Background: Present experiment was aimed to know the influence of weather on the incidence of thrips, a major sucking pest and potential vector of GBNV in blackgram. Methods: The incidence of thrips complex for consecutive three seasons (spring 2019-20, autumn 2020-21, spring 2020-21) have been recorded from 7 DAS, till to crop maturity and correlated with weather parameters. Result: The thrips population was observed in the field approximately after 14 DAS. Overall view of thrips incidence in blackgram was more during autumn 2020-2021 (17.35 mean no of thrips per plant) compared to spring 2019-2020 (10.6) and 2020-2021 (10.10). Thrips population has showed a highly significant positive correlation with maximum temperature (0.74), minimum temperature (0.75), as well as with mean temperature (0.819) during rabi 2019. During spring 2020-21 only maximum temperature has shown significant positive correlation, but minimum and mean temperatures have shown positive correlation without any significance. Whereas during autumn 2020-21 temperature has shown positive correlation without any significance. Across the three seasons relative humidity has shown insignificant negative correlation.

Background: Soybean is considered one of the most important economic crops; however, its productivity is influenced by genetic variability among cultivars and their response to phosphorus fertilization levels. The use of nano-phosphorus fertilizer contributes to enhancing growth efficiency and yield, which necessitates genetic evaluation of soybean cultivars under such fertilization conditions. Methods: A field experiment was conducted in northern Kirkuk during the summer season of 2024 to estimate genetic parameters and analyze genetic relationships among six soybean cultivars (Iman, Taqa-2, Taqa-3, Lee-74, Shaima, Senaia-2) under six levels of nano-phosphorus foliar fertilizer (0, 1000, 2000, 3000, 4000 and 5000 ppm). The experiment was laid out in a randomized complete block design (RCBD) with a split-plot arrangement and three replications. Sowing was carried out on May 20, 2024. Result: The data showed high estimates of genetic variance (σ2G), environmental variances (σ2E) and phenotypic variances (σ2P), while broad-sense heritabilities reached a high of 91.65%. There were significant positive genetic correlations between seed yield and number of pods per plant (0.731**), number of seeds per pod (0.819**) and 1000 seed weight (0.956**). The variances and coefficients of variation for total seed yield per plant were 41073.86, 3740.47, 44814.33 and 8.70% and 8.33%, respectively. GGE Biplot analysis revealed that the genotype Lee-74 was the most stable and superior line for seed yield per plant. The results from hierarchical cluster analysis revealed that the pair of Iman and Shaima was the closest in genetic relationship (248.27) and the most distant between Taqa-2 and Lee-74 (68233.67).

Ca-B interactions in crop plants are essential in crop productivity, quality and stress-tolerance in a variety of agro-climatic conditions. This review discusses the complex processes behind Ca-B nutrition in plants, both at the molecular interaction level and in the field. Calcium ionically bridges with the pectin compounds at the cellular level and boron forms borate crosslinking with rhamnogalacturonan II (RG-II). The resulting B-RG-II complex that involves two molecules of boric acid and two Ca2+ ions is important to retain the cell wall integrity. The effect of these nutrients during the plant development is synergistic and when there is deficiency of boron, it leads to increased cytosolic Ca2+ and also calcium-regulated gene expression. Physicochemical properties of soil play a great role in Ca-B dynamics. Boron adsorption on clay minerals is enhanced as pH rises reaching a peak of about pH 9.0 in alkaline environment. The arable land of the world is estimated at around 50% of the global land, with 50% of this area being acid in nature making the availability of the two nutrients to be limited and thus requires strategic interventions. Optimised Ca-B nutrition leads to significant increases in yield of major crops. This can only be achieved through combined methods of soil testing, precise fertilisation and environmental concerns to facilitate good management. Nutrient management strategies are being transformed with the new technologies such as genomics, metabolomics, precision agriculture, mycorrhizal associations and machine learning algorithms. New areas of research should be directed towards new decision support systems, molecular level interventions, sustainable boron recovery of waste streams and mycorrhizal-mediated nutrient interactions.

Background: This study investigates the impact of climate change on rice productivity in Jharkhand, India, with a focus on temperature fluctuations and rainfall patterns. It highlights the risks associated with maximum temperatures during critical growth stages for rice, while minimum temperatures can benefit growth. The study also underscores the challenges posed by water scarcity, as agriculture in Jharkhand heavily relies on rainfed systems. Methods: The current study employs secondary district-level data collected from different sources and applies the System GMM approach for empirical estimation. Result: The findings indicate that both temperature and rainfall have a significant influence on rice yields. The results suggest that policymakers should account for district-level heterogeneity when designing climate adaptation strategies. Enhancing irrigation coverage and efficiency, as well as converting fallow land into arable land, are identified as key measures to mitigate climate-related risks and improve farm income.

Background: Intersectoral synergies between technology, environment and farming are vital for sustainable agricultural development. This requires innovative solutions to overcome low productivity and environmental stress; digital technologies offer potential to transform smallholder agricultural systems. Methods: This study evaluates the sustainability impacts of digital engagement (DE) in Sub-Saharan African agriculture through a systems-based assessment framework. Using Partial Least Squares-Structural Equation Modeling (PLS-SEM) on World Bank datasets (2000-2023), this research quantifies DE’s effects on agricultural productivity while accounting for critical moderators: environmental stress, feasibility assessment (FA), technical skills (TS) and livestock farming (LF). Result: Results reveal significant positive interactions, with coefficients of 1.690 for natural environment (NE), 2.387 for FA, 3.901 for TS and 77.202 for LF, demonstrating the moderating role of environmental performance between DE and agricultural productivity. The findings contribute to impact evaluation methodologies by demonstrating how PLS-SEM can assess complex technology-environment interactions, while providing actionable criteria for appraising digital agriculture projects in resource-constrained settings. However, challenges such as inadequate infrastructure and limited farmer technical skills must be addressed. By bridging digital innovation with environmental stewardship, this research offers actionable insights for policymakers to advance sustainable agricultural practices in resource-constrained settings.

The plants viruses have been examined to study the economic losses associated with agricultural crops and the viruses that represent a focus of attention of this study, in particular the Tomato Yellow leaf curl virus (TYLCV) and its impact on tomato productivity in Iraq. A study highlights the destroy produced by this virus, which can reach up to 100% in severe cases. This review aims to provide a comprehensive overview of the economic impact of TYLCV on tomato productivity in Iraq and to discuss integrated management strategies. It addresses the significant yield losses, which can be up to 100% in severe cases. In addition, it examines the effect of the virus on the chemical composition of fruit and reduces both nutritional value and marketing. The study emphasizes that controlling plant viruses requires integrated strategies, including development of resistant cultivars, the use of chemical, biological and agronomic control measures within an integrated management framework has been stressed as the best way to control plant viruses. It also underscores the need for enhanced scientific research and for improving farmers’ awareness. Additionally, it explores the effects of plant viruses on the chemical composition of associated plants, such as some mineral elements and plant hormones and how the plant responses resulting from the interaction of the host plant and the virus can lead to the decay of crop quality. Virus management strategies, including resistant cultivars, agricultural control methods such as the use of biological control methods and nanotechnology, in some limited cases, chemical pesticides used in a responsible manner, are discussed. Overall, this review highlights the urgent need for robust, integrated management strategies to mitigate the devastating effects of TYLCV and enhance the sustainability of tomato production in Iraq.

Background: Coconut (Cocos nucifera L.) and peanut (Arachis hypogaea L.) are widely cultivated in tropical and subtropical regions. Intercropping peanuts in young coconut gardens can enhance soil fertility through biological nitrogen fixation while supporting local food production. This study evaluated the optimal intercropping density of VD 01-1 peanut in Dua Dua coconut gardens (an aromatic variety) during the establishment phase in Phu Quoc, An Giang Province, Vietnam. Methods: A field experiment was conducted in Phu Quoc, An Giang Province (10o14'40.7"N; 104o01'22.4"E) from 2024 to 2025 to compare three intercropping densities (15, 20, 25 peanut rows) with a non-intercropped control. The study assessed VD 01-1 peanut growth, yield and pod quality, as well as changes in soil properties and nutrient availability. Result: VD 01-1 peanut grew well under Phu Quoc conditions. Intercropping 20 rows in Dua Dua gardens resulted in higher yield and better pod quality than 15- or 25-row treatments, without affecting coconut growth. This density also enhanced soil fertility and nitrogen-fixing microbial activity, with the most favorable soil and microbial conditions observed at 20 rows. Nutrient availability supported coconut growth, with highest nitrogen and phosphorus at 20 rows and potassium at 25 rows. Overall, intercropping 20 rows (covering 60% of the intercroppable area) is optimal, improving productivity, soil health and economic returns while maintaining coconut development.

Aquaponics represents a revolutionary approach to sustainable agriculture, combining aquaculture and hydroponics in an integrated system that maximizes resource efficiency while minimizing environmental impact. This comprehensive review examines the development and implementation of cost-effective automated aquaponics systems utilizing Arduino-based technologies for enhanced legume cultivation and sprout production. The integration of Internet of Things (IoT) sensors, automated control systems and energy-efficient technologies has transformed traditional aquaponics into smart farming solutions capable of optimizing nutrient delivery, water quality management and environmental conditions. Recent advances in microcontroller technologies, particularly Arduino and ESP32 platforms, have enabled the development of affordable monitoring and control systems that can maintain optimal growing conditions while reducing operational costs. This review synthesizes current research on automated aquaponics systems, focusing on their application in legume and sprout production, technological infrastructure requirements, energy harvesting solutions and the nutritional benefits of sprouted legumes. The analysis reveals significant potential for Arduino-based systems to enhance productivity, improve resource utilization and contribute to sustainable food production systems. Key challenges identified include system scalability, energy management and the need for standardized protocols for different crop types. Future research directions emphasize the development of AI-driven control systems, renewable energy integration and optimization of nutrient cycling for specific legume varieties.

Background: Climate change is predicted to aggravate abiotic stresses such as salinity, drought and temperature, harshly affecting crop plants, especially rice plants and reducing their productivity. Soil quality is affected by stress conditions, which makes it a big challenge to secure food resources in rice-growing regions. Abiotic stress-tolerant rice is necessary to grow in extreme environmental conditions for food safety. Methods: The present investigation was carried out by randomly selecting ten local rice varieties and screening them naturally for salt and drought tolerance. In this study, the salinity-sensitive rice variety (IR64) was taken as a control. We analysed biochemical parameters such as H2O2, chlorophyll, proline content, relative water content (RWC), lipid peroxidation (MDA) content, CAT (catalase), GPX (guaiacol peroxidase), GR (glutathione reductase), leaf disc assay, electrolytic leakage and hormone assay. The photosynthetic parameters were also determined to identify the salinity and drought-tolerant rice lines. Result: Our results showed that stress-tolerant rice varieties, such as T2 (Jagannath) and T5 (Swarnamayee), T3 (Parijata) and T9 (Prativa) have higher chlorophyll, endogenous ion and soluble sugar contents than other varieties. The present study can help to develop stress-tolerant rice plants worldwide and increase food availability in salinity and drought environments.

Background: This study assesses post-eruption soil health on Mount Kelud to support the development of superior commodities such as pineapple. Utilising a modified Cornell Soil Health Assessment (SHA) method, the analysis integrates physical, chemical and biological soil properties. This parameter combination of land characteristics includes slope and NDVI (Normalized Difference Vegetation Index). Methods: A physiographic survey and land unit classification based on land use and criticality levels were employed. Statistical analyses (normality tests, ANOVA and correlation) were performed using RStudio, while spatial analyses used overlay and interpolation methods in ArcGIS. Result: SHA post-eruption has criteria healthy (63.30%) and moderately healthy (36.70% ) and KBA has the highest. Key parameters significantly influencing SHA included porosity (0.77), sand composition (-0.70), BD (-0,49), permeability (-0.44), pH (r=0.36), earthworm population (0.73), organic matter (0.37), slope (-0.62) and NDVI (0.56). Integrating soil and land indicators into spatially distributed SHA mapping offers a strategic approach to land management and supports the targeted cultivation of pineapple as a leading post-eruption crop.