb/C mice (n = 6/group) and compared to each vaccine administered separately and controls. Thirty-five days post immunization, we measured specific antibodies titers. Hib vaccine increased Men antibody titers significantly for serotypes Y and W. When Hib vaccine was coadministrated with Nim, antibody titer for Y, W and A significantly increased. For serotype C, there was no significant difference in antibody titers among immunized groups. As for effect of meningococcal vaccines on Hib, Men significantly increased Hib antibody titers while Nim had no effect. Collectively, our data suggested that coadministration of Hib and Men or Nim vaccines was safe and had synergistic effect on immune responses elicited to both vaccines. Further studies are needed before immunization schedule modifications. Such immunization schedule recommendation should provide better protection against this life-threatening disease in young children.

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California’s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ystem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an r² >= 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm day^-1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.

This study proposed to use wearable EEG to study the impact of vipassana mindfulness practice on beginner's physiological and neurological responses. Mindfulness meditation has been shown to have numerous benefits, including stress reduction, improved attention and cognitive function, and enhanced emotional regulation. The roots of mindfulness meditation in Buddhism emphasize cultivating present-moment awareness and insight. However, the neural mechanisms together with physiological mechanism and their interaction underlying these benefits remain poorly understood. Method: One middle age man (50 years old) participated in this longitudinal study using wearable EEG to investigate the neurophysiological change during a one-month consecutive vipassana mindfulness practice. Both EEG and heart rate responses were recorded each time, before (5 minutes), during (20 minutes), and after (5 minutes) meditation sessions. The EEG and HR data were analyzed by Matlab and EEGlab to examine changes in brainwave activity and heart rate. Results: alpha peak frequency (APF) is significantly lower after mindfulness meditation, as shown by comparison of APF before mindfulness (pre-5) and during mindfulness practice (med-20), and comparison between APF of pre-5 and after mindfulness practice (post-5). The same is with the beta peak power. While for theta peak frequency, it is significant lower during mindfulness meditation (med-20), when comparing to either pre-5 or post-5. See figure 1a. However, peak power index is not so sensitive, and it is more obvious in theta wave band. That is, the theta power peak is significantly lower after meditation, as can be observed in comparison between pre-5 and med-20, also between pre-5 and med-20. See figure 1b. STATE Heart-mean (bpm) Heart-std(bmp) pre-5 69.88 3.88 med-20 68.36 2.81 post-5 69.55 4.13 t-value test (pre-med) 0.0694 0.0003 t-value test (pre-post) 0.7934 0.3656 t-value test (post-med) 0.3193 0.0001 Table 1. The difference of Heart rate (mean and SD) in before (pre-5), during (med-20) and after (post-5)mindfulness meditation. We find significant change in standard deviation (SD) of heart rate between meditation and non-meditation mental states, as shown in table 1. The study provides insights into the underlying neurophysiological mechanisms of mindfulness meditation using wearable EEG devices. It demonstrates that in term of EEG measurement, spectrum frequency can be more sensitive than spectrum power; also heart rate variability as measured by SD is more sensitive to mean of HR. The proposed study contributes to the literature by using wearable EEG devices to collect data in a more accessible and convenient manner.

Fermented foods have long been known to have immunomodulatory capabilities and fermentates derived from the lactic acid bacteria of dairy products can modulate the immune system. We have used skimmed milk powder to generate novel fermentates using Lb. helveticus strains SC234 and SC232 and we demonstrate here that these fermentates can enhance key immune mechanisms that are critical to the immune response to viruses. We show that our novel fermentates SC234 and SC232 can positively impact on cytokine and chemokine secretion, nitric oxide (NO) production, cell surface marker expression, and phagocytosis in macrophage models. We demonstrate that fermentates SC234 and SC232 increase the secretion of cytokines IL-1β, IL-6, TNF-α, IL-27, and IL-10, promote an M1 proinflammatory phenotype for viral immunity via NO induction, decreases chemokine expression of Monocyte Chemoattractant Protein (MCP), increasing cell surface marker expression, and enhance phagocytosis in comparison to their starting material. These data suggest that these novel fermentates have potential as novel functional food ingredients for the treatment, management and control of viral infection.

Berberis vulgaris L. (Berberidaceae) is a shrub that has been widely used in European folk medicine as an anti-inflammatory and antimicrobial agent. The purpose of our study was to elucidate the mechanisms of antiproliferative action of the plant’s methanolic root extract (BVR) against colon cancer cells. Cytotoxicity and pro-apoptotic activity were determined in human colon adenocarcinoma cell lines (LS180 and HT-29) and control colon epithelial CCD841 CoN cells. According to the MTT assay, after 48 h of cell exposure, the IC50 values were as follows: 4.3; 46.1 and 50.2 µg/mL for LS180, HT-29, and CCD841 CoN cells, respectively, showing the greater sensitivity of cancer cells to BVR. The Cell Death Detection ELISAPLUS kit demonstrated that BVR induced programmed cell death only against HT-29 cells. RT-qPCR with relative quantification method showed significant changes in the expression of genes related to apoptosis in both colon cancer cell lines. The genes BCL2L1 (126.84-366.66%), BCL2L2 (277.08-330.12%), CASP3 (180.36-261.36%) and CASP9 (158.08-213.46%) had significantly elevated expression, while BCL2 (23.08-52.06%) had reduced expression. Furthermore, in a panel of antioxidant tests, BVR showed positive effects (63.93±0.01, 122.92±0.01, and 220.29±0.02 mg Trolox equivalents (TE)/g in the DPPH•, ABTS•+ and ORAC assays, respectively). In the lipoxygenase (LOX) inhibition test, BVR revealed 62,60±0.87% of enzyme inhibition. The chemical composition of BVR was determined using UHPLC-UV-CAD-MS/MS analysis and confirmed the presence of several known alkaloids, including berberine, as well as other alkaloids and two derivatives of hydroxycinnamic acid (ferulic and sinapic acid hexosides). This is the first such extensive assessment of the biological activity of BVR. The results are very promising and encourage for the use of BVR as a comprehensive chemopreventive agent (anti-inflammatory, antioxidant, and pro-apoptotic) in colorectal cancer.

Abstract: Kiwifruit, a perennial horticultural crop known for its nutritional value, faces significant challenges due to biotic and abiotic stresses, affecting its yield and quality. Leucine-rich repeat receptor-like proteins (LRR-RLPs), a major group of receptor-like proteins in plants, have diverse functions in plant physiology, including growth, development, signal transduction, and stress responses. Despite their importance, the specific roles of kiwifruit LRR-RLPs in response to biotic and abiotic stresses remain poorly understood. In this study, we investigated the expression patterns of kiwifruit LRR-RLPs under various stress conditions, including pathogen stress, heat stress, waterlogging stress, and copper stress. Through genome and transcriptome analyses, we identified a total of 101, 164, and 105 LRR-RLPs in Actinidia Chinensis 'Hongyang', Actinidia eriantha 'Huate', and Actinidia chinensis 'Red5' kiwifruit, respectively, classified into 9 subgroups based on phylogenetic relationships. Synteny analysis revealed that the expansion of kiwifruit LRR-RLPs was primarily attributed to segmental duplication events. Using RNA-seq data from pathogen-infected kiwifruits, we identified specific LRR-RLP genes potentially involved in different stages of pathogen infection. Additionally, we observed the potential involvement of kiwifruit LRR-RLPs in abiotic stress responses, with upstream transcription factors possibly regulating their expression. Furthermore, protein interaction network analysis unveiled the participation of kiwifruit LRR-RLP genes in the regulatory network of abiotic stress responses. These findings highlight the crucial roles of LRR-RLPs in mediating both biotic and abiotic stress responses in kiwifruit, offering valuable insights for the breeding of stress-resistant kiwifruit varieties.

RNAi technology is a versatile, effective, safe, and eco-friendly alternative for crop protection. There is plenty of evidence of its use through host-induced gene silencing (HIGS) and spray-induced gene silencing (SIGS) techniques to control viruses, bacteria, fungi, insects, and nematodes. For SIGS, its most significant challenge is achieving stability and avoiding premature degradation of RNAi in the environment or during its absorption by the target organism. One alternative is encapsulation in liposomes, virus-like particles, polyplex nanoparticles, and bioclay, which can be obtained through the recombinant production of RNAi in vectors, transgenesis, and micro/nanoencapsulation. The materials must be safe, biodegradable, and stable in multiple chemical environments, favoring the controlled release of RNAi. Most of the current research on encapsulated RNAi focuses primarily on oral delivery to control insects by silencing essential genes. The regulation of RNAi technology focuses on risk assessment using different approaches; however, this technology has positive economic, environmental, and human health implications for its use in agriculture. The emergence of alternatives combining RNAi gene silencing with the induction of resistance in crops by elicitation and metabolic control is expected, as well as multiple silencing and biotechnological optimization of its large-scale production.

A number of studies suggested that influenza vaccination can provide protection against COVID-19 but the underlying mechanisms that could explain this association is still unclear. In this study, the effect of the 2021/2022 seasonal influenza vaccination on the immune response to the booster dose of anti-SARS-CoV-2 vaccination was evaluated in a cohort of healthy individuals. One hundred and thirteen participants were enrolled, and 74 of them with no prior COVID-19 diagnosis or significant co-morbidities were considered for the analysis. Participants received the anti-influenza tetravalent vaccine and the booster dose of the anti-SARS-CoV-2 vaccine or the anti-SARS-CoV-2 vaccine alone. Blood was collected before and 4 weeks after each vaccination and 12 weeks after SARSCoV2 vaccination and analyzed for anti-flu and anti-spike-specific antibody titers and for in vitro influenza and SARS-CoV-2 neutralization capacity. Results indicated an increased reactivity in subjects who received both influenza and SARSCoV2 vaccinations, as compared to those who received only the SARS-CoV-2 vaccine, with sustained anti-spike antibody titers up to 12 weeks post-vaccination. Immune response to influenza vaccine was evaluated and individuals were stratified as high or low responders. High responders showed increased antibody titers against SARSCoV2 vaccine both after 4- and 12-weeks post-vaccination. On the contrary, the individuals classified as low responders were less responsive to the SARS-CoV-2 vaccine. These data indicate that both external stimuli, such as influenza vaccination, and the host's intrinsic ability to respond to stimuli play a role in the response to vaccine.

Nitrogen (N) is an essential macro nutrient for crop growth; therefore, N deficit can greatly limit crop growth and production. In the North China Plain (NCP), winter wheat is one of the main food crops, and its yield has increased from approximately 4000 kg ha-1 to 6000 kg ha-1 in the last two decades. Determining the proper N application rates at different growth stages and in all seasons is very important for the sustainable and high production of wheat in the NCP. A field experiment with five N application rates (250, 200, 150, 100, and 40 kgN·ha-1, designated as N250, N200, N150, N100, and N40, respectively) was conducted during the 2017-2018 and 2018-2019 winter wheat seasons to investigate the effects of the N application rate on water- and fertiliz-er-utilization efficiency, and on the crop growth and yield of winter wheat under sprinkler fer-tigation conditions. The results showed that, in the N application range of 40-200 kg ha-1, crop yield and water- and fertilizer-use efficiencies increased as the N application rate increased; however, further increases in the N application rate did not have additional benefits. The N up-take after regreening of winter wheat linearly increased with crop growth. Considering the wheat yield and N-use efficiency, the optimal N application range was 200 kg ha-1, and the best top-dressing strategy was equal amounts of N applied at the regreening, jointing, and grain-filling stages. The results of this study will be useful for optimizing field N management to achieve high wheat yield production in the NCP and in regions with similar climatic and soil environment conditions.

Maize is an important staple food crop in sub-Saharan Africa (SSA). However, the average grain yield on farmers’ fields falls considerably short of the demand of the region’s population. In addition, the normal endosperm maize widely consumed in SSA is deficient in vitamin A. Drought, a consequence of climate change, is a major constraint to maize production, resulting in seasonal low grain yield in farmers’ fields. The objectives of this study were to assess the performance of newly developed extra-early maturing provitamin A hybrids under managed drought and well-watered conditions, compare the outcomes of multiple trait base-index and multi-trait genotype-ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety provitamin A hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14*14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple trait base index and multiple-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA.

The antimicrobial properties of the new strains of microorganisms isolated from natural sources of various ecological niches in the Moscow Region and the Republic of Tatarstan were studied. An antifungal activity of isolates was established in a test culture of toxin-producing microscopic fungi that cause various plant diseases: Fusarium oxysporum, Aspergillus flavus, Penicillium spp. and Candida albicans. Of the 46 studied microorganisms, 4 isolates (Bacillus subtilis, Propionibacterium freudenreichii, Lactobacillus plantarum and Streptomyces spp.) showed an ability to produce biologically active metabolites with a pronounced antimicrobial potential. This is promising in the growth and protection of the Scots pine, pedunculate oak and small-leaved linden forest crops from diseases caused by fungi Lophodermium pinastri Chev. and Microsphaera alphitoides stimulation. Based on selected isolates, a Bacterial product LRV composition has been developed. A Scots pine, pedunculate oak and small-leaved linden seedlings single and double foliar treatment with Bacterial product LRV at a concentration of 10 ml/l led to an increase in the growth of an above-ground part by 31.8, 51.9 and 25.4 %, respectively, and an underground part – by 25.0, 37.2 and 25.7 %, respectively, compared with the control. The weight of seedling at the end of the study exceeded the control variant by an average of 26.0, 44.0 and 78.0 %, respectively. A use of a plant protection Bacterial product LRV did not have a significant effect on a powdery mildew and Schütte disease damage to forest crops. A Biogeosystem Technique methodology has been developed to improve a long-term forest growing.

Fibrosis is a ubiquitous pathology, and prior studies have indicated that various artemisinin (ART) derivatives (including artesunate (AS), artemether (AM), and dihydroartemisinin (DHA)) can reduce fibrosis in vitro and in vivo. The medicinal plant, Artemisia annua L., is the natural source of ART and is widely used, especially in underdeveloped countries, to treat a variety of diseases including malaria, while A. afra contains no ART but is also antimalarial. Using human dermal fibroblasts (CRL-2097), we compared the effects of A. annua and A. afra tea infusions, ART, AS, AM, DHA, and a liver metabolite of ART, deoxyART (dART), on fibroblast viability and expression of key fibrotic marker genes after 1 and 4 days of treatment. AS, DHA, and Artemisia tea significantly reduced fibroblast viability at 1 and 4 d post-treatment. After 4 d post treatment, AS, DHA, and A. afra tea downregulated ACTA2, and upregulated MMP3, with other genes either being unaffected or differentially affected. ART and AM had no significant effect on either fibroblast viability or fibrotic gene expression. Although A. annua contains ART, it had a significantly greater anti-fibrotic effect than ART alone. Immunofluorescent staining for smooth muscle α-actin (α-SMA) correlated well with transcriptional responses of drug-treated fibroblasts. Together, proliferation, qPCR, and immunofluorescence results show that treatment with ART, AS, DHA, and the two Artemisia teas yield differing responses, including those related to fibrosis, in human dermal fibroblasts.

Studies on the domestication, genetic differentiation, and crop evolution of foxtail millet are re-viewed. Several genetic studies were carried out to elucidate the genetic relationships among foxtail millet accessions originating mainly from Eurasia, based on intraspecific hybrid pollen semi-sterility, isozymes, DNA markers, and single-nucleotide polymorphisms. Most studies suggest that China is the center of diversity of foxtail millet, and landraces were categorized into geographical groups. Furthermore, the evolution of genes was reviewed (i.e., the Waxy gene conferring amylose content in the endosperm, the Si7PPO gene controlling polyphenol oxidase, the HD1 and SiPRR37 genes controlling heading time, the Sh1 and SvLes1 genes involved in grain shattering, and the C gene controlling leaf sheath pigmentation), and the variation and distribu-tion of these genes suggested complex patterns of evolution under human and/or natural selec-tion.

Increased soluble endoglin (sENG) were observed in human brain arteriovenous malformations (bAVMs), and overexpression of sENG with vascular endothelial growth factor (VEGF)-A induced dysplastic vessel formation in mouse brain. However, the underlying mechanism of sENG-induced vascular malformations is not clear. While evidence suggests the role of sENG as a pro-inflammatory modulator, increased microglial accumulation and inflammations were observed in bAVMs. Therefore, we hypothesized that microglia mediate sENG-induced inflammation and endothelial cell (EC) dysfunction in bAVMs. In this study, we confirmed that sENG with VEGF-A overexpression induced dysplastic vessel formation. Remarkably, there were increased microglial activation around dysplastic vessels with expression of NLRP3, inflammasome marker. We found that sENG increased the gene expression of VEGF-A, pro-inflammatory cytokines/inflammasome mediators (TNF-α, IL-6, NLRP3, ASC, Caspase-1, and IL-1β), and proteolytic enzyme (MMP-9) in BV2 microglia. The conditioned media from sENG-treated BV2 (BV2-sENG-CM) significantly increased angiogenic factors (Notch-1 and TGFβ) and pERK1/2 in ECs while it decreased IL-17RD, an anti-angiogenic mediator. Finally, the BV2-sENG-CM significantly increased EC migration and tube formation. Together, our study demonstrates that sENG provokes microglia to release angiogenic/inflammatory responses which may be involved in EC dysfunction. Our study suggests the contribution of microglia in the pathology of sENG-associated vascular malformations.

Endophytic microbes are a ubiquitous group of plant-associated communities that colonize the intercellular or intracellular host tissues while giving numerous beneficial effects to the plants. All the plant species are thought to be associated with endophytes, majorly constituted with bacteria and fungi. During the last two decades, there has been a considerable movement toward the study of endophytes associated with coffee plants. In this review, the main consideration is given to address the coffee-associated endophytic bacteria and fungi, particularly their action on plant growth promotion and the biocontrol of pests. In addition, we sought to identify and analyze the gaps in available research. Additionally, the potential of endophytes to improve the quality of coffee seeds is briefly discussed. Even though there are limited studies on the subject, it has been well recognized the potentiality of coffee endophytes in plant growth promotion through enhancing nitrogen fixation, availability of minerals, nutrient absorption, secretion of phytohormones, and other bioactive metabolites. Further, the antagonistic effect against various coffee pathogenic bacteria, fungi, nematodes, and also insect pests lead to the protection of the crop. Furthermore, it is recognized that endophytes enhance the sensory characteristics of coffee as a new field of study.

In Bangladesh, climate change is a major concern because of its geophysical location and climate dependent agriculture. As sessile organisms, crops plants have to face difficulties often in this environmentally vulnerable country. Therefore, this study examines the seasonal trend of two climatic parameters viz. temperature (maximum and minimum) and rainfall over a period of 1983 to 2013. Besides, this study provides insight into the relationship between climatic parameters and crop yield of two major crops viz. rice and wheat during 1997-2013. To assess the relationship of climatic parameters with time and yield using Pearson correlation analysis, time series data used at an aggregate level. SPSS software utilized for this analysis. The cropping seasons such as rice growing seasons Aus (summer rice), Aman (autumn rice) and Boro (winter rice) exhibited a significant increase in maximum and minimum temperature. Rainfall found to have a decreasing trend for all the seasons. This study also revealed that the climatic parameters had significant effects on rice yield, but these results varied among three rice crops. Maximum temperature had positive effects on all rice yields, especially on Aus and Aman. Minimum temperature had a negative effect on Aman rice yield but a positive effect on Aus rice yield. Wheat yield negatively associated with temperature. Rainfall exhibited negative relation with both rice and wheat yield.

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

Fermented foods and ingredients, including fermentates derived from lactic acid bacteria (LAB) in dairy products, can modulate the immune system. Here we describe the use of reconstituted skimmed milk powder to generate novel fermentates from Lactobacillus helveticus strains SC232, SC234, SC212, and SC210, and from Lacticaseibacillus casei strains SC209 and SC229, and demonstrate using in vitro assays that these fermentates can differentially modulate cytokine secretion by bone marrow derived dendritic cells (BMDCs) when activated with either the viral ligand, loxoribine, or an inflammatory stimulus, lipopolysaccharide. Specifically, we demonstrate that SC232 and SC234 increase cytokines IL-6, TNF-α, IL-12p40, IL-23, IL-27 and IL-10, and decreased IL-1β in primary bone marrow derived dendritic cell (BMDCs) stimulated with a viral ligand. In contrast exposure of these cells to SC212 and SC210 resulted in increased IL-10, IL-1β, IL-23, and decreased IL-12p40 following activation of the cells with the inflammatory stimulus LPS. Interestingly SC209 and SC229 had little or no effect on cytokine secretion by BMDCs. Overall, our data demonstrates that these novel fermentates have specific effects and can differentially enhance key immune mechanisms that are critical to viral immune responses, or can suppress responses involved in chronic inflammatory conditions, such as Ulcerative Colitis (UC), and Crohn’s disease (CD).

Crop breeding is an important global strategy to meet sustainable food demand. CRISPR-Cas is a most promising gene-editing technology for rapid and precise generation of novel germplasm, and leads to revolutionary crop breeding innovation. In this review, we summarize recent advance of CRISPR/Cas technology in gene function analyses and generation of new germplasms with increased yield, improved product quality, and enhanced resistance to biotic and abiotic stress. We highlight their applications and breakthroughs in agriculture including crop de novo domestication, decoupling the gene pleiotropy tradeoff, crop hybrid seed conventional production, hybrid rice asexual reproduction, and double haploid breeding. Moreover, the challenges and development of CRISPR/Cas technology in crops are also discussed.

Various environmental challenges, related to oil palm commodity has became a major environmental challenge to oil palm production. The aim and objective of this study is to analyze the actual water footprint of oil palm based on root water uptake under varying crop age and soil type. The research was conducted in Pundu Village, Central Kalimantan. The methodology adopted in carrying out this study consists of various stages which includes observing soil moisture, rainfall, and water table, ETo, root water uptake and oil palm water footprint. The highest rate of water consumption was the 13 years oil palm on spodosol soil type with an average daily rate of 3.73 mm/day. The lowest evapotranspiration was represented by the 7th year oil palm on spodosol with an average rate of 3.07 mm/day. The total water footprint value obtained was between 0.56 – 1.14 m3/kg for a variety of plants with various age and soil types. It can be deduced that the water footprint value of oil palm vary for different crop age and soil types on temporal scale. The study also presented that the source of green water from the first root zone of oil palm deliver the highest contribution for oil palm root water uptake.

Glyphosate-based herbicide products are the most widely used broad-spectrum herbicides in the world for post-emergent weed control. There are ever-increasing concerns that glyphosate, if not used judiciously, may cause adverse non-target impacts in agroecosystems. The purpose of this brief review is to present and discuss the state of knowledge with respect to its persistence in the environment, possible effects on crop health, and impacts on crop nutrition.

In recent years, the integration of sensors in agriculture has emerged as a pivotal catalyst for transforming conventional farming practices into precision agriculture. Sensor application is impacting the everyday objects that enhance human life. In this special issue, the main objective was to address recent advantages of sensor application in agriculture covering a wide range of topics in this field. This provides overview of diverse application of sensors in agriculture, highlighting their role in enhancing productivity, sustainability, and resource management. sensors are instrumental in monitoring various agriculture parameter such as soil condition, weather, crop health and livestock wellbeing. By collecting real-time data and providing valuable insight, sensors enable precision farming, optimize resource allocation, and minimize environmental impacts. we have to explore the key sensor types used in agriculture, their applications, benefits, and future prospects, emphasizing their crucial roles in the modernization of agriculture and global quest for food security and crop production.

Alternative splicing (AS) is a gene regulatory mechanism modulating gene expression in multiple ways. AS is prevalent in all eukaryotes including plants. AS generates two or more mRNAs from the precursor mRNA (pre-mRNA) to regulate transcriptome complexity and proteome diversity. Advances in next-generation sequencing, omics technology and bioinformatics tools, and computational methods provide new opportunities to quantify and visualize AS-based quantitative trait variation associated with plant growth, development, reproduction, and stress tolerance. Domestication, polyploidization and environmental perturbation may evolve novel splicing variants associated with agronomically beneficial traits. To date, pre-mRNAs from many genes are spliced into multiple transcripts that cause phenotypic variation for complex traits, both in model plant Arabidopsis and field crops. Cataloguing and exploiting such variation may provide new paths to enhance climate resilience, resource-use efficiency, productivity, and nutritional quality of staple food crops. This review provides insights into AS variation alongside gene expression analysis to select for novel phenotypic diversity for use in breeding programs. AS contributes to heterosis, enhances plant symbiosis (mycorrhiza and rhizobium), and provides a mechanistic link between the core clock genes and diverse environmental clues.

Damage to crops from wildlife interference is a common threat to food security among rural communities in or near Game Management Areas (GMAs) in Zambia. This study uses a two-stage econometric model and cross-sectional data from a survey of 2,769 households to determine the impact of land use planning on the probability and extent of wildlife-inflicted crop damage. The results show that crop damage is higher in GMAs as compared to non-GMAs, and that land use planning could be an effective tool to significantly reduce the likelihood of such damage. These findings suggest that there is merit in the current drive to develop and implement land use plans as means to minimize human-wildlife conflict such as crop damage. This is especially critical as Zambian conservation policies do not have an explicit provision for compensation in the event of damage from wildlife.

Transketolase (TKT) is an essential thiamine diphosphate (ThDP)-dependent enzyme of the non-oxidative branch of pentose phosphate pathway, with the glucose-6P flux through the pathway regulated in various medically important conditions. Here, we characterize the brain TKT regulation by acylation in rats with perturbed thiamine-dependent metabolism, known to occur in neurodegenerative diseases. The perturbations are modelled by administration of oxythiamine inhibiting ThDP-dependent enzymes in vivo, or by reduced thiamine availability in the presence of metformin and amprolium, inhibiting intracellular thiamine transporters. Compared to control rats, chronic administration of oxythiamine does not significantly change the modification level of the two detected TKT acetylation sites (K6 and K102), but doubles malonylation of TKT K499, concomitantly decreasing 1.7-fold the level of demalonylase sirtuin 5. The inhibitors of thiamine transporters do not change average levels of TKT acylation or sirtuin 5. TKT structures indicate that the acylated residues are distant from the active sites. The acylations-perturbed electrostatic interactions may be involved in conformational shifts and/or formation of TKT complexes with other proteins or nucleic acids. Acetylation of K102 may affect the active site entrance/exit and subunit interactions. Correlation analysis reveals that the action of oxythiamine is characterized by significant negative correlations of K499 malonylation or K6 acetylation with TKT activity, not observed upon the action of the inhibitors of thiamine transport. However, the transport inhibitors induce significant negative correlations between the TKT activity and K102 acetylation or TKT expression, absent in the oxythiamine group. Thus, perturbations in the ThDP-dependent catalysis or thiamine transport manifest in the insult-specific patterns of the brain TKT malonylation and acetylations.

Ectopic expression of the MYB transcription factor of AmROSEA1 from Antirrhinum majus has been reported to change anthocyanin and other metabolites in several species. In this study, we found that overexpression of AmRosea1 significantly improved the tolerance of transgenic rice to drought and salinity stress. Transcriptome analysis revealed that a considerable amount of stress-related genes were affected by exogenous AmRosea1 during both drought and salinity stress treatments. These affected genes are involved in stress signal transduction, the hormone signal pathway, ion homeostasis and the enzymes that remove peroxides. This work suggests that the AmRosea1 gene is a potential candidate for genetic engineering of crops.

This research investigates the potential benefits of integrating machine learning algorithms and IoT sensors in modern agriculture. The focus is on optimizing crop production and reducing waste through informed decisions about planting, watering, and harvesting crops. The paper discusses the current state of machine learning and IoT in agriculture, highlighting key challenges and opportunities. It also presents experimental results that demonstrate the impact of changing labels on the accuracy of data analysis algorithms. The findings recommend that by analyzing wide-ranging data collected from farms, including real-time data from IoT sensors, farmers can make more informed verdicts about factors that affect crop growth. Eventually, the integration of these technologies can transform modern agriculture by increasing crop yields while minimizing waste. In our studies, we achieve a classification accuracy of 99.59% using the Bayes Net algorithm and 99. 46% using Naïve Bayes Classifier, and Hoeffding Tree algorithms. Our results indicate that we achieved high accuracy results in our experiments in order to increase crop growth.

Crop-type mapping is an important intermediate step for cost-effective crop management at the field level, as an overview of all fields with a particular crop type can be used for monitoring or yield forecasting, for instance. Our study used a data set with 2400 fields and corresponding satellite observations from the federal state of Bavaria, Germany. The study classified corn, winter wheat, winter barley, sugar beet, potato, and winter rapeseed as the main crops grown in Upper Bavaria. We additionally experimented with a rejection class "Other", which summarised further crop types. Corresponding Sentinel-2 data included the normalised difference vegetation index (NDVI) and raw bands from 2016 to 2018 for each selected field. The influence of raw bands compared to NDVI was analysed and the classification algorithms, i.e. support vector machine (SVM) and random forest (RF), were compared. The study showed that the use of an index should be critically questioned and that raw bands provided a wider spectral bandwidth, which significantly improved the mapping of crop types. The results underline the use of RF with raw bands and achieved overall accuracies (OA) of up to 92%. We also predicted crop types in an unknown year with significantly different weather conditions and several months before the end of the growing season. Thus, the influence of climate anomalies and the accuracy depending on the time of prediction were assessed. The crop types of a test site and year without labels could be determined with an OA of up to 86%. The results demonstrate the usefulness of the proof-of-concept and its readiness for use in real applications.

Empirical models help us understand the process of plant residue decomposition and nutrient release into the soil. The objective of this study was to determine an appropriate model to describe the decomposition of hairy vetch (Vicia villosa Roth) and cereal rye (Secale cereale L.) cover crop (CC) residue and nitrogen (N) release. Data pertaining to above and belowground CC residue mass loss and N release for up to 2633 cumulative decomposition degree days (112 d) after litterbag installation were obtained from two cropping system experiments, one conducted in 2015 and the other in 2017 and 2018 at the humid subtropical environment of southern IL, USA. Six exponential and two hyperbolic models were fit to percent mass and N remaining data to find the one with minimum Akaike Information Criterion (AIC) and residual sum of squares. Modified three-parameter single exponential and two- or three-parameter hyperbolic models best met the assumed criteria of selection for above and belowground CC residue, respectively. Fitting a double exponential model to a combined data for percent mass and N remaining, which identified two mass and N pools, a fast and a slow pool with different rate constants. A five-parameter double exponential with an asymptote met the preset criteria and passed all tests for normally distributed population, constant variance, and independence of residuals at α = 0.05 when fit to combined data of hairy vetch shoot mass and N remaining. However, a two-parameter hyperbolic and three-parameter asymptotic hyperbolic model provided the best fit to a combined data of cereal rye shoot mass and N remaining, respectively. Both hyperbolic decay models showed a good fit for belowground mass decomposition and N release for both CCs. Cereal rye had poorer fit than hairy vetch for mass and N remaining of both above and belowground mass. The best-selected decay models can be used to estimate the decomposition and N release rates of hairy vetch and cereal rye above and belowground residue in a similar environment.

Deep learning is widely used in image segmentation, effectively identifying crops and weeds and contributing to the reduction of herbicide use. Traditional methods of applying pesticides over large areas are inefficient in dealing with weeds as needed, leading to massive waste of pesticides, high-cost production, and serious environmental pollution. This affects crop yield and quality. Although weed recognition using conventional deep learning methods has evolved over time, there are still challenges in weed extraction, detection, and segmentation. Accurate recognition and detection of weeds are essential prerequisites for implementing variable spraying. This paper proposes a semantic segmentation method based on UNet++ for complex environments where accurate identification of plants and weeds is challenging, targeting weeds in sugar beets, peas, and rice. An attention module is integrated into the upsampling process of UNet++, and UNet++ is used as a backbone network to effectively integrate multi-scale information, efficiently suppressing external noise interference. The UNet++ model with an integrated attention mechanism module achieves higher IOU than the general UNet++ model used in medical image analysis. This method effectively detects crops and weeds in complex backgrounds, providing reference material for the accurate application of robotic herbicides.

Climate change and the increasing frequency of high-temperature events are significant threats to global crop yields. To address this, a comprehensive understanding of how plants respond to heat shock (HS) is essential. Signaling pathways involving calcium (Ca2+), a versatile second messenger in plants, encode information through temporal and spatial variations in ion concentration. Ca2+ is detected by Ca2+-sensing effectors, including channels and binding proteins, which trigger specific cellular responses. At elevated temperatures, the cytosolic concentration of Ca2+ in plant cells increases rapidly, making Ca2+ signals the earliest response to HS. In this review, we discuss the crucial role of Ca2+ signaling in raising plant thermotolerance and we explore its multifaceted contributions to various aspects of the plant HS response.

Crop genetic diversity is most for the long-term sustainable production system. The breeding and production strategies of developing and growing uniform and homogenous varieties have created many different problems. Such populations are static and very sensitive to unpredictable stresses. In Nepal, more than 80% of seed system is informal s which has contributed greatly to creating and maintaining genetic diversity within the field particularly contributing to landrace diversity. This paper aims to assess and present the approaches and advantages of increased crop genetic diversity in the fields. The paper is developed based on experiences of implementing on-farm conservation activities carried out in Nepal since last two decades. Some of the evidences have been derived from on-going evolutionary plant breeding project being implemented in Nepal. The information is supplemented with field assessment, focus group discussion, and literature review. The major approaches to increase crop genetic diversity are evolutionary plant breeding, cultivar mixture, landrace enhancement, informal seed system, bulk method, diversifying the sources, participatory plant breeding, open pollination, etc. EPB and cultivar mixture are very simple and effective approaches to increase crop genetic diversity at field level. The involvement of farmers in these approaches helps to accelerate the population improvement particularly for landraces. The major advantages of increased crop genetic diversity are: seed maintenance by farmers themselves, minimal risk of crop failure, resilience to unpredictable stresses, increased amount of diversified nutrition, production increment each year, ease to produce organically, etc. However, there are some issues and problems associated with mixtures and diverse varieties, for example, not being able to harvest by machine, mature at a different date, difficulty in maintaining seeds and registration, etc. Crop genetic diversity should be considered for a climate-resilient and self-dependent production system. The higher the genetic diversity in farming land, the more chance of getting the multiple benefits in the agriculture system (Vernooy 2022).

Sustainable agricultural production is endangered by several ecological factors such as drought, extreme temperatures, excessive salts, parasitic ailments, and insect pest infestation. These challenging environmental factors may have adverse effects on future agriculture production in many countries. In modern agriculture, conventional crop breeding techniques alone are inadequate for achieving the increasing population’s food demand on a sustainable basis. The advancement of molecular genetics and related technologies are promising tools for the selection of new crop species. Gene pyramiding through marker assisted selection (MAS) and other techniques have accelerated the development of durable resistant/tolerant lines with high accuracy in the shortest possible period of time for agricultural sustainability. Gene stacking has not been fully utilized for biotic stress resistance development and quality improvement in most of the major cultivated crops. This review emphasizes on gene pyramiding techniques that are being successfully deployed in modern agriculture for improving crop tolerance to abiotic and biotic stresses for sustainable crop improvement.

Agriculture and farming worldwide are responsible for numerous environmental threats, including degradation of land and water resources depletion. Underlining the dynamic interaction between bio-physical and socio-economic drivers is the key towards a more sustainable land and water management. With regard to a highly developed agricultural area in southern Italy, multi-regression models were developed to interpret the observed inter-annual variability of cropped land. Main drivers related to Common Agricultural Policy support, product market prices, crop yield and irrigation water availability were investigated. The adopted models revealed the different weighs of each driver. The findings reported the role that direct payments played in supporting the extension of irrigated crops, such as processing tomato. Likewise, the models pointed to decoupled payment scheme as the most important driver of change in the crop pattern over the last years.

Maintaining sufficient levels of plant nutrients in the soil and controlling certain heavy metals, which can be toxic to the environment, are critical to ensure sustainable agricultural production. The study aimed to assess the linkage of crop-specific agricultural practices established by farmers in the Kvemo Kartli region (Georgia) with metal accumulation in soils of agricultural lands being subject to influence from polluted irrigation water in the past. In particular, we tried to identify the primary sources of micronutrients, including iron (Fe), copper (Cu), manganese (Mn), nickel (Ni), and zinc (Zn), and toxic elements such as cadmium (Cd) and lead (Pb), and share of the contaminated irrigation water and other factors related to agricultural practices under different land uses, such as intensive and extensive arable farming, vineyards, orchards, and permanent pastures having the least disturbed soil. Based on principal component analysis, five primary sources were identified and categorized according to farmers' interviews and previous studies conducted in the region. The results showed that increased concertation of plant-available Cu, Zn, Cd and Pb were mainly associated with irrigation water and intensive use of fungicides; Fe, Mn, and Ni were closely linked to several factors, such as the mineralogical composition of soils, mineral and organic fertilizers inputs, and atmospheric deposition from diffuse sources, where exhausts from transport are probably the primary source. During our study, we attempted to differentiate irrigation water inputs from fungicides using simulation based on irrigation pattern and irrigation water quality on the one hand and fungicide application rate and their metal content on the other. The simulation revealed that the intensive application of fungicides, especially in vineyards, is more significant in enriching soils with Cu and Zn than irrigation water. Identification of factorial dependences was supported by statistical analysis and application of a number of contamination assessment methods: Contamination Factor (CF), Pollution Load Index (PLI), single-factor Pollution Index (PI), Nemerow’s comprehensive pollution index (PIN), Enrichment Factor (EF), and Geo-Accumulation Index (Igeo). Applied environmental indices indicate that the soils under the former and existing vineyards are the most enriched with Cu and Zn, highlighting the significance of agricultural practices on heavy metals accumulation in soils of agricultural lands.

A growing body of research has examined farmers' increasing economic challenges in the United States and the new models adopted to increase profit, remain in business, and achieve agricultural sustainability. However, the entrepreneurial strategies that western corn (Zea mays) belt farmers use to overcome economic challenges and achieve agricultural sustainability remain understudied. The model system used in this study was eastern South Dakota, and it examined the entrepreneurial aspirations of commodity crop producers using mail and online survey data collected in 2018. Using the diffusion of innovations framework, we investigated how innovation and entrepreneurialism spread among farmers, whether frequent training, building, and using social networks were essential to farmers' business success, and how age, education level, and farm size relate to their entrepreneurial aspirations. We analyzed these three socio-demographic characteristics of farmers against their adoption of entrepreneurship and engagement in networking and training. Our results show that: 1) farmers are looking for ways to adopt entrepreneurship; 2) education and farm size were positively related to the adoption of entrepreneurship; 3) age was negatively related to farmers' adoption of entrepreneurship, and 4) larger farm size is associated with farmers' use of social networks and participation in training. This study emphasizes the need to train farmers, equip them with entrepreneurial skills, maximize their utilization of social networks and opportunities, and encourage them to adopt strategic planning and best management practices.

About a decade ago, active optical crop canopy sensors are being used to manage in-season variable nitrogen (N) fertilization in cornfields to match the plant demand that occurs mid season, increasing the efficiency compared to broadcast N applications. There were also initiatives of using ultrasonic sensors to measure plant height on-the-go for N application and crop water demand estimation, but no studies have integrated the optical, ultrasonic and canopy temperature for crop water stress assessment. The objective of this chapter is to evaluate the crop water status using infrared thermometry integrated with optical and ultrasonic sensors. Specifics objectives are: (i) evaluate the corn canopy temperature under different previous crop, N rates and irrigation levels; (ii) test a procedure for water stress assessment in commercial cornfields using the integration of sensors, (iii) correlate plant based sensor measurements (N status, plant height and canopy temperature) with grain yield, soil attributes and detailed topographical features, and (iv) study the spatial dependence of canopy temperature. This study was conducted in one small plot study area and on three producer’s fields in 2010. The small plot experiment consisted of two irrigation levels (70 and 100% of evapotranspiration – ET), two previous crop schemes (corn after corn – CC and corn after soybeans – CS), and four N rates (0, 75, 150, 225 kg N ha^-1). Canopy temperature, optical reflectance and plant height was measured from R2 until R6 in the small plots. At the producer’s fields, three long strips across center pivots were used to have a non-limited N and water crop and then continuous georeferenced sensors measurements were taken during side-dress (V11 growth stage) in about 10 hectares in each field. In the small plot study the crop canopy temperature was influenced by the irrigation levels and N rates. The procedure proposed could be used to identify zones in the producer’s field where water stress can be a yield limiting factor other than N derived. Inside the zones considered that water stress played a major whole, there were low correlations between plant height, plant N status and canopy temperature, indicating that the canopy temperature had more influence from water stress than vegetation cover. Concave and lower elevation areas had higher yields compared to convex and high elevation, showing that the detailed elevation mapping can be beneficial to delineate stables zones that possibly could be used in variable irrigation systems. The spatial dependence of canopy temperature was over 65 meters across producers’ sites, showing that the commercial high clearance applicator’s swath width was adequate to obtain accurate maps. The integration of plant N status, plant height and canopy temperature was beneficial to detect water stressed zones in the field. Opportunities can be foresee also for on-the-go N fertilization using integration of these sensors because is likely that water stress can be confounded with different N supply during the growing season and in different zones in the field.

Weeds are among the major constraints to any crop production system, reducing productivity and profitability. Herbicides are among the most effective methods to control weeds, and reliance on herbicides for weed control has increased significantly with the advent of herbicide-resistant crops. Unfortunately, over-reliance on herbicides leads to environmental-health issues and herbicide-resistant weeds, causing human-health and ecological concerns. Crop diversification can help manage weeds sustainably in major crop production systems. It acts as an organizing principle under which technological innovations and ecological insights can be combined to manage weeds sustainably. Diversified cropping can be defined as the conscious inclusion of functional biodiversity at temporal and/or spatial levels to improve the productivity and stability of ecosystem services. Crop diversification helps to reduce weed density by negatively impacting weed seed germination and weed growth. Additionally, diversified farming systems are more resilient to climate change than monoculture systems and provide better crop yield. However, there are a few challenges to adopting a diversified cropping system, which ranges from technology innovations, government policies, farm-level decisions, climate change, and market conditions. In this review, we discuss how crop diversification supports sustainable weed management, the challenges associated with it, and the future of weed management with respect to the diversification concept.

Plant breeding conventionally depends on genetic variability available in a species to improve a particular trait in the crop. However, epigenetic diversity may provide an additional tier of variation. The recent advent of epigenome technologies has elucidated the role of epigenetic variation in shaping phenotype. Further, the development of epigenetic recombinant inbred lines (epi-RILs) in the model species such as Arabidopsis has enabled accurate genetic analysis of epigenetic variation. Subsequently, mapping of epigenetic quantitative trait loci (epiQTL) allowed association between epialleles and phenotypic traits. Thus, quantitative epigenetics provides ample opportunities to dissect the role of epigenetic variation in trait regulation, which can be eventually utilized in crop improvement programs. Moreover, locus-specific manipulation of DNA methylation by epigenome-editing tools such as clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) can facilitate epigenetic based molecular breeding of important crop plants.

Chronic stress is a major risk factor for various psychiatric diseases, including depression; it induces a range of cellular and structural adaptations, culminating in altered neurocircuitry and subsequent depression. Accumulating evidence suggests that microglial cells orchestrate stress-induced depression. Preclinical studies of stress-induced depression revealed microglial inflammatory activation in regions of the brain that regulate mood. Although studies have identified several molecules that trigger inflammatory responses in microglia, the pathways that regulate stress-induced microglial activation remain unclear. Understanding the exact triggers that induce microglial inflammatory activation can help find therapeutic targets to treat depression. In the current review, we summarize the recent literature on possible sources of microglial inflammatory activation in animal models of chronic stress-induced depression. In addition, we describe how microglial inflammatory signaling affects neuronal health and causes depressive behavior. Finally, we propose ways to target the microglial inflammatory cascade to treat depressive disorders.

Climate change poses a serious threat to global agricultural activity and food production. To address this issue, plant genome editing technologies have been developed to provide an alternative solution for crop improvement. Unlike conventional breeding techniques (e.g., selective breeding and mutation breeding), modern genome editing tools offer more targeted and specific alterations of the plant genome to produce crops with desired traits, such as higher yield and/or stronger resilience to the changing environment. In this review, we discuss the current development and future applications of genome editing technologies in mitigating the impacts of biotic and abiotic stresses on agriculture. We focus specifically on the CRISPR/Cas system, which has been the center of attention in the last few years as a revolutionary genome-editing tool in various species. We also conducted a bibliographic analysis on CRISPR-related papers published from 2012 to 2021 (10 years) to identify trends and possible gaps in the CRISPR/Cas-related plant research. In addition, this review article outlines the current shortcomings and challenges of employing genome editing technologies in agriculture with notes on future prospective. We believe combining conventional and more innovative technologies in agriculture would be the key to optimizing crop improvement beyond the limitations of traditional agricultural practices.

Over the past few decades, there have been major advances in crop productivity across the world, which has been made possible through a combination of productivity enhancing technological innovations. Beyond this achievement however, most parts of Africa are still battling with low crop productivity resulting in food shortages and food insecurity. The yields of many staple crops are still far below their agronomic potentials with output increases being attributed largely to area expansion. This paper examines the implications of the current trends of crop/plant productivity for food security and rural livelihood development in Africa using Ghana as a case study. The paper argues that crop production in Africa is becoming a less viable and unattractive livelihood activity with farmers diversifying out of agriculture into non-agricultural activities such as illegal small-scale mining, which have negative consequences on the ability of African countries to attain the Sustainable Development Goals (SDGs).

Farming systems prevalent in sub-Saharan Africa are exposed and vulnerable to climate change due to their high dependence on rainfall. However, most studies have only estimated the impacts of climate change on agricultural productivity at a regional or national level. We add to this literature by focussing on the sub-national impacts. This study uses 30 years (1981–2011) of yield and weather data in Zambia and applies the Just and Pope model to determine how rainfall and temperature affect yield and yield variability of maize and beans at the national and subnational levels. Results show a negative impact of temperature rise on yield and a positive impact of rainfall rise on yield, above the current mean levels. These results differ by agro-ecological region. Worst-case-scenario predicted impacts using HadGEM-ES2 global circulation model show that major yield decreases (25% for maize and 34% for beans) by 2050 will be in region II and will be driven mainly by temperature increase offsetting the positive gains from rainfall increase. The model mainly under-predicts yield for maize and overpredicts yield for beans. These findings call for agro-ecological region-specific adaptation strategies and well-planned policy interventions to make agriculture more resilient to climate change.

This study evaluated the using of machine vision in combination with deep learning to identify weeds in real-time for wheat production system. PMAS-Arid Agriculture university research farm were selected for collection of images (6000 total images) of weeds and wheat crops under different weather condition. During growing season, the database was constructed to identify the weeds. For this study two framework were used TensorFlow and PyTorch under CNNs and Deep learning. Deep learning perfromed better with in PyTourch value as compared to another model in Tensorflow. comparing with other networks such as YOLOv4, we concluded that our network reaches a better result between speed and accuracy. Specifically, the maximum precision of weed and wheat plants were 0.89 and 0.91 respectively with 9.43 ms and 12.38 ms inference time per image (640 × 640) NVIDIA RTX2070 GPU.

Faba bean (Vicia faba L.), a member of the Fabaceae family, is one of the important food legumes cultivated in cool temperate regions. It holds great importance for human consumption and livestock feed because of its high protein content, dietary fibre, and nutritional value. Major faba bean breeding challenges include its mixed breeding system, unknown wild progenitor, and genome size of ~13 Gb, which is the largest among diploid field crops. The key breeding objectives in faba bean include improved resistance to biotic and abiotic stress and enhanced seed quality traits. Major progress on reduction of vicine-convicine and seed coat tannins, the main anti-nutritional factors limiting faba bean seed usage, have been recently achieved through gene discovery. Genomic resources are relatively less advanced compared to other grain legume species, but significant improvements are underway due to a recent significant increase in research activities. A number of bi-parental populations have been constructed and mapped for targeted traits in the last decade. Faba bean now benefits from saturated synteny‐based genetic maps, along with next-generation sequencing and high-throughput genotyping technologies that are paving the way for marker-assisted selection. Developing a reference genome, and ultimately a pan-genome, will provide a foundational resource for molecular breeding. In this review, we cover the recent development and deployment of genomic tools for faba bean breeding.

Prediction of crop yield is essential for food security policymaking, planning, and trade. The objective of the current study is to propose novel crop yield prediction models based on hybrid machine learning methods. In this study, the performance of artificial neural networks-imperialist competitive algorithm (ANN-ICA) and artificial neural networks-gray wolf optimizer (ANN-GWO) models for the crop yield prediction is evaluated. According to the results, ANNGWO, with R of 0.48, RMSE of 3.19, and MEA of 26.65, proved a better performance in the crop yield prediction compared to the ANN-ICA model. The results can be used by either practitioners, researchers or policymakers for food security.

Abstract: Brassinosteroids (BR) are essential plant hormones that play a crucial role in regulating plant growth and development, as well as their resistance to abiotic and biotic stresses, including pathogen infections. In the context of plant im-munity, BR influence various processes such as the expression of genes related to pathogen defense, the production of antimicrobial compounds, and the re-inforcement of the plant cell structure. The aim of work is understand the role of BR in plant defense against abiotic and biotic stresses. BR are involved in the regulation of metabolic processes, water economy, and photosynthesis, contributing to increased plant resistance to abiotic stresses. The study discusses various mechanisms of BR action on plant immunity, including the regulation of gene expression related to defense, activation of the plant defense system, in-teraction with other plant hormones, regulation of water and salt balance, and influence on photosynthetic processes. In the context of plant immunity, BR influence various processes, including the expression of genes related to pathogen defense, the production of antimicrobial compounds, and the reinforcement of the plant cell structure. Additionally, BR are involved in the regulation of metabolic processes, water economy, and photosynthesis, con-tributing to increased plant resistance to abiotic and biotic stresses. The paper emphasizes the importance of further research on the role and mechanisms of action of BR in plant immunity, which may contribute to the development of more effective strategies for the use of BR in agriculture, horticulture, and plant protection.

Reef-dwelling calcifiers face numerous environmental stresses associated with anthropogenic carbon dioxide emissions, including ocean acidification and warming. Photosymbiont-bearing calcifiers, such as large benthic foraminifera, are particularly sensitive. To gain insight into their resistance and adaptive mechanisms to climate change, Amphistegina lobifera from the Gulf of Aqaba were cultured under elevated pCO2 (492, 963, and 3182 ppm) fully-crossed with elevated temperature (28°C and 31°C) for two months. Differential protein abundances in host and photosymbionts amongst treatments were investigated alongside physiological responses and microenvironmental pH variations. Over 1000 proteins were identified, of which one-third varied significantly between treatments. Thermal stress induced protein depletions, along with reduced holobiont growth. Elevated pCO2 caused only minor proteomic alterations and color changes. However, combined stressors reduced pore sizes and increased microenvironmental pH, indicating adaptive modifications to gas exchange. Notably, substantial proteomic variations at moderate-pCO2 and 31°C indicate cellular stress, while stable physiological performance at high-pCO2 and 31°C is scrutinized by putative decreases in test stability. Our experiment shows that the effects of climate change can be missed when stressors are assessed in isolation, and that physiological responses should be assessed across organismal levels to make more realistic predictions for the fate of reef calcifiers.

Carbohydrate and menthol mouth-swilling have been used to enhance exercise performance in the heat. However, these strategies differ in mechanism and subjective experience. Participants (n=12) sat for 60 min in hot conditions (35°C; 15±2%), following a 15 min control period, participants undertook three 15 min testing blocks. A randomised swill (Carbohydrate; Menthol; Water) was administered per testing block (one swill every three minutes within each block). Heart rate, tympanic temperature, thermal comfort, thermal sensation and thirst were recorded every three minutes. Data were analysed by ANOVA, with carbohydrate intake controlled for via ANCOVA. Small elevations in heart rate were observed after carbohydrate (ES: 0.22 ± 90% CI: -0.09 to 0.52) and water swilling (0.26; -0.04 to 0.54). Menthol showed small improvements in thermal comfort relative to carbohydrate (-0.33; -0.63 to 0.03) and water (-0.40; -0.70 to -0.10), and induced moderate reductions in thermal sensation (-0.71; -1.01 to -0.40 and -0.66; -0.97 to -0.35, respectively). Menthol reduced thirst by a small to moderate extent. These effects persisted when controlling for dietary carbohydrate intake. Carbohydrate and water may elevate heart rate, whereas menthol elicits small improvements in thermal comfort, moderately improves thermal sensation and may mitigate thirst; these effects persist when dietary carbohydrate intake is controlled for.

The health benefits of extra virgin olive oil (EVOO) are related with its chemical composition and the presence of bioactive compounds with antioxidant properties. The aim of this study was evaluate antioxidant compounds (pigments, CoQ10 and phenolic compounds) and antioxidant properties of EVOO from the same region comparing different cultivars (Hojiblanca and Arbequina), harvest year and crop stage. Antioxidant properties of oils were studied before and after a gastrointestinal digestion process, by in vitro assays (DPPH, ABTS and FRAP) and antioxidant markers in Caco-2 cells (reactive oxygen species production). The content of bioactive compounds measured was significantly affected by cultivar and harvest year (except for carotenoids) and by the crop stage (except for coenzyme Q10). Higher amount of coenzyme Q10 was observed in Hojiblanca than in Arbequina EVOO. Total phenol content and antioxidant properties were also different depending on cultivar and harvest year and the in vitro digestion process strongly improved antioxidant marker values. Antioxidant potential in bioaccessible fractions was mainly related with content of coenzyme Q10 and phenolic compounds in EVOO. Chemometric analysis showed that the oils were clearly classified by cultivars, harvest and crop stage, according with chemical composition and antioxidant activity analyzed in the present study

Plant transcriptomes are an extremely dynamic entities shaped spatially and temporally by many intracellular and environmental cues. In this review, we first summarize the complexity and diversity of plant genomes and transcriptomes as a start point for the multitude of transcriptomic responses. Numerous alterations within various tissue and organ-specific transcriptomes as well as the most relevant transcriptomic responses associated with plant acclimation to selected abiotic and biotic stress conditions, from the current studies employing high-throughput transcriptomic analysis are widely discussed. Understanding changes within plant transcriptomes, revealed by in silico functional analysis, allows for the characterization of stress-affected genes and stress acclimatory mechanisms, as well as allows to perform plant metabolic engineering. The latter allow cultivars to produce more secondary metabolites in the future, which are often desirable substances in the biomedical industry. Accordingly, in this review special attention was also paid to characterize the potential of transcriptomic analyses of medicinal species, particularly to search for new cultivars. Extensive characterization of transcriptomic responses in stress would also result in the development of new cultivars that display physiological and molecular mechanisms that allow them to cope with adverse environmental conditions more adequately.

Salmonella is the intracellular pathogen and etiological known for the cause of asymptomatic carriage, gastroenteritis, systemic disease (typhoid fever), in severe cases death may also occur. Altered function of mitochondria due to Salmonella infection impacts the immune response. Mitochondria which are recognized as the “powerhouse” of the cells are also know to play central role in the immune metabolism. Mitochondrial dynamics such as fusion, fission, signaling, transport and mitophagy influences the immune system and also maintains the cellular integrity. Mitochondrial DNA and Reactive oxygen species formation also elicits the inflammatory responses. This review discusses the immune metabolism and effect of altered mitochondrial dynamics in case of Salmonella infection.

Maize (Zea mays L.) stands as one of the most extensively cultivated crops globally, offering significant contributions to food, animal feed, and biofuel production. Maize yield is significantly impacted by diverse climate and soil variables, yet its productivity faces hindrances due to abiotic stresses, including drought, salinity, extreme temperatures, and cold conditions. In confronting these hurdles, the field of crop breeding has undergone a transformation thanks to high-throughput sequencing technologies (HSTs). These advancements have streamlined the identification of beneficial quantitative trait loci (QTL), associations between markers and traits (MTAs), as well as genes and alleles that contribute to crop improvement. Presently, well-established omics techniques such as genomics, transcriptomics, proteomics, and metabolomics are being amalgamated into maize breeding studies. These approaches have unveiled new biological markers that are being employed to bolster maize's capacity to withstand an array of challenges. In this chapter, we explore the current knowledge regarding the morpho-physiological and molecular mechanisms that underlie the resistance and tolerance of maize to biotic and abiotic stresses. The focus is on utilizing omics techniques to augment maize's ability to withstand these challenges. Moreover, it emphasizes the significant potential of integrating various omics techniques to tackle the challenges presented by biotic and abiotic stress in maize productivity, contrasting with singular approaches.

Droughts occurring more and more frequently in recent years are usually associated with progressive climate changes. Modern monitoring methods is mainly associated with agricultural use due to the high market demand for services protecting against agricultural losses. In natural wetland ecosystem this problem is neglected which is probably due to fact that this are ecosystems rich in water by definition. Nevertheless this droughts might become a problem of wetlands, whose good condition depends on adequate hydration. Therefore this study focused on determination Crop Water Stress Index (CWSI) for natural heterogeneous wetland habitats. CWSI based on remotely sensed land surface temperature and associated basic meteorological (air temperature and humidity) measurements. CWSI was calculated based on high resolution LST measurements from UAV platform and compare with on ground measurements of soil moisture, CCI, fAPAR and meteorological conditions. Results shows that CWSI properly shows water condition of plants in measured habitats and revels high importance of metrological conditions during data acquisition.

Background: In this investigation, we explored the effects of pharmacological cholinergic stimulation on cardiac function and renal inflammation following acute myocardial infarction (AMI) in spontaneously hypertensive rats (SHRs). Methods: Adult male SHRs were randomized into three experimental groups: sham-operated; AMI+Veh (infarcted, treated with vehicle); and AMI+PY (infarcted, treated with the cholinesterase inhibitor pyridostigmine bromide (PY) - 40 mg/kg, once daily for seven days). Rats were euthanized 7 or 30 days post-surgery. Clinical parameters were assessed on the day before euthanasia. Subsequent to euthanasia, blood samples were collected and renal tissues were harvested for histological and gene expression analyses aimed to evaluate inflammation and injury. Results: Seven days post-surgery, the AMI+PY group demonstrated improvements in left ventricular diastolic function and autonomic regulation, and a reduction in renal macrophage infiltration compared to the AMI+Veh group. Furthermore, there was a notable downregulation of pro-inflammatory gene expression and an upregulation of anti-inflammatory gene expression. Analysis 30 days post-surgery showed that PY treatment had a sustained positive effect on renal gene expression, correlated with a decrease in biomarkers indicative of subclinical kidney injury. Conclusion: Short-term cholinergic stimulation with PY provides both cardiac and renal protection by mitigating the inflammatory response after AMI.

Abiotic stresses extensively reduce agricultural crop production globally. Traditional breeding approaches have been widely used to mitigate the risks of abiotic stresses. The discovery of gene editing technology for modifying stress-responsive genes and associated molecular networks has paved the foundation for sustainable crop management against environmental stress. Integrated approaches based on functional genomics and transcriptomics are now expanding the opportunities to elucidate the molecular mechanisms underlying abiotic stress responses. This review summarizes some of the features and weblinks of plant genome databases related to abiotic stress genes utilized for crop improvement. Clustered, regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas) based gene-editing tool has revolutionized stress tolerance research due to its simplicity, versatility, adaptability, flexibility, and broader applications. However, off-target and low cleavage efficiency hinder the successful application of CRISPR/Cas systems. Computational tools have been developed for designing highly competent gRNA with better cleavage efficiency. This powerful genome editing tool offers tremendous crop improvement opportunities, overcoming conventional breeding techniques' shortcomings. Furthermore, we also discuss the mechanistic insights of the CRISPR/Cas9-based genome editing technology. This review summarizes the current advances in understanding plant species' abiotic stress response mechanism and applying the CRISPR/Cas system genome editing technology to develop crop resilience against drought, salinity, temperature, heavy metals, and herbicides.

Crop disease classification has always been a critical and persistent problem in the field of agricultural and forestry sciences, where often we do not have access to a sufficient number of samples to know the distribution of real-world samples. How to make full use of the existing data is the starting point of our thinking. To address this problem, this paper proposes a supervised image augmentation method Negative Contrast, which uses the contrast images of existing disease samples after removing disease areas as negative samples for image augmentation when samples are relatively scarce. Numerous experiments have shown that several classical models using this augmentation method have improved in disease classification of four crops, rice, wheat, corn, and soybean, with a maximum accuracy improvement of 30.8%. In addition, the comparative analysis of attentional heat map shows that the model using Negative Contrast is more accurate and intense on the area of interest of diseases, and thus reflects better generalization ability in real-world disease classification. Our dataset and codes can be found in https://www.kaggle.com/datasets/w970704112/corn-wheat-rice-soybean and https://github.com/hiter0/contrastaug .

A field experiment was conducted at farmer field of Sundarbazar, Lamjung during rainy season of 2020 with an objective to determine the dynamics of weed with respect different planting methods and varieties. The experiment was laid out in split plot design with three replications where five Varieties (KabreKodo 1, KabreKodo 2, Dalle 1, Okhale 1 and local) were used as the main plot factor and three planting methods (Direct sowing;10*10cm, Conventional transplanting;10*10 cm with 15 days old seedlings and System of Crop Intensification;25*25 cm with 30 days old seedlings) as sub plot factor. Result showed that among 5 genotypes of weeds based on Importance value index, Cyperusrotundus was the most dominant during the initial stage but after the first weeding, Aegeratumhaustinianum dominated the field. Weed biomass and density was recorded highest in directly sown field than that in transplanted field. Among the transplanted crop, weed infestation was seen higher in SCI than in conventionally transplanted finger millet due to wider spacing. But after the first hand weeding, due to profuse root growth and tillering in SCI, weeds were suppressed and thus weed biomass was observed higher in CT. After one hand weeding, SCI showed higher weed control index, crop resistance index and planting method efficiency index in terms of yield. Weed infestation was observed higher in Dalle 1 among varieties.

The most striking and dramatic catastrophe, as on April 2020, is - COVID - 19. Understanding of the COVID-19, the causing agent- the virus and the resultant causalities are still evolving. Till now, there is no specific treatment, no vaccine for the COVID-19. At this stage, what is utmost important now to face the disaster is to put emphasis on the preparedness and responses: research to discover vaccine, antivirals as soon as possible. Till then, it is necessary to put emphasis on infection preventive and control measures like to avoid close contact of infected people showing symptoms of respiratory diseases, hand hygiene and coughing etiquette. To make the infection preventive and control measures a success, the followings are to make success: ‘quarantine’ ‘isolation’, ‘travel bans’, ‘cordon sanitaire’ and ‘social distancing’ measures. The tools of modern information technology could help the authority to manage and monitor the preventive measures. Above all, preventive and control measures will not be successful if we fail to make aware the common people about the fatality of the COVID - 19. So, rapid preparedness and responses to COVID-19 are critically essential to face such disaster. Not a single moment is to waste!

The spillover of the terrorist activities of Boko Haram, a Nigerian jihadi group, into Cameroon’s northern region has resulted in security challenges and humanitarian activity opportunities for Christian churches. The insurgents have attacked and destroyed churches, abducted Christians, worsened Muslim-Christian relations, and caused a humanitarian crisis. Aggregately, these ensuing phenomena have adversely affected Christian churches in this region, triggering an aura of responses: coping strategies, humanitarian work among refugees, and inter-faith dialogue. These responses are predicated on Christianity’s potential as a resource for peace, compassion, and love. In this study we emphasize the role of Christian churches in dealing with the Boko Haram insurgency. It opens up with a contextualization of Boko Haram in Cameroon’s north. This is followed by an examination of the brutality meted out on Christians and church property. The final section is an examination of the spiritual, humanitarian and relief services provided by Christian churches. The paper argues that although Christian churches have suffered at the hands of Boko Haram insurgents, they have engaged in various beneficial responses underpinned by the Christian values of peace and love.

Ebola virus is a zoonotic virus comprised of 6 different species designated within the family Filoviridae and genus Ebolavirus. The first recorded outbreak of an Ebola virus (EBOV) was in Yambuku, Zaire (ZEBOV) in 1976, followed by Sudan Ebola virus (SUBOV) later that year. Outbreaks have been increasing throughout the 21st century, and mortality rates can reach up to 90%. Such extraordinary virulence is evidenced with few pathogens, similarly with Marburg virus (MARV) that originated in Uganda and was first detected in Germany in 1967. The virulent nature of filovirus disease has established these related viruses as a formidable global concern. There are currently four types of Ebolaviridae species known to infect humans, with two more recently identified in other animals that are genomically different with respect to cellular pathogenesis or aetiology of disease. Recent advances into understanding the pathogenesis of filovirus disease infections have been remarkable, yet the immunological response to filovirus infection remains unknown. Scientific analysis of cellular mechanisms can provide insight into virulence factors utilised by other pathogenic viruses that also cause febrile illness with occasional haemorrhagic fever in humans. In this review, we aim to provide a brief summary of EBOV proteins and the role of innate and adaptive immune cells known since 2000. We will consider the relevance and implications of immunological proteins measured by CD marker, alongside cytokine, chemokine and other biologically relevant pathways, as well as genetic research. Thorough understanding of immunological correlates affecting host responses to Ebola viruses will facilitate both clinical and applied research knowledge, contributing towards protection against potential public health threats.

Inspired by the reflective and deliberative control mechanisms used in cognitive architectures such as SOAR and Sigma, we propose an alternative decision mechanism driven by architectural appraisals allowing robots to overcome impasses. The presented work builds on and improves on our previous work on a generally applicable decision mechanism with roots in the Standard Model of the Mind and the Generalized Cognitive Hour-glass Model. The proposed decision mechanism provides automatic context-dependent switching between exploration-oriented, goal-oriented, and backtracking behavior, allowing a robot to overcome impasses. A simulation study of two applications utilizing the proposed decision mechanism is presented demonstrating the applicability of the proposed decision mechanism.

Genome-wide epigenetic changes in plants are being reported during the development and environmental stresses, which are often correlated with gene expression at the transcriptional level. Sum total of the biochemical changes in nuclear DNA, post-translational modifications in histone proteins and variations in the biogenesis of non-coding RNAs in a cell is known as epigenome. These changes are often responsible for variation in expression of the gene without any change in the underlying nucleotide sequence. The changes might also cause variation in chromatin structure resulting into the changes in function/activity of the genome. The epigenomic changes are dynamic with respect to the endogenous and/or environmental stimuli which affect phenotypic plasticity of the organism. Both, the epigenetic changes and variation in gene expression might return to the pre-stress state soon after withdrawal of the stress. However, a part of the epigenetic changes may be retained which is reported to play role in acclimatization, adaptation as well as in the evolutionary processes. Understanding epigenome-engineering for improved stress tolerance in plants has become essential for better utilization of the genetic factors. This review delineates the importance of epigenomics towards possible improvement of plant’s responses to environmental stresses for climate resilient agriculture.

This review deals with the adaptive mechanisms that plants can implement to cope with the challenge of salt stress. Plants tolerant to NaCl implement a series of adaptations to acclimate to salinity, including morphological, physiological and biochemical changes. These changes include increases in the root/canopy ratio and in the chlorophyll content in addition to changes in the leaf anatomy that ultimately lead to preventing leaf ion toxicity, thus maintaining the water status in order to limit water loss and protect the photosynthesis process. Furthermore, we deal with the effect of salt stress on photosynthesis and chlorophyll fluorescence and some of the mechanisms thought to protect the photosynthetic machinery, including the xanthophyll cycle, photorespiration pathway and water-water cycle. Finally, we also provide an updated discussion on salt-induced oxidative stress at the subcellular level and its effect on the antioxidant machinery in both salt-tolerant and salt-sensitive plants. The aim is to extend our understanding of how salinity may affect the physiological characteristics of plants.

Smart farm is a technology that greatly helps improve the productivity and quality of crops and is being actively introduced into indoor environments such as green houses. However, it has not yet been distributed to field-grown crops. The main reason is that, unlike indoor environments, it is very difficult to collect sensor data for monitoring the growth environment of crops in open fields where weather conditions change significantly and power supply is difficult. Additionally, because various sensors are used, the data formats of the devices are different, making it difficult to process. This paper presents a field crop growth environment monitoring and big data analysis system. The proposed system first solves power supply and data communication problems using solar power generation and LPWA technology. Additionally, based on the oneM2M architecture, data from various sensors is transmitted to the server using standardized technology. The transmitted data is stored and managed on the server as big data, and can be used to predict the production and quality of field-grown crops and take appropriate measures. The proposed system is expected to create an environment optimized for the growth of field crops and help prevent and manage diseases.

Abiotic stress is a significant factor restricting the normal growth and development of plants. Under abiotic stress, plants maintain their life and continuous growth by reconfiguring transcriptional regulation and metabolic networks. In recent years, with the development of sequencing technology and mass spectrometry technology, transcriptomics and metabolomics have emerged as new disciplines following genomics and proteomics, which are conducive to identifying metabolites and regulatory genes in plants under abiotic stress. In this review, we mainly analyzes the technical characteristics, advantages, and disadvantages of transcriptomics and metabolomics, focusing on reviewing the research progress in the field of plant responses to abiotic stress (temperature stress, salt stress, water stress, and heavy metal stress) using transcriptomics and metabolomics both domestically and internationally in recent years. It also provides a prospective view on current issues, which helps accelerate the understanding of the mechanisms of plant responses to abiotic stress and provides new ideas for breeding stress-resistant varieties in the future.

Plants are subjected to abiotic stresses throughout their developmental period. Abiotic stresses include drought, salt, heat, cold, heavy metals, nutritional element and oxidative stresses. Improving plant response to various environmental stresses is critical for plant survival and perpetuation. The WRKY transcription factors have special structure (WRKY structural domains), which enable WRKY transcription factors to have different transcriptional regulatory functions. The WRKY transcription factors can not only regulate abiotic stresses response and plant growth and development by regulating phytohormone signalling pathways, but also promote or suppress the expression of downstream genes by binding to the W-box [TGACCA/TGACCT] in the promoters of their target genes. In addition, WRKY transcription factors not only interact with other families of transcription factors to regulate plant defence responses in abiotic stresses, but also self-regulate by recognizing and binding to W-boxes in their own target genes to regulate their defence responses to abiotic stresses. However, in recent years, research reviews on the regulatory roles of WRKY transcription factors in higher plants are scarce and shallow. In this review, we focus on the structure and classification of WRKY transcription factors, as well as the identification of their downstream target genes and molecular mechanisms involved in the response to abiotic stresses, which can improve the tolerance ability of plants in abiotic stress and we also look forward to their future research directions, with a view to providing theoretical support for the genetic improvement of crop abiotic stresses tolerance.

The structural, elastic, and electronic properties of orthorhombic Cd2SiO4 and Hg2GeO4 were examined under varying pressure conditions using first-principles calculations based on densi-ty-functional theory employing the projector augmented wave method. The obtained cell pa-rameters at 0 GPa were found to align well with existing experimental data. We delved into the pressure-dependence of normalized lattice parameters and elastic constants. In Cd2SiO4, all lat-tice constants decreased as pressure increased, whereas in Hg2GeO4, parameters a and b de-creased while parameter c increased under pressure. Employing the Hill average method, we calculated the elastic moduli and Poisson’s ratio up to 10 GPa, noting an increase with pressure. Evaluation of ductility/brittleness under pressure indicated both compounds remained ductile throughout. We also estimated elastic anisotropy and Debye temperature under varying pres-sures. Cd2SiO4 and Hg2GeO4 were identified as indirect band gap insulators, with estimated band gaps of 3.34 eV and 2.09 eV, respectively. Interestingly, Cd2SiO4 exhibited a significant increase in band gap with increasing pressure, whereas the band gap of Hg2GeO4 decreased under pres-sure, revealing distinct structural and electronic responses despite their similar structures.

Understanding the impact of drought stress on Arabica coffee physiology and metabolism is essential in the pursuit of developing drought-resistant varieties. In this study, we explored the physiological and metabolite changes in coffee genotypes exhibiting varying degrees of tolerance to drought—namely, the relatively tolerant Ca74110 and Ca74112, and the sensitive Ca754 and CaJ-19—under well-watered conditions and during terminal drought stress periods over two-time intervals (0 and 60 days following the onset of stress). The Metabolites profiling conducted uncovered significant associations between growth and the physiological characteristics of coffee genotypes with distinct drought tolerance behaviors. Initially, no marked differences were observed among genotypes or treatments. However, at the 60-day post-drought onset, notable increases in shoot growth, biomass, CO2 assimilation, pigments, and various physiological parameters were evident, particularly in the relatively tolerant genotypes. Metabolite profiling revealed elevations in glucose, maltose, amino acids, organic acids, and decreases in other metabolites, more pronounced in drought-tolerant genotypes. These alterations were more pronounced in the drought-tolerant genotypes, indicating a correlation with enhanced compatible solutes and energy-associated metabolites crucial for drought tolerance mechanisms. This research introduces GC-MS based metabolome profiling to Ethiopian coffee, shedding light on the intricate responses to drought stress and paving the way for the potential development of drought-resistant coffee seedlings in intensified agro-ecological zones.

This study compared cortical responses to speech in preschoolers with typical language development (TLD) and Developmental Language Disorder (DLD), and in adults. We investigated whether top-down language effects modulate speech perception in an adult-like manner. We compared cortical mismatch responses (MMR) during passive perception of speech differing in linguistic complexity in three groups of participants: preschoolers with TLD (n=11), preschoolers with DLD (n=16) and adults (n=20). We also measured children’s phonological skills and investigated if they are associated with the cortical responses. MMR results indicated top-down language effects in adults, with enhanced cortical discrimination of lexical stimuli but not of non-words. In preschoolers, the TLD and DLD groups did not differ on the MMR measures and no top-down effects were detected. Moreover, we found no association between MMRs and phonological awareness skills, even though the DLD group’s phonological skills were significantly lower. Our findings suggest that top-down language modulations on speech discrimination may not be present during early childhood, and that children with DLD may not exhibit cortical speech perception deficits. The lack of association between phonological and MMR measures indicates that further research is needed to understand the link between language skills and cortical activity in preschoolers.

Coastal ecosystems provide a wide range of goods and services for the lives of human beings and aquatic species. Nevertheless, climate-induced extreme events cause unprecedented impacts on these areas, instigating a reduction of aquatic goods and services, destruction of infrastructure, and loss of human lives. Hence, this review investigated the impacts of climate-induced coastal hazards and adaptation responses. A systematic review method was used to address the objectives of this literature review. The main data sources were Research Gate, Google Scholar, Scopus, Web of Science, and PubMed databases. A total of 40 research articles (2012-2023) were selected using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2020) methodology. The findings of this review revealed that Bangladesh was the leading country based on the number of studies published on the impacts of climate-induced coastal hazards and coastal adaptations (20%), followed by the USA, which accounts for about 15%. Sea-level rise, coastal flooding, and climate change and variability were the most studied climate-induced coastal hazards, each accounting for 55%, 52.5% and 52.5% respectively. Coastal hazards have had significant impacts on the fishery, water, coastal ecosystems and biodiversity, agriculture, tourism, and infrastructure sectors. Besides, they caused migration and death of humans and animals. About 35% of the articles explored the assessment of vulnerability to climate-induced hazards. Moreover, 32.5% of the articles investigated anticipated climate-induced hazards. Hard, soft, ecosystem-based, and hybrid adaptation measures were used to adapt to the impacts of diverse climate-induced coastal hazards. In conclusion, developing countries are more vulnerable to the adverse impacts of climate-induced coastal hazards than developed countries. The coastal area’s vulnerability to climate change risks will continue unless all stakeholders act proactively. Thus, it is suggested that the adaptation policies of vulnerable coastal areas should give due attention to nature-based solutions to reduce the adverse impacts of coastal hazards sustainably.

Experimental systems to simulate future elevated CO2 conditions in the field often have large, rapid fluctuations in CO2. To examine possible impacts of such fluctuations on photosynthesis, intact leaves of field grown plants of five species were exposed to two-minute cycles of CO2 between 400 and 800 mol mol-1 lasting a total of 10 minutes, with photosynthesis, stomatal conductance and PSII fluorescence measured at the end of each half-cycle, and also 10 minutes after the end of the cycling. Prior to the cyclic CO2 treatments, steady-state responses of leaf gas exchange and fluorescence to CO2 were determined. In four of the five species, in which stomatal conductance decreased with increasing CO2, the cyclic CO2 treatments reduced stomatal conductance. In those species, both photosynthesis and the photochemical efficiency of PSII were reduced at limiting internal CO2 levels, but not at saturating CO2. In the fifth species, there was no change in stomatal conductance with CO2, and no change in either photosynthesis or PSII efficiency at any CO2 level with CO2 cycling. It is concluded that in many, but not all, species fluctuations in CO2 may reduce photosynthesis at low CO2 partly by decreasing the photochemical efficiency of photosystem II, as well as by decreasing stomatal conductance.

Music and language are hypothesized to share neural resources, particularly at the level of syntax processing. Recent reports suggest that attention modulates this sharing of neural resources, but the time-course of the effects of attention, and the degree to which attention operates similarly on music and language, are yet unclear. In this EEG study we manipulate the syntactic structure of simultaneously presented musical chord progressions and garden-path sentences in a modified rapid serial visual presentation paradigm, while varying top-down attentional demands to the two modalities. The Early Right Anterior Negativity (ERAN) was observed in response to both attended and unattended musical syntax violations. In contrast, an N400 was only observed in response to attended linguistic syntax violations, and a P3 only in response to attended musical syntax violations. Results show that top-down allocation of attention indeed affects the processing of syntax in both music and language, with different neural resources acting upon the two modalities particularly at later stages of cognitive processing. However, the processing of musical syntax at an earlier stage of the perceptual-cognitive pathway, as indexed by the ERAN, is partially automatic, and is strongly indicative of separate neural resources for music and language.

Subsoil tillage loosens compacted soil for better plant growth, but promotes water loss, which is a concern in areas commonly irrigated. Therefore, our objective was to determine the physiological responses of high yield spring corn (Zea mays L.) to Subsoil tillage depth when grown in the western plain irrigation area of Inner Mongolia that leads to the best water use efficiency. The experiment during 2014 and 2015 used Zhengdan958 and Xianyu335 with three differing subsoil tillage depths (30, 40, or 50 cm) as trial factor and shallow rotary as a control. Subsoil tillage increased shoot dry matter accumulation, leading to a greater shoot/root ratio. Subsoil tillage helped retain greater leaf area index in each growth stage, increase the leaf area duration, net assimilation rate, and relative growth rate, with greater effects as tillage was deeper, effectively delaying the aging of the blade. Grain yields were increased by 0.7%–8.9% on average in subsoil tillage treatments compared to conventional soil treatment shallow rotary, Water use efficiency were increased by 1.93%–18.49% on average in subsoil tillage treatment compared to shallow rotary, resulting in net income increases by 2.24% to 6.97% compared to shallow rotary. Among the three different subsoil tillage depth treatment, the grain yield, water use efficiency, and net income is the best under the treatment of subsoil tillage depth of 50 cm.