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The slowing of agricultural productivity growth globally over the past two decades has brought a new urgency to detect its drivers and potential solutions. We show that air pollution, particularly surface ozone (O3), is strongly associated with declining agricultural total factor productivity (TFP) in China. We employ machine learning algorithms to generate estimates of high-resolution surface O3 concentrations from 2002 to 2019. Results indicate that Chinas O3 pollution has intensified over this 18-year period. We coupled these O3 estimates with a statistical model to show that rising O3 pollution during nonwinter seasons has reduced agricultural TFP by 18% over the 2002-2015 period. Agricultural TFP is projected to increase by 60% if surface O3 concentrations were reduced to meet the WHO air quality standards. This productivity gain has the potential to counter expected productivity losses from 2°C warming.

Digital ability can increase job-searching efficiency of labour. However, the impact of digital ability on employment adequacy in rural households in China has not received sufficient attention. Using survey data from 1,953 rural households in China, this study analyzes labour participation and working time as indicators of employment adequacy. Item response theory was used to construct digital ability indicators, while conditional mixed process, IV-Probit, and IV-Tobit models were used for empirical estimation. After controlling for endogeneity, the results show that: 1) digital ability has a positive impact on labour participation rate and total working time; 2) digital ability has a positive effect on non-agricultural participation and working time, but negative effect on agricultural participation and production time; 3) the promotion effect of digital ability on working time is more obvious in households with high dependency ratio and low income; 4) both overtime work and underemployment co-exist among rural households. These results provide evidence that digital ability promotes employment adequacy and off-farm transfer of rural labour. Policymakers should consider improving the digital ability of rural households, especially those with high dependency burdens and low incomes. An in-depth discussion of digital ability should be undertaken in further research. [ABSTRACT FROM AUTHOR]

What types of agricultural enterprises should be supported by finance to improve the economic effect? The paper applies the panel data from Chinese agricultural enterprises from 2014 to 2019, and uses the Heckman two-stage method and fixed effects model to test the relationship between financial support and the economic effects of agricultural enterprises (AEs) from the perspectives of 'who was supported' and 'who benefited'. The results showed that finance tended to support agricultural enterprises with large scale and low productivity; agricultural enterprises with specialized R&D institutions, state-owned and export enterprises are easier to receive financial support and the larger scale of financial support. Financial support improved the economic effect of agricultural enterprises. Heterogeneity analysis showed that financial support has a significant positive impact on agricultural enterprises sales revenue and total factor productivity in western, grain and private enterprises. [ABSTRACT FROM AUTHOR]

The article is devoted to the study of legislation in the sphere of adaptation of agricultural production to climate change. It is noted that the implementation of this type of activity is not only related to environmental pollution, but also directly depends on favorable climatic conditions. It is stated that the norms that regulate relations in the sphere of adaptation of agricultural production to climate change in Ukraine are contained in various legal acts, mostly of a strategic or conceptual in nature. Sometimes their norms are inconsistent and contradictory. There is no mechanism for the implementation of the measures established in these documents. So, their implementation becomes optional. In particular, the Recommendations on the adaptation of agriculture to climate change for the period up to 2030, which are provided by the Action Plan for the Implementation of the Realization Concept of State Policy in the Sphere of Climate Change for the Period up to 2030, approved by the Decree of the CMU of December 6, 2017 № 878-p, are unadopted. It is claimed that for solving the problem of adaptation of agriculture to climate change, it is especially important to increase the role of organic production as an activity that contributes to sustainable development of rural areas and solving a number of social problems. Because organic production is one of the most common direction of climate smart agriculture, it is proposed to put Consept of this one on basis of the legislation about adaptation of Ukrainian agricult ure to climate change. Taking into account the significant negative impact of agricultural production to the environment, we propouse to provide agriculture among the main sources of greenhouse gas emissions (industry, energy and transport) into the Ukrainian Law of February 28, 2019 «About the Basic Principles (Strategy) of the Ukrainian State Environmental Policy for the Period up to 2 030» (part I) [ABSTRACT FROM AUTHOR]

Drawing on data from the 2015 China Household Finance Survey, this paper assess the links between rural-urban migration and the marketization of land rentals. The estimated results indicate that farm households with more migrant labour are less likely to participate in land rentals, and lessees with more agricultural labour tend to use the rented land for non-grain production. Meanwhile, lessees with less migrated labour are more likely to rent land for profit and pay high land rent, even when land rentals are conducted between acquaintances. Further evidence shows that lessors with more migrated labour have a higher probability of leasing farmland for for-profit purposes and obtain high land rent. Our analysis reveals that with rural-urban migration, the marketization of land rentals between acquaintances in rural China increases if there emerge large numbers of lessees who are specialized in agricultural production. [ABSTRACT FROM AUTHOR]

Weather and climate uncertainties significantly impact crop and food production, particularly in the Bihar region of India. Crop cultivation in this region faces significant risks due to several climatic challenges: rising minimum temperatures in the winter (rabi), extreme temperatures in the spring, intense rainfall, and extended dry spells during the kharif ;(monsoon) season. The growth and development of the plants majorly depend on the climatic and nutrient factors. The plant uptake and utilization of nutrients are surprisingly reliant on the weather conditions. Therefore, understanding the interaction of climatic factors and nutrient application methods is crucial for achieving higher growth and yield stewardship. A two-year field experiment was conducted from 2019 to 2021 in the riverine area (Diara) of Bihar, India, to evaluate the relationship between weather parameters and application methods of Molybdenum and Boron on the dry matter production (DMP) and grain yield of chickpea. Six different application methods of Boron and Molybdenum were tested. The study aimed to identify the ideal micronutrient application methods for chickpea production in the rabi season under the Diara ;(riverine) area. Results indicated that the combination of boron basal + molybdenum seed treatment produced the highest grain yield (1740 kg ha−1) and dry matter production (5.81 g plant−1) at all phenological phases, performing on par with boron basal + molybdenum foliar application for both years. Concerning the weather parameters, the correlation studies showed that all the direct weather parameters and agrometeorological indices showed positive and negative effects (p =.05) on DMP and grain yield of chickpea during both years. This study contributes to the development of site-specific application methods for molybdenum and boron, identifies optimal sowing times, minimizes the negative impacts of climate change, and maximizes chickpea production in the riverine (Diara) area of Bihar. [ABSTRACT FROM AUTHOR]

Current agricultural production systems face challenges of poor economic returns, soil fatigue and negative environmental outcomes from excess use of nitrogenous fertilizers, especially in wheat production under middle gangetic plains. To overcome these challenges, the current study was conducted to optimize nitrogen management in different wheat genotypes with precision nitrogen management tools and approaches. The field experiment was laid out in split-plot design, with three genotypes assigned to the main plot and six nitrogen management practices to the sub-plot. The soil of the experimental field was sandy loam in texture, with low levels of organic carbon and available nitrogen, and medium levels of available phosphorus and potassium. Results revealed that the HD-2967 genotype outperformed others in terms of growth, grain yield (4.7 and 4.81 t ha−1), gross return (1417.41 and 1505.48 US$ ha−1), net return (953.43 and 1019.76 US$ ha−1), and B-C ratio (2.04 and 2.08) in 2015-16 and 2016-17, respectively. Among the nitrogen management practices, application of 150 kg N ha−1 in three equal splits demonstrated improved crop growth, grain yield (4.7 and 4.81 t ha−1), and economic returns (gross return, 1500.40 and 1607.65 US$ ha−1, net return, 1025.40 and 1110.38 US$ ha−1 and B: C ratio, 2.17 and 2.23) in 2015-16 and 2016-17, respectively. However, it resulted in higher nitrogen losses. Green seeker guided N application significantly reduced apparent nitrogen losses compared to all other nitrogen applied treatments. These findings provide valuable insights for optimizing wheat production by selecting appropriate genotypes and implementing precision nitrogen management techniques to enhance yield, profitability, and environmental sustainability. [ABSTRACT FROM AUTHOR]

Low soil phosphorus (P) availability is a limiting factor for crop production. Application of livestock manure as organic fertilizer can increase soil P availability, but may cause soil contamination with antibiotics such as sulfadiazine (SD), thus adversely affecting plant growth and nutrient uptake. The effects of P (0 and 50 mg kg−1) and SD (0, 1, 10, and 100 mg kg−1) levels on plant growth, root development, and nitrogen (N) and P uptake of maize and soybean were examined in a pot experiment using a loess soil as the test soil. High levels of SD considerably inhibited plant growth of both crops. Both P fertilization and SD negatively affected root development of both crops, especially at higher SD levels. For both crops, the average root diameter and the proportion of thick roots increased with increasing soil SD level. When soil SD level was ≤10 mg kg−1, the effects of P fertilization and SD on plant N and P concentrations, and N:P, N- and P-utilization efficiency were not significant in most cases. The effects of SD on plant N and P nutrition could not be of a great concern when soil SD level was ≤10 mg kg−1. Overall, soil SD pollution could reduce plant biomass and inhibit root development of soybean and maize, with a stronger effect on root development than on plant biomass at a high soil SD level (≥10 mg kg−1). In agricultural production, attention should be paid to soil SD pollution via manure application. [ABSTRACT FROM AUTHOR]

The significance of zinc and iron in crop production, particularly in rice-wheat cropping systems, has been increasingly recognized. The present study aimed to determine the effect of different soil samples collected from the rice-wheat cropping system of Haryana with different soil texture on rice grain yield and micronutrient content using a greenhouse trial with four levels of Fe (0, 25, 50 mg kg−1 as soil and 0.5% foliar spray of FeSO4 at 45 DAS) and four levels of Zn (0, 5, 10 mg kg−1 as soil and 0.5% foliar spray of ZnSO4 at 35 DAS). This study discovered that rice grain yield showed a positive correlation with soil Zn and Fe concentrations in soil before sowing and a negative correlation with soil Fe and Zn concentrations in soil after crop harvesting. In most of the soils studied, foliar spray alone Fe @ 0.5% foliar (45 DAS) and Zn @ 0.5% foliar (35 DAS) improved Fe and Zn concentrations in rice significantly more than soil application of 25 mg Fe kg−1 and 5 mg Zn kg−1, respectively. The rice grain yield in clay soil was 14-42% higher than in sandy soil with different doses of Zn and Fe application. The order of preponderance of different Fe and Zn fractions were CA-Fe < OM-Fe < EX-Fe < FeMnOX-Fe < Res-Fe and Res-Zn > FeMnOX-Zn > OM-Zn > CA-Zn > Ex-Zn in the soils, respectively. Conclusively, concomitant consideration of grain yield and grain Zn and Fe concentrations of rice are the sustainable approach toward food targets achievement. [ABSTRACT FROM AUTHOR]

Precision nutrient management is a modern approach for optimizing nutrient supply in fruit crops, ensuring that plants receive the actual amount of essential elements at the right time and place. Traditional nutrient management methods often undergo deficiencies, leading to over-fertilization, uneven distribution of nutrients, environmental pollution, and economic inefficiency. These review paper challenges can be addressed by providing real-time data of soil conditions, plant health and nutrient levels. This strategy depends on advanced technologies such as remote sensing, variable rate technology, fertigation, slow/control release fertilizer, and organic amendments to weave nutrient application to the specific needs of each crop and individual plant within a field. It is emphasized by its potential for plant growth and development, increased crop yield, optimized resource utilization and mitigated environmental concerns. By fine-tuning nutrient application, farmers can achieve better economic returns while promoting sustainable agriculture. Precision nutrient management for fruit crops is characterized by a scarcity of studies exploring the application of advanced technologies and data-driven approaches. There is a need for more in-depth investigation to develop and validate precision nutrient management strategies tailored to the unique requirements of different crops. Closing this research gap will contribute to sustainable and optimized fruit crop production. In conclusion, precision nutrient management represents a paradigm shift in agricultural practices, offering a more sustainable and efficient approach to nutrient application in fruit crops. By untried advanced technologies and data-driven insights, farmers can optimize their resource use, enhance crop performance, and contribute to the long-term sustainability of agriculture. [ABSTRACT FROM AUTHOR]

Grape is a staple crop in many parts of Iran which has shown moderate sensitivity to salinity stress. Water and soil salinity is one of the major environmental stresses that strongly affect the production of agricultural products, including grapes. To overcome the harmful effects of salinity, different methods and materials are used, one of which is the use of nitric oxide. In order to explore the impact of nitric oxide on the mitigation of the negative effects of salinity stress on four grape cultivars and rootstocks ('Bidaneh Sefid' (Sultana) and 'Yaghouti' cultivars, and 140Ru and 1103 P rootstocks), a pot experiment was performed in a factorial based on a randomized complete block design with three replications. Plants were subjected to three sodium chloride (NaCl) levels of 0 (control), 25, and 50 mM and three levels of sodium nitroprusside (SNP) of 0 (control), 0.5, and 1 mM. Results indicated that increasing SNP concentration caused an increase in growth indices such as leaf area, shoot and root length, fresh and dry weights of leaves, shoots, and roots, and leaf relative water content (RWC). Furthermore, salinity decreased the concentrations of potassium (K+), calcium (Ca2+), magnesium (Mg2+), and iron (Fe2+) in leaves, while increased the amount of sodium (Na+) and chlorine (Clˉ) as well as the electrolyte leakage (EL). In addition, SNP at 0.5 and 1 mM could increase the growth efficiency and RWC as well as the elements such as K+ and Mg2+ while decreased the absorption of Na+ and Clˉ as well as the EL in plants under salinity. According to the obtained results, SNP at both concentrations (0.5 and 1 mM) had a pronounced effect on reducing the negative effect of salinity in the evaluated grape rootstocks and cultivars. In general, the positive effects of SNP on 'Yaghouti' and 'Bidaneh Sefid' cultivars were higher than those on 140Ru and 1103 P rootstocks. [ABSTRACT FROM AUTHOR]

Given the challenges posed by climate change and population growth, Iraq faces increasing demands for food production and water resources. To enhance agricultural productivity and optimize water management for crop efficiency, this study evaluated various wheat varieties, specifically Mawaddah, Bohuth 10, Aba99, and Babel113, under different irrigation level. These level were based on depletion levels of available water at 40%, 55%, and 70%. Key metrics measured included actual evapotranspiration, water use efficiency (WUE), grain yield, spike number, grains per spike, and the weight of 100 grains over the growing seasons of 2022–2023 and 2023–2024. The findings revealed that water consumption varied with depletion levels for all wheat varieties, amounting to 435.53, 397.13, and 365.13 mm season-1, and 465.7, 422.10, and 385.40 mm season-1 for the respective depletion levels of 40%, 55%, and 70%, across the two seasons. WUE ranged from 1.01 for Babel 113 at the 70% depletion level to 1.85 for Bohuth and Mawaddah at the 40% depletion level. Among the plant traits, Mawaddah had the best performance at the 40% depletion level, while Babel113 had the lowest performance at the 75% depletion level. The drought sensitivity index varied among the varieties due to their genetic differences. Our research supports the feasibility of utilizing water at depletion levels up to 75% when cultivating drought-tolerant wheat varieties in semi-arid and arid conditions. [ABSTRACT FROM AUTHOR]

Drought had affected the crops production in Morocco, during the last decade. Plants breeding is still a solution to increase crops tolerance for water scarcity. Using natural biofertilizer based on microorganisms still a good practice to enhance the resilience of agriculture to drought. The objective of this study is to investigate the effect of water shortage and use of a biofertilizer based on the strain of Pseudomonas putida on five genotypes of eggplants selected for drought tolerance under the semi-arid of the northeast of Morocco. Two irrigations regimes: 100% (amount of water irrigation made by growers) and 50% of this amount with and without the biofertilizer (1 × 108 UFC/g). The biofertilizer was applied three times during the plant growth stages. The experiment was conducted at commercial farm production and using a randomized complete block design. Plants were organized in blocks containing 3 plants for each genotype and repeated in 5 repetitions. Crops were planted on August 3rd, 2022, and experiments ended on January 2nd, 2023. The results showed different responses among the genotypes in terms of growth. The effect of Pseudomonas on plant height showed that there was a significant increase, at 100% irrigation for C14, B3, C8, B5 and C11 with 20%, 19%, 17%, 14.29% and 12,5%, respectively compared with the control. For C8 and B3, when subjected to 100% water with biofertilizer, there was an increase in the average number of fruits compared to 100% water without the biofertilizer. The highest yield was recorded with B5 under 100% irrigation + fertilizer (1.35 kg/plant). Water shortage impacted the productivity of all genotypes and the fruit number and yield increased with the use of the biofertilizer. Our study is still valuable under the conditions of this trial and more experiments will be needed at several seasons and at different growing conditions. [ABSTRACT FROM AUTHOR]

In tropical countries, especially Indonesia, even though there is a notable correlation between rainfall pattern and indices of global climate, limited proof exists regarding the impact on crop productivity. Global climate indices are one of the indicators to identify the occurrence of climate change, but there is little research on climate change in Indonesia. In this research, the relationships among indices of global climate are represented by the southern oscillation index (SOI) and the sea surface temperature (SST) such as Nino. West, the Indian Ocean Basin-Wide (IOBW), and Nino 3, then the pattern of rainfall distribution and crop productivity during 10 years from 2012 to 2022 in the southern part of Java. The southern part of Java which is represented by Gunung Kidul District is a rain-fed area, and its location is in hilly topography so rainfall will be an important factor in this area, not only for daily life but also for agricultural sector purposes. The purpose of the study was to discover the relationship between global climate indices, rainfall distribution pattern and crop productivity in the Southern Part of Java, Indonesia. Rainfall distribution pattern for 10 years was calculated and displayed with spatial method, then principal component analysis (PCA) was used to analyse SST, and correlation analyses were used, along with wet and dry seasons as well as crop productivity. The results showed that from 2012 to 2022, high rainfall and correlation with global climate indices occurred in the southern and western part of Gunung Kidul district, and correlation among rainfall patterns and crop productivity showed significant correlations in some sub-districts. This result also showed that the relationships among global climate indices and rainfall distribution pattern can be influenced the agricultural productivity in the rainfed areas. [ABSTRACT FROM AUTHOR]

ABSTRACT Prediction of seasonal onset is crucial to agriculture in southern and eastern Africa. Here, we applied two definitions of onset, namely meteorological and agricultural (crop‐germination), to evaluate CMIP6 models through the lens of rainfall onset over representative maize agricultural regions of South Africa, Tanzania, Malawi and Zambia. We use the ERA5 reanalysis as a proxy for observations, and robust regression to calculate a statistical comparison of the onset definitions for the period 1979–2021. Evaluation of ERA5 reanalysis shows similar magnitude and pattern as gauge based MSWEP. Our results show that, for meteorological onset, Johannesburg, with a subtropical highland climate, experienced earliest onset after 23 December; and an increasing trend (later onset) but not statistically significant (p = 0.2). Over Bethlehem, which has continental climate, the earliest onset date was after October 9 and an increasing interannual variability since 2000 is noted. The standard deviation of onset dates across the regions shows an East‐Central‐South gradient. We also found that the crop‐germination onset definition shows earlier onset of seasonal rains, it differs considerably across regions, and has higher interannual variability, in comparison with the meteorological definition. Over Lilongwe, Mbeya and Lusaka, late meteorological onset with a weak positive and insignificant trend is observed. The CMIP6 model's representation of onset trend differs from reanalysis data, with inter‐model differences. Late meteorological onset is underestimated by GFDL‐CM4 and MPI while INM5, MPI and NorESM overestimate the observed earliest onset. The largest bias is shown by INM and MPI which simulate earliest and latest onset as 190 (07 January) and 206 (23 January) respectively. In addition, models often fail to simulate sufficient precipitation to produce onset for seed germination and crop development. The ACCESS model showed an insignificant trend (p value = 2) and later onset over Lilongwe, an insignificant trend (p value = 0.9) over Lusaka, and an earlier onset over Mbeya. Using the agricultural onset definition, over Bethlehem, all the models and the ERA5 reanalysis did not produce enough precipitation to meet onset conditions. We suggest that rainfall onset studies use several definitions or metrics of onset and that the choice of metric be informed by the research question. Using such an ensemble of onset metrics contributes to a better understanding of variability and uncertainties in agricultural productivity. [ABSTRACT FROM AUTHOR]

The evaluation of land suitability for agricultural production is a complex process that requires specialized information and expert analysis. This paper introduces the Soil Suitability Evaluation (SSE) model, a computer program designed to assess land suitability for agriculture. The model considers soil surface conditions (erosion, micro-relief, and slope), physical characteristics (texture and depth), and chemical properties (salinity, sodicity, fertility, and calcium carbonate). It involves calculating these soil characteristics along with their respective weights. Compared to other land suitability evaluation methods, the SSE model provides realistic and practical results including assessments of soil and crop suitability. It serves as a simple and useful tool for decision-makers to determine land quality for agricultural use and proposed some recommendations for land reclamation. [ABSTRACT FROM AUTHOR]

Bioconversion of organic orange peel wastes into compost (OPC) or biochar (OPB) can help overcome the effects of soil salinity and maintain agricultural productivity. Effect of 1.0% OPC or 1.0% OPB as soil amendments on soil properties and performance of Phaseolus vulgaris plants under two salinity levels [5.60 dS m−1 (S-1) and 9.60 dS m−1 (S-2)] versus control [1.60 dS m−1 (S-0)] was investigated. Compared to the control, S-1 and S-2 increased soil sodium ion (Na+) content, while reducing soil organic matter (OM), macro- and micro-nutrients, cation exchange capacity (CEC), and enzyme (urease, acid phosphatase, and alkaline phosphatase) activities, reflecting decreased plant growth and yield. Under S-1 or S-2, OPC application exceeded OPB application, but both considerably enhanced soil OM content, nutrients, CEC, and enzyme activities. These positive results reflected decreased leaf electrolyte leakage and increased leaf-relative water content, pigments, nutrients, K+/Na+ ratio, antioxidant activity, plant growth, and yield. The beneficial impacts of 1.0% OPC were more pronounced under S-2 than S-1 or S-0. In conclusion, adding 1.0% OPC to saline soil (ECe of about 5–10 dS m−1) could mitigate the influences of soil salinity to improve Phaseolus vulgaris growth, physio-biochemistry, and yield. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) contamination poses significant risks to agricultural productivity and human health, particularly through its accumulation in staple crops such as bread wheat (Triticum aestivum L.). This study evaluated Cd accumulation and tolerance among six bread wheat cultivars exposed to six Cd concentrations (0, 2.5, 5, 10, 15, 20, and 25 mg kg−1 soil). Phenotypic assessments and quantitative real-time PCR (qRT-PCR) were conducted to analyze the expression patterns of TaNRAMP and TaZIP genes in various tissues and developmental stages of wheat, which play crucial roles in Cd uptake and transport. Results demonstrated significant variability in Cd accumulation. The Barat cultivar exhibited the lowest accumulation in grain (ranging from 0.21 to 8.8 mg kg−1) and the highest tolerance. In contrast, Kavir and Pishtaz displayed elevated Cd levels in both grain and straw, while Parsi accumulated more Cd in straw at lower concentrations (56.9 mg kg−1 in Cd concentration of 10 mg kg−1 soil). The gene expression analysis revealed that most cultivars showed increased expression of TaNRAMP genes, particularly TaNRAMP2 in Cd concentration of 10 mg kg−1 soil, which facilitates Cd uptake from the soil, and TaZIP genes, such as TaZIP4 and TaZIP7, involved in transporting Cd within the plant. Notably, the expression of TaZIP1 was significantly lower in cultivars with high Cd accumulation, suggesting a potential regulatory mechanism for Cd tolerance. Furthermore, cultivars exhibiting higher Cd levels correlated with increased expression of stress-responsive genes, indicating a broader response to Cd stress. These findings highlight Barat's potential for bread-making applications due to its low Cd accumulation, while Morvarid and Pishtaz which show reduced Cd content in the straw even under high Cd exposure are better suited for animal feed. This research underscores the genetic variability of wheat cultivars in response to Cd stress and provides essential insights into the molecular mechanisms underlying Cd accumulation, offering valuable information for breeding programs aimed at developing Cd-tolerant varieties to ensure food security in contaminated regions. [ABSTRACT FROM AUTHOR]

This study analyses the climate change and technological change impact on food production in Benin using data from the agriculture ministry and Climate Analytics over the period 1995–2015 and a bio‐economic model. The results suggest that land‐use changes may depend on crop types and prevailing future conditions. With respect to crop production, the results show that the climate change effect on different crops varies from one municipality to another. Moreover, crops such as rice and soybean will benefit more from climate change in several Benin's municipalities, while maize will suffer from climate change. Moreover, results showed technological change globally mitigates the negative impact of moderate climate change. The results suggest that Beninese's government must invest in agriculture technology through agriculture and engineering high schools' installation, which could improve farmers' productivity and efficiency. [ABSTRACT FROM AUTHOR]

Introduction: Although drought resistance of a plant may be achieved through morphological, structural, physiological, cellular, and molecular adaptations, most studies remain limited to quantifying the effect of drought on biomass. Methods: Using a highthroughput phenotypic imaging system, we evaluated the drought resistance of 151 bean accessions (Phaseolinae; Fabaceae) in an explorative approach, by quantifying five different traits simultaneously: biomass, water use efficiency (WUE), relative water content (RWC), chlorophyll content (NDVI), and root/shoot ratio. Since crop wild relatives are important resources for breeding programs, we analyzed both wild and cultivated accessions, most of which have never been evaluated for drought resistance before. Results: We demonstrate that the five traits are affected very differently by drought in the studied accessions, with significant correlations existing only between the biomass and WUE indicators (r=0.39), and between the RWC and NDVI indicators (r=0.40). When grouping accessions by subgenus or by species, large intraspecific and withinsubgenus variation was found. For this reason, we performed a cluster analysis, which grouped the accessions into five distinct clusters with similar response profiles. We also correlated the drought resistance for each accession to local climate variables at their original collection sites. The biomass, WUE, and RWC indicators were significantly correlated to annual precipitation (r=0.40, r=0.20, r=0.22, respectively), confirming that accessions from arid environments are generally more drought resistant. Discussion: Our results demonstrate that the drought resistance of Phaseolinae beans is a multifaceted characteristic and cannot be simply quantified through biomass. Furthermore, the broader knowledge of the drought resistance of the accessions studied here may prove an invaluable resource for future crop production. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is essential for agricultural productivity, yet its surplus poses significant environmental risks. Currently, over half of applied nitrogen is lost, resulting in resource wastage, contributing to increased greenhouse gas emissions and biodiversity loss. Excess nitrogen persists in the environment, contaminating soil and water bodies for decades. Quantifying detailed historical N-surplus estimation in India remains limited, despite national and global-scaled assessments. Our study develops a district-level dataset of annual agricultural N-surplus from 1966-2017, integrating 12 different estimates to address uncertainties arising from multiple data sources and methodological choices across major elements of the N surplus. This dataset supports flexible spatial aggregation, aiding policymakers in implementing effective nitrogen management strategies in India. In addition, we verified our estimates by comparing them with previous studies. This work underscores the importance of setting realistic nitrogen management targets that account for inherent uncertainties, paving the way for sustainable agricultural practices in India, reducing environmental impacts, and boosting productivity. [ABSTRACT FROM AUTHOR]

Integrated systems are efficient technologies used for diversifying production and promoting agricultural sustainability. The benefits of double intercropping are well-established in research. With advancements in sustainable food production technology, some studies have explored triple intercropping by adding legumes. However, triple intercropping methods must be comprehensively understood. This study aimed to evaluate the production of dry mass, fermentation profile, and nutritive values of silage from maize based intercropping. The experiment was conducted in the field, in Instituto Federal Goiano, Campus Rio Verde, State of Goiás, Brazil, where we assessed silage production and quality in monoculture and intercropping systems, in a randomized block complete design with three replications. We evaluated 8 treatments, consisting of silage from: maize monoculture; Tamani guinea grass monoculture; Quênia guinea grass monoculture; Zuri guinea grass monoculture; Pigeon pea monoculture; maize + Tamani guinea grass + Pigeon pea; maize + Quênia guinea grass + Pigeon pea and maize + Zuri guinea grass + Pigeon pea. The results showed that maize silage intercropped with cultivars of Panicum maximum (Tamani, Quênia and Zuri guinea grasses) and Pigeon pea increased silage mass production by 37.8% and the crude protein content at 25.1% compared with that of the monoculture maize silage. It also improved the fermentation characteristics of silage, reducing 5.1% of pH, 32.5% of buffering capacity, 28.9% of ammoniacal nitrogen in total nitrogen, 15.7% of effluent production, and 20.0% of dry matter losses, compared with those of grass and legume silage in monoculture. Thus, the silage produced by the triple intercropping proved to be an efficient technique for sustainable forage production. [ABSTRACT FROM AUTHOR]

Introduction: Enhancing agricultural productivity and promoting sustainable development in China are critical priorities, given their significant contribution to food security and rural development. However, achieving consistent agricultural productivity growth across regions and sectors has been challenging, leading to inefficiencies and environmental pressures. To address this, the potential of digital inclusive finance (DIF) as a catalyst for progress has been explored. Methods: This study investigates the impact of DIF on agricultural total factor productivity (ATFP) through farmland transfer, with implications for rural revitalization and high-quality agricultural development. Using the HMB index method, we calculate and decompose China's inter-provincial ATFP from 2011 to 2020. Employing the dynamic panel fixed effect model and SYS-GMM method, we empirically test the influence of DIF on agricultural productivity in relation to farmland transfer. Results and discussion: Our findings reveal a slow upward trend in China's ATFP, driven primarily by scale efficiency. Notably, a 1% increase in the general index of DIF correlates with a 0.136% increase in ATFP. We analyze the sub-classification indexes of digital inclusive finance, namely coverage breadth, depth of use, and digitalization degree. Their contributions to agricultural productivity growth are significant, with coverage breadth having the greatest impact, followed by depth of use and digitalization degree. Farmland transfer acts as a crucial intermediary, enhancing agricultural allocation efficiency and driving the relationship between digital finance and total factor productivity growth. Interestingly, the western region exhibits the highest growth rates, followed by the eastern region, while the central region shows no significant effects. Conclusion: To comprehensively enhance ATFP, aligning supply and demand for digital financial services, leveraging service depth, and guiding farmland transfer according to local conditions are essential. These findings offer valuable insights into effective strategies for maximizing the potential of DIF, promoting rural development, and achieving sustainable agricultural growth. [ABSTRACT FROM AUTHOR]

The sub-Saharan Africa region continues to experience food insecurity, a consequence of the less productive agricultural sector that has dragged to adapt to the effects of climate change. As the region's population continues to grow, there is a need to modernize the region's agricultural sector to meet the increasing food demand. Although extreme atmospheric conditions cannot be entirely mitigated, however, the integration of technologies such as the Internet of things (IoT) and machine learning (ML) can increase the quantity and quality of production from the crop fields. These technologies have the potential to empower agricultural management systems to handle both climatic and farm data in an orchestrated manner, and inform the formulation of effective strategies. This study presents the design and development of a system for predicting crop yields that integrates IoT and ML. The system combines historic and current weather and crop yield data to predict seasonal crop yields. The weather parameters including, rainfall, temperature, humidity and soil moisture are collected by IoT sensors and transmitted to the cloud for crop yield forecasting. The system is used to analyze seasonal yields of Irish-Potato and Maize in Musanze District of Rwanda. Using data over different agricultural seasons, the system achieved favorable predictive accuracy with mean absolute percentage error (MAPE) values of 0.339, 0.309, and 0.177 for two seasons of Irish potatoes and one season of maize, respectively. Such predictive yield systems can reduce food insecurity risks and enhance harvest efficiency by enabling early awareness of crop production, fostering effective strategies shared among decision-makers and stakeholders. While maize and Irish potatoes were the initial case studies, expansion to include other crops and more variables is envisioned. [ABSTRACT FROM AUTHOR]

Quantifying seedling emergence pressure or forces (soil impedance to seedling) during the process of plant emergence is difficult in a practical setting. In this study, a mechanical seedling testing device was designed and calibrated to measure seedling emergence pressures experienced by conical or spherical mechanical seedling in soil with varying compaction levels. The data were analysed to generate regression models for predicting seedling emergence forces. Results showed a high correlation between the seedling emergence pressure and soil resistance. The resultant regression model produced a coefficient of determination (R2) of 0.99. After incorporating the morphological characteristics of soybean cotyledon and maize coleoptile into the model, the predicted seedling emergence forces increased with the soil compaction level. During the emergence process, average emergence force of the soybean seedlings was 11.8 N for the lowest compaction level and 28.5 N for the highest compaction level, and the corresponding values of the maize seedlings were 0.2 N and 0.6 N. In a non-compacted field plot, maize crop had a 95.4% emergence rate and soybean crop had 97.2%, whereas for a compacted plot, the corresponding emergence rates were decreased to 19.1% and 60.5%. Inferences made from the study provide information on the dynamics of soil-seedling interaction, which have important implications for managing soil compaction in crop production. • A testing device was developed to measure seedling emergence forces. • Regression models were generated from the measurement data. • Models predicted the seedling emergence forces of soybean and maize. • Seedling emergence force increased significantly with increasing soil compaction. [ABSTRACT FROM AUTHOR]

Human–elephant conflict is growing in Africa as human populations and development increases, creating disturbance to elephant habitats. Beehive fences have been trialed as a coexistence tool with some success but all studies have looked at small sample sizes over a short time period. Our study analyses the behavior of African elephants (Loxodonta africana) that approached a network of beehive fence protected farms in two conflict villages over 9 years next to Tsavo East National Park. We compare differences in elephant raids and beehive occupation rates annually, during a drought, and during peak crop production seasons. Out of 3999 elephants approaching our study farms 1007 elephants broke the beehive fence and entered the protected farm areas (25.18%). This was significantly less than the 2649 encounters where elephants remained either outside the farm boundary or broke into the control farms (66.24%). A further 343 elephants entered the farm by walking through a gap at the end of a fence (8.56%). The annual beehive fence break‐through rates averaged 23.96% (±SE 3.15) resulting in a mean of 76.04% elephants deterred from beehive fences protected farm plots. Over six peak crop growing seasons the beehive fences kept between 78.3% and 86.3% of elephants out of the farms and crops. The beehive fences produced one ton of honey sold for $2250; however, a drought caused a 75% reduction in hive occupation rates and honey production for 3 years after negatively impacting honey profits and the effectiveness of the fences. Beehive fences are very effective at reducing up to 86.3% of elephant crop‐raids during peak crop seasons after good rainfall, but any increase in elephant habitat disturbance or the frequency and duration of droughts could reduce their effectiveness as a successful coexistence tool. [ABSTRACT FROM AUTHOR]

The study presents the potential use of winemaking residues, specifically grape pomace, for energy purposes. The pomace was obtained from the cultivation of the Regent grape variety on three different rootstocks—125AA, 161-49, and SO4—as well as a control group grown on its own roots. The research included determining the calorific value and combustion heat, conducting a technical and elemental analysis of the potential biofuel, as well as estimating emission indicators (CO, CO2, NOx, SO2, and particulate matter) and the theoretical volume of flue gases based on stoichiometric equations. The study revealed significant differences among the combustion heat, tested properties and calorific value, ash content, and the total volume of flue gases. The highest calorific value (17.7 MJ kg−1) and combustion heat (18.9 MJ kg−1) were obtained for pomace from the SO4SO4 rootstock, while the lowest values were observed in the control group (17.0 MJ·kg−1 and 15.8 MJ·kg−1, respectively). The highest ash content was also recorded for the SO4 rootstock (9.2%), with the lowest in the control group (6.7%). The control group exhibited the lowest CO2 emissions at 1390.50 kg·Mg−1, while the highest emissions were found in the pomace from the SO4 rootstock (1478.8 kg·Mg−1). Regarding the total flue gas volume, the highest volume was estimated for the pomace from the 125AA rootstock (7.8 m3·kg−1) and the lowest for the control group (7.3 m3·kg−1). The research demonstrated that grape pomace possesses favorable energy properties and could serve as a potential biofuel, contributing to the fuel and energy balance of agricultural production enterprises. The analyzed biomass exhibits properties similar to agrobiomass. [ABSTRACT FROM AUTHOR]

A comparison and evaluation of the AEP(Annual Energy Production) of a wind farm were conducted in this study with a feasibility study and using the actual operation data from the S wind farm on Jeju Island from January 2020 to December 2022. The free wind speed data were selected from the data measured from a nacelle anemometer, the correlation equation between wind speed and AEP was obtained, and the annual average wind speed for the past 20 years was predicted using the MCP method. As a result, comparing the AEP from the operation data with that estimated in the feasibility study, we found that the AEP was reduced by approximately 2.40% in 2020 and 12.14% in 2021, and increased by 6.76% in 2022. The wind speeds over the 20-year lifetimes of the wind turbines were obtained, and the AEP that could be generated at the S wind farm indicated that it could be used for operation. In the future, the S wind farm will operate at between 25% and 30% availability for the remaining 17 years of operation. If the availability falls below 25%, there will be a need to check the reasons for the deterioration of wind turbine performance and the frequency of failures. [ABSTRACT FROM AUTHOR]

Agriculture is the strength of our nation, and its production rate is also important for feeding food to all. The crop production rate is more significantly affected by various diseases. Currently, these diseases are identified and classified using a visual inspection method, which is not suitable for larger crop fields. Therefore, a machine-based, systematic approach is needed to identify various diseases that occur on the leaves of the jasmine plant. The present article develops and proposes a computer-based systematic approach to the detection and diagnosis of jasmine plant diseases using the dual deep learning method. The proposed classifier consists of a general adversarial network (GAN) module and a proposed convolutional neural network (CNN) architecture for diagnosing diseases in the jasmine plant. The GAN module extracts the features from the dataaugmented jasmine plant leaf image, and the CNN module performs the disease classification process. The proposed CNN module contains both lower and higherorder kernels that produce the hybrid features, which are further classified by the CNN architecture. The proposed classification approach is validated on the set of jasmine plant leaf images. The simulation is carried out using MATLAB software, and the results of the plant leaf classification system are compared with state-of-the-art models in terms of crop sensitivity, crop specificity and accuracy. [ABSTRACT FROM AUTHOR]

Tropical tuber crops such as cassava, sweet potatoes and elephant foot yam play vital roles in global food security and economic development, particularly in developing nations. The present study examines the current scenario of tuber crop production and trade dynamics, focusing on India's role both as a producer and an exporter. Using empirical data from various sources including Food and Agriculture Organization of the United Nations and Agricultural and Processed Food Products Export Development Authority, the study analyses production trends, trade patterns and policy frameworks, to elucidate potential pathways for enhancing productivity, sustainability and competitiveness in the tuber crops sector. The analysis reveals significant growth in cassava and sweet potato production globally, with India emerging as a key player. However, climate change, pests and diseases, soil degradation, and trade barriers pose hurdles to the growth of the sector. This study also recommends comprehensive strategies, including climate-resilient agricultural practices, integrated pest management, soil health enhancement and infrastructure development, to address these challenges and promote the sustainable growth of tuber crops. [ABSTRACT FROM AUTHOR]

A comprehensive study of the Mundrothruthu (MT) core (70 cm) from the Asthamudi wetland in Kollam, Kerala, India reveals three climate phases during the Little Ice Age (LIA) through multi-proxy investigations. The period (1507–1518 CE) shows high agricultural activity indicated by abundant diatom diversity, significant terrestrial influx, and freshwater runoff. Elevated TOC% and δ13C TOC values suggest high temperature and a warm, humid climate, likely driven by high terrestrial influx and transport of organic matter from the nearby surroundings. This may have increased the organic matter influx to the estuary leading to high TOC% and more negative δ1³C values. The second phase (1519–1548 CE) is characterized by increased marine incursion due to enhanced tidal currents, evidenced by a rise in marine palynomorphs, mixed terrestrial and marine organic matter, less negative δ13C values, and increased mud content. This shift likely reflects changes in sea level or tidal dynamics. The final period (1548–1804 CE) is marked by further enhancement of marine taxa, lower TOC%, and δ13C TOC values, indicating reduced atmospheric CO 2 and a temperature decrease of about 1 °C. This period is associated with reduced solar insolation and a southward shift of the Inter Tropical Convergence Zone (ITCZ). The study highlights both synchronous and asynchronous climatic behavior on the southwest coast of India relative to global changes during the LIA. Initially warm and humid with high agricultural productivity, the region gradually shifted to marine-dominated conditions due to tidal dynamics and broader climatic shifts. These findings underscore the complex interplay between local and global climatic factors during the LIA. [ABSTRACT FROM AUTHOR]

The UN Decade on Ecosystem Restoration will result in an unprecedented need for seeds. Agricultural production, or the growing of plants under controlled conditions to produce desired resources, can be a helpful tool for providing the quantities of seeds needed for large‐scale restoration. In some ecosystems, agricultural production of native plant seeds is part of the restoration process. This is particularly true for native plants that are similar to major food crops, such as native grasses. However, conventional crops have contrasting characteristics (e.g. fast growing, high yield for a focused use) from those desired in restored vegetation (plants capable of surviving and providing ecosystem services in variable environments). This contrast leads to significant, often opposing differences in desirable characteristics in crop versus natural systems. Examples include rapid germination in domesticated crops versus seed dormancy in wild plants, uniform germination, growth and flowering versus bet‐hedging strategies, or high seed retention versus seed dispersal. While it may be useful to maximize productivity of native plants in agricultural environments with similar trait modifications, for restoration, the demands of the natural environment should be primary, and agricultural production should aim to maximize the diversity, function, and evolutionary potential of native species. Any perceived benefits that come from the production of large quantities of inexpensive seeds that cannot meet the needs of wild communities are short‐sighted. We suggest research directions that will be needed to meld agricultural production needs with those of restoration practitioners, as a challenge for those invested in the procurement and use of wild seeds. [ABSTRACT FROM AUTHOR]

New approaches are required in the agricultural sector to keep pace with the ever-growing demand for food in the context of climate change and resource deterioration and avoiding further negative impact on the environment. Nonthermal plasma is an environmentally-friendly technology which could make a difference in future agricultural production. This review intends to introduce the topic of plasma agriculture to a broad audience by describing in detail various plasma sources with potential for agricultural applications, as well as the effects of plasma exposure of seeds, both at the macroscopic scale, and concerning the intimate mechanisms occurring inside the plant. Examples meant to illustrate the plasma effect on seeds and plants have been selected among extensively investigated species, such as cereals and legumes, as well as among a few species that are less often reported in literature, such as medicinal plants and woody plants. Generally, the main effects for all types of seeds consist in increased germination, higher plant yield, seed decontamination, and sometimes higher tolerance to various stress factors. These effects are due to the physical and chemical plasma interaction with seeds followed by the response of cell mechanisms, which are addressed in detail in the paper. Finally, a few crucial aspects regarding the practical application of nonthermal plasma in agriculture are discussed to illustrate the challenges and perspective of such treatments. [ABSTRACT FROM AUTHOR]

The hormonal variation essential for fruit set differs regarding crop species. Parthenocarpy is a key trait to reduce the climate dependency of fruit crops. Two distinct molecular mechanisms lead to a gibberellin-induced fruit setting. Transcription factors and miRNA interactions control parthenocarpy in several species. Fruit development is essential for flowering plants' reproduction and a significant food source. Climate change threatens fruit yields due to its impact on pollination and fertilization processes, especially vulnerable to extreme temperatures, insufficient light, and pollinator decline. Parthenocarpy, the development of fruit without fertilization, offers a solution, ensuring yield stability in adverse conditions and enhancing fruit quality. Parthenocarpic fruits not only secure agricultural production but also exhibit improved texture, appearance, and shelf life, making them desirable for food processing and other applications. Recent research unveils the molecular mechanisms behind parthenocarpy, implicating transcription factors (TFs), noncoding RNAs, and phytohormones such as auxin, gibberellin (GA), and cytokinin (CK). Here we review recent findings, construct regulatory models, and identify areas for further research. [ABSTRACT FROM AUTHOR]

In future cropping systems, a focus on belowground plant–soil interactions should exploit the synergy of plant responses to multiple soil factors to maximize the biological potential of roots. Key soil factors include root-zone heterogeneity arising from the physical, biological, and chemical properties varying in time and space. Optimizing the match between root functioning and soil properties is needed to achieve increased crop productivity and improved soil health. The integration of plant and soil sciences, and the application of holistic plant–soil solutions in the crop systems, will provide effective new approaches towards a more sustainable crop production. The Green Revolution transformed agriculture with high-yielding, stress-resistant varieties. However, the urgent need for more sustainable agricultural development presents new challenges: increasing crop yield, improving nutritional quality, and enhancing resource-use efficiency. Soil plays a vital role in crop-production systems and ecosystem services, providing water, nutrients, and physical anchorage for crop growth. Despite advancements in plant and soil sciences, our understanding of belowground plant–soil interactions, which impact both crop performance and soil health, remains limited. Here, we argue that a lack of understanding of these plant–soil interactions hinders sustainable crop production. We propose that targeted engineering of crops and soils can provide a fresh approach to achieve higher yields, more efficient sustainable crop production, and improved soil health. [ABSTRACT FROM AUTHOR]

The efficacy of Azospirillum argentinense REC3, applied by seed inoculation, in enhancing soybean (Glycine max [L.] Merr.) nodulation with native rhizobia, improving grain yield, and protecting against Fusarium fungi was studied. In La Cruz, Tucumán, Argentina, 23 fungal isolates were identified as F. oxysporum (2 strains), F. solani (2), and F. tucumaniae (19). Following soil infestation, only F. tucumaniae was confirmed as a phytopathogen, with REC3 inhibiting its mycelial growth. Greenhouse trials, for a duration of 30 days, showed significant reductions in disease severity (78.2%), root rot (32.3%), and disease incidence (50.9%) in plants susceptible to sudden death syndrome (SDS) when REC3 was applied. Field experiments (2018–2019; January-April) under drought stress conditions, displayed increased nodulation (37.2%) and grain yield (2077 ± 272.8 kg ha−1, p < 0.05) in REC3-treated plants compared to controls (1516 ± 272.8 kg ha−1, p < 0.05). Additionally, a low disease incidence (0.90%) was observed only in the SDS-susceptible soybean variety without REC3 treatment. Overall, the findings showed the significant potential of REC3 inoculation as a biotechnological strategy for enhancing agricultural productivity, managing diseases, and improving crop resilience under challenging environmental conditions. This integrated approach, combining the use of a partially SDS-resistant soybean variety with REC3 inoculation, showed promise in protecting soybean cultivation against SDS and other fungal diseases, thereby ensuring more sustainable and resilient agricultural practices. [ABSTRACT FROM AUTHOR]

SUMMARY: Wheat (Triticum aestivum L.) is a globally staple crop vulnerable to various fungal diseases, significantly impacting its yield. Plant cell surface receptors play a crucial role in recognizing pathogen‐associated molecular patterns (PAMPs) and activating PAMP‐triggered immunity, boosting resistance against a wide range of plant diseases. Although the role of plant chitin receptor CERK1 in immune recognition and defense has been established in Arabidopsis and rice, its function and potential agricultural applications in enhancing resistance to crop diseases remain largely unexplored. Here, we identify and characterize TaCERK1 in Triticeae crop wheat, uncovering its involvement in chitin recognition, immune regulation, and resistance to fungal diseases. By a comparative analysis of CERK1 homologs in Arabidopsis and monocot crops, we demonstrate that AtCERK1 in Arabidopsis elicits the most robust immune response. Moreover, we show that overexpressing TaCERK1 and AtCERK1 in wheat confers resistance to multiple fungal diseases, including Fusarium head blight, stripe rust, and powdery mildew. Notably, transgenic wheat lines with moderately expressed AtCERK1 display superior disease resistance and heightened immune responses without adversely affecting growth and yield, compared to TaCERK1 overexpression transgenics. Our findings highlight the significance of plant chitin receptors across diverse plant species and suggest potential strategies for bolstering crop resistance against broad‐spectrum diseases in agricultural production through the utilization of plant immune receptors. Significance Statement: CERK1 acts as a chitin immune receptor for plant defense and survival, but its role and applied potential in Triticeae crops remain unknown. We identify TaCERK1 in wheat, revealing distinct characteristics of CERK1 homologs in chitin recognition and immune activation between cereals and the dicot Arabidopsis. Notably, overexpressing CERK1s from both cereal and Arabidopsis in wheat confers broad‐spectrum resistance to fungal diseases. Our findings highlight the potential of plant immune receptors in controlling crop diseases. [ABSTRACT FROM AUTHOR]

The increasing levels of cadmium (Cd) pollution in agricultural soil reduces plant growth and yield. This study aims to determine the impact of green synthesized zinc oxide nanoparticles (ZnO-NPs) on the physiochemical activities, nutrition, growth, and yield of Zea mays L. under Cd stress conditions. For this purpose, ZnO-NPs (450 ppm and 600 ppm) synthesized from Syzygium aromaticum were applied through foliar spray to Z. mays and also used as seed priming agents. A significant decline in plant height (35.24%), biomass production (43.86%), mineral content, gas exchange attributes, and yield (37.62%) was observed in Cd-spiked plants compared to the control. While, 450 ppm ZnO-NPs primed seed increased plant height (18.46%), total chlorophyll (80.07%), improved ascorbic acid (25.10%), DPPH activity (26.66%), and soil mineral uptake (Mg+2 (38.86%), K+ (27.83%), and Zn+2 (43.68%) as compared to plants only spiked with Cd. On the contrary, the foliar-applied 450 ppm ZnO-NPs increased plant height (8.22%), total chlorophyll content (73.59%), ascorbic acid (21.39%), and DPPH activity (17.61%) and yield parameters; cob diameter (19.45%), and kernels numbers 6.35% enhanced compared to plants that were spiked only with Cd. The findings of the current study pave the way for safer and more cost-effective crop production in Cd-stressed soils by using green synthesized NPs and provide deep insights into the underlying mechanisms of NPs treatment at the molecular level to provide compelling evidence for the use of NPs in improving plant growth and yield. NOVELTY STATEMENT: Novelty statement: Phyto zinc nanoparticles improve stress tolerance and growth of Zea mays under cadmium stress [ABSTRACT FROM AUTHOR]

Weeding is an important part of agricultural production. With the development of science and technology, automated weeding is regarded as the future development direction, and how to accurately and efficiently detect plants in the field is one of the key points. Corn seedlings and weeds are similar in color, shape and other characteristics, which brings serious challenges to plant detection. In this paper, we propose an improved model based on YOLOv7-tiny, called DC-YOLO. To improve the extraction of key features in the model, we propose Dual Coordinate Attention model (DCA). In addition, we introduce the Content-Aware ReAssembly of FEatures (CARAFE) operator to represent the up-sampling process as a learnable feature reorganization, which enriches the feature information of the sampled images. Finally, we decoupled the detection head to minimize conflicts between features from different tasks. The results show that applying the proposed method to corn and weed datasets, the detection accuracy of the model reaches 95.7% mean Average Precision (mAP@0.5), the computational effort of the model is 13.083 Giga Floating-point Operations (GFLOPs), and the parameter size is 5.223 Millon (M), which is better than the rest of the mainstream light-weight target detection model. [ABSTRACT FROM AUTHOR]

Rice is one of the major food crops, and the study of suitable planting areas for rice plays an important role in improving rice yield and optimizing the production layout. This study used Maximum Entropy (MaxEnt) model to simulate and predict the distribution of suitable rice planting areas in China from 1981 to 2020 by combining the climate, soil, and human activities, analyzed the spatial and temporal changes of suitable rice planting areas in China, and determined the main factors affecting rice planting suitability. The results indicated that the main factors influencing the distribution of suitable planting areas for rice in China were gross domestic product (GDP), population density (Pop), and annual sunshine duration (Sun), with human activities playing a dominant role. The high suitable planting areas of rice were mainly distributed in Hubei, Hunan, Jiangxi, Anhui, Guangdong, southeastern Sichuan and western Guizhou. The total suitable planting areas for rice were 346.00 × 104 km2, 345.66 × 104 km2, 347.01 × 104 km2, and 355.57 × 104 km2 from 1981 to 1990, 1991 to 2000, 2001 to 2010 and 2011 to 2020, respectively. With the passage of time, the area of unsuitable areas for rice gradually decreased, and the area of medium suitable areas increased, with large changes in the area of high- and low-suitable areas. Moreover, due to the transfer of a large number of rural laborers to the cities in recent years, the tension between people and land caused by the population explosion has led to the increasing impact of Pop on rice suitable areas and the relatively weakening of the impact of GDP on rice production interventions. The results can be used to provide scientific evidence for the management of rice cultivation and food production safety, with a view to reducing the impacts of climate change on agricultural production in the context of global climate change. [ABSTRACT FROM AUTHOR]

The response of agricultural productivity anomalies to drought stress plays a crucial role in the carbon cycle within terrestrial ecosystems and in ensuring food security. However, detailed analysis of how global agricultural productivity anomalies response to drought stress, particularly within irrigated and rainfed agricultural systems, remains insufficient. In this study, the impact of drought stress on agricultural productivity anomalies during the growing season (zcNDVIS), across both irrigated and rainfed agriculture, were analyzed using a suite of hydro-climatic variables. Specifically, the investigation utilized the multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI), the Multivariate ENSO Index (MEI), and the Madden-Julian Oscillation (MJO). Meanwhile, the relationships between hydroclimatic variables and zcNDVIS were analyzed at one, two, three and four months before the ending of growing season (EOS). Results showed that (1) the percentages of significant (p<0.1) drying trends varied across the globe from 8.30% to 13.42%, 6.50% to 14.63%, 6.52% to 14.23%, and 6.47% to 14.95% at one-, two-, three-, and four-month lead times before EOS, respectively, during 2001–2020, which represented by the multiscalar SPEI. This observation highlights that most regions across the globe tend to be arid, which could significantly impact agricultural productivity; (2) the global mean correlation coefficients (rmax) for SPEI-1, SPEI-3, SPEI-6, SPEI-12 (indicating SPEI at 1-, 3-, 6-, and 12-month lags), MEI, and MJO with zcNDVIS ranged between 0.24–0.25, 0.27–0.28, 0.25–0.26, 0.21–0.22, −0.02–0.01 and 0.06–0.11, respectively, across both irrigated and rainfed agriculture system from 2001 to 2020. Agricultural productivity anomalies demonstrated a significant correlation with drought stress. The strongest correlations were noted for SPEI-3 and SPEI-6, suggesting a delayed response of crops to drought conditions. This indicates that agriculture ecosystem experiences prolonged disturbances due to abiotic drought stress; and (3) the percentages of regions that showed significant correlations (p<0.1) between zcNDVIS and drought indices (SPEI-1, SPEI-3, SPEI-6, and SPEI-12), as well as climate indices (MEI and MJO) ranged as follows: 14.77%–20.27%, 21.51%–32.55%, 22.60%–35.68%, 21.89%–35.16%, 7.93%–11.20% and 9.44%–17.94%. Quantitatively identifying how zcNDVIS spatially responds to hydro-climatic variables can help us better understand the impact of drought on agricultural productivity anomalies worldwide. [ABSTRACT FROM AUTHOR]

Salt-induced stress poses a significant barrier to agricultural productivity by impeding crop growth. Presently, environmentalists are dedicated to safeguarding food security by enhancing agricultural yields in challenging environments. Biostimulants play a crucial role in mitigating abiotic stresses in crop production, and among these, plant essential oils (EOs) stand out as organic substances with diverse biological effects on living organisms. Among the natural promoters of plant growth, Rosmarinus officinalis L. essential oil (RoEO) has gained considerable attention. Although the manifold effects of essential oils (EOs) on plant growth have been extensively demonstrated, their impact on salt stress tolerance in durum wheat seedlings remains unexplored. This investigation was undertaken to evaluate the biostimulatory capabilities of RoEO on the durum wheat cultivar "Mahmoudi." The effects of three RoEO concentrations (1, 2.5, and 5 ppm) on seed germination, growth establishment, and the induction of salt resistance under salinity conditions (150 mM NaCl) were tested. At 5 ppm, RoEO enhanced seedlings' tolerance to salinity by improving growth and reducing membrane deterioration and oxidative stress-induced damage. The expression profile analyses of seven stress-related genes (TdNHX1, TdSOS1, TdSOD, TdCAT, TdGA20-ox1, TdNRT2.1, and TdGS) using RT-qPCR showed enhancement of several important genes in durum wheat seedlings treated with 5 ppm RoEO, even under control conditions, which may be related to salt stress tolerance. The results indicate that the application of RoEO suggests a possible alternative strategy to increase salt tolerance in durum wheat seedlings towards better growth quality, thus increasing ROS scavenging and activation of antioxidant defense. [ABSTRACT FROM AUTHOR]

Summary: Societal Impact Statement: Climate change continues to intensify the challenges of food production as agricultural systems face more variable and extreme weather. Coupled with increasing human population, growers must balance increasing crop yields with nutrient content to prevent global malnutrition. Photosynthetic diversity may permit some crops to tolerate climate change and elevated CO2 whilst maintaining both crop yield quantity and quality. This review examines how photosynthetic diversity interacts with crop production and nutritional stability under elevated CO2 and climate change, and highlights opportunities for photosynthetic diversity to inspire agricultural solutions. Summary: Innovative agricultural solutions are desperately needed to achieve food security for a growing human population amidst the imminent pressures of climate change that threaten more variable and extreme weather, placing additional pressures on already precarious agricultural systems. Not only are crop yields at risk under climate change but rising global atmospheric CO2 concentrations are concurrently driving a carbon dilution effect that threatens to reduce the nutritional quality of our crops to further global malnutrition. Plants using different photosynthetic metabolisms, however, experience these negative impacts to yield and nutrition to different degrees. Thus, photosynthetic diversity may offer solutions to combat malnutrition under climate change and elevated CO2 concentrations, whether that be through targeting existing resilient species for agricultural programmes or applying agricultural biotechnology to engineer photosynthetic diversity into existing crops. Here, we discuss how each major photosynthetic type is predicted to fare under elevated CO2 concentrations and climate change and explore agricultural opportunities to maintain both yield and nutrient stability. [ABSTRACT FROM AUTHOR]

BACKGROUND: The simultaneous prediction of yield and maturity date has an important impact on ensuring food security. However, few studies have focused on simultaneous prediction of yield and maturity date for wheat–maize in the North China Plain (NCP). In this study, we developed the prediction model of maturity date and yield (PMMY) for wheat–maize using multi‐source satellite images, an Agricultural Production Systems sIMulator (APSIM) model and a random forest (RF) algorithm. RESULTS: The results showed that the PMMY model using peak leaf area index (LAI) and accumulated evapotranspiration (ET) has the optimal performance in the prediction of maturity date and yield. The accuracy of the PMMY model using peak LAI and accumulated ET was higher than that of the PMMY model using only peak LAI or accumulated ET. In a single year, the PMMY model had good performance in the prediction of maturity date and yield. The latitude variation in spatial distribution of maturity date for WM was obvious. The spatial heterogeneity for yield of wheat–maize was not prominent. Compared with 2001–2005, the maturity date of the two crops in 2016–2020 advanced 1–2 days, while yield increased 659–706 kg ha−1. The increase in minimum temperature was the main meteorological factor for advance in the maturity date for wheat–maize. Precipitation was mainly positively correlated with maize yield, while the increase in minimum temperature and solar radiation was crucial to the increase in yield. CONCLUSION: The simultaneous prediction of yield and maturity can be used to guide agricultural production and ensure food security. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The fall armyworm, Spodoptera frugiperda (J. E. Smith), identified as an invasive pest worldwide, has severely threatened agricultural production and food security in India. To formulate eco‐friendly integrated pest management strategies for S. frugiperda in its new invasive habitat, the basic knowledge about demographic parameters and damage potential of this pest is crucial. The effects of five host crops viz. maize (Zea mays L.), popcorn (Zea mays everta Sturt), sweet corn (Zea mays saccharata Sturt), sorghum (Sorghum bicolor (L.)) and soybean (Glycine max (L.) Merr.) on the development and food consumption of S. frugiperda were examined. Population projection curves based on life table and consumption rates were drawn on different hosts using computer simulation.The pre‐adult development of S. frugiperda was fastest on popcorn (28.02 days), maize (28.04 days) and sweet corn (28.31 days) but slowest on soybean (34.83 days). The highest net reproductive rate, intrinsic rate of increase and finite rate of increase were observed on maize. The feeding potential of S. frugiperda was also highest on maize. The maximum consumption of the sixth larval instar was observed on maize (19470.47 mm2) while lowest on soybean (9033.67 mm2). In the simulation period of 90 days, the fastest growth of S. frugiperda was expected on maize, popcorn and sweet corn while the slowest on soybean.High larval and pupal survival recorded on the non‐maize hosts (sorghum and soybean) reflects that fall armyworm could be an obstacle in their production as well as in the success of maize‐soybean intercropping system. Simulations based on age‐stage, two‐sex life table could be helpful in predicting the most appropriate time for the pesticide application as well as augmentative releases of egg and larval parasitoids for the control of fall armyworm. [ABSTRACT FROM AUTHOR]

Efficient soybean mapping is critical for agricultural production and yield prediction. However, current sample-driven soybean mapping methods heavily rely on large representative sample datasets, limiting the interpretability of physical mechanisms. Besides, sample-free methods failed to exploit key features that differentiate soybean from other crops, especially Chlorophyll content. Misclassification errors persist and spatiotemporal generalization remains limited. Therefore, this study develops a novel Soybean Mapping Composite Index (SMCI) within a precise Global Optimal Time Window (GOTW). It integrates unique features of soybean Chlorophyll content, canopy water content, and canopy greenness by coupling three red-edge bands (RE2, RE3, and RE4), one near-infrared band, one shortwave infrared band, and two feature indices (Enhanced Vegetation Index and Green Chlorophyll Vegetation Index). The novel index was applied to soybean mapping at six sites in four major soybean producing countries (China, Argentina, Brazil, and the United States) from 2019 to 2021, using an optimal threshold of 3.25. Within the GOTW, the index responds better to spectral features and improves soybean separability. The average overall accuracy (OA: 91%) and average Kappa coefficient (Kappa: 0.83) for the novel index at all sites outperformed the traditional sample-driven Random Forest (RF) method (OA: 84%, Kappa: 0.70) and the existing sample-free index-based Greenness and Water Content Composite Index (GWCCI) (OA: 81%, Kappa: 0.64). Furthermore, interannual transfer experiments consistently showed high accuracy, demonstrating robust spatiotemporal transferability. The proposed SMCI index meets the need for a lightweight and stable soybean mapping tool and serves as a valuable reference for efficient global crop mapping. [ABSTRACT FROM AUTHOR]

This study applied plithogenic statistics to evaluate how different doses of guinea pig manure affect the cultivation of Opuntia ficus-indica (commonly known as prickly pear) and soil quality. It was determined that 7.5 tons/ha, referred to as treatment T3, is the optimal dose, as it maximizes the growth and production of the plant, improves plant height, and increases the production of buttons and berries. T3 also optimized organic matter and adjusted the pH to ideal levels, maintaining a nutritional balance that ensures the availability of nitrogen, phosphorus, and potassium. This balance enhances agricultural production without sacrificing soil sustainability. In conclusion, the research showed that T3 provides the best performance, improving soil quality without the risks associated with higher doses. This underscores the need to carefully calibrate organic fertilizers to maximize efficiency and minimize negative environmental impacts. [ABSTRACT FROM AUTHOR]