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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.

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]

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]

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]

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]

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]

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]

Debate persists on light in controlled environment agriculture. To dissect the effects of conventionally used wavelengths on a crop and provide new information to this expanding food production sector, this study investigated the effects of monochromatic and combined red, blue, and amber light on lettuce growth with increasing light intensities (up to 1300 µmol·m−2·sec−1) for 18 days with a 16 h·d−1. Under amber light at PPFDs ranging from 500 to 700 µmol·m−2·sec−1, fresh mass displayed a 33.3% greater yield when compared to red light at the same PPFD. Suppressed growth was observed with either red or amber alone at high PPFD (>800 µmol·m−2·sec−1). Blue light was the least productive of the four treatments, yet lettuce plant growth was not suppressed at high intensities. No growth suppression was observed for lettuce plants grown under combined red-blue-amber light at high intensities, and these plants exhibited greater biomass yield than blue light alone. Varied degrees of pigmentation occurred under each light treatment, yet bleaching was only observed in plants grown under amber light alone at PPFD above 1000 µmol·m−2·sec−1. Findings present novel plant responses to high intensity light, setting precedence for future experiments aimed at expanding the use of LEDs in horticulture. [ABSTRACT FROM AUTHOR]

Purpose: The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains. Design/methodology/approach: The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022. Findings: The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies' financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth. Practical implications: Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth. Originality/value: This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management. [ABSTRACT FROM AUTHOR]

Sustainable agriculture is crucial for meeting the growing global food demand. With the pressure of climate change, resource depletion, and the need for increased agricultural productivity, innovative approaches are essential. Nanotechnology is an emerging technology in achieving sustainable development goals (SDGs). Despite its promising benefits, the safe implementation of nanotechnology in agriculture requires careful consideration of potential health and environmental risks. However, there is a lack of comprehensive documentation on the application, potential and limitations of nanotechnology in the field of agriculture. To address this gap, a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed, Scopus, Google Scholar, Web of Science, and Science Direct for relevant articles. Out of 157 initially identified articles, 85 were deemed pertinent, focusing primarily on potential nanotechnology in smart agricultural systems. Taking into account research findings worldwide, we found significant improvements with nanotechnology over traditional methods which underscores the practical benefits of nanotechnology, including increased crop yields, efficient resource use, and reduced environmental footprint. The objective of this systematic review is to explore the nexus between nanotechnology and agricultural systems, highlighting its potential to enhance productivity, sustainability, and resilience and to inform researchers, practitioners, and policymakers about the transformative impact of nanotechnology on sustainable agriculture and underscores the need for further research to address safety concerns and maximize its potential for agricultural advancement. Article highlights: A thorough study of nanotechnology's new method to lessen fertilizer and pesticide harmful impacts and their responsibilities. Developing an integrated approach for smart farming systems. A guide for future nanotechnology studies in agriculture suggests breakthroughs in biotic and abiotic remediation using nano-particles for a safe climate change scenario. Identifying setbacks, limitations, and solutions. [ABSTRACT FROM AUTHOR]

While a lot has been written on the socio‐economic and welfare impacts of agricultural technologies, there has been a bias toward crop production systems to the neglect of improved livestock production methods and technologies. This paper explores the welfare impacts of improved livestock production practices and technologies using data from a low‐income country. Using an econometrics technique that corrects selection bias, the paper shows that the adoption of improved livestock production practices has a positive impact on household welfare, measured by consumption expenditure and diet quality. The study also identified increased consumption of animal source foods, reducing animal death and income from the sale of animals as potential mechanisms through which such improvements in livestock production affect family welfare. [ABSTRACT FROM AUTHOR]

The purpose of this study is to determine whether hyper spectral images can be used to identify plant diseases and crop pressure from aerial photographs. With extensive research on the prevalent methods used closer to the problem, this study offers a potent strategy for identifying crop distress and illnesses using this efficient imaging technique. To identify the spectral fingerprints of common indications and symptoms of plant diseases and crop strains, this study evaluates the available hyper spectral photo datasets. After that, the data are examined using two learning algorithms--the highly randomized trees and the Random Woodland set of rules--to create predictions that are entirely dependent on the results that are discovered. In the end, a benchmarked set of test statistics is used to assess the prediction accuracy. The results of this study show that hyper spectral photo evaluation has a strong and promising utility for crop stress and disease identification. Hyper spectral light evaluation is a method for identifying plant diseases caused by strain on crops. By gathering and evaluating high-dimensional spectral reflection data from satellite or aircraft structures, details regarding the physiological homes of flowers can be identified. The health of plants, illnesses brought on by stress, and agricultural productivity predictions can all be made using these facts. Hyper spectral recordings can also be used to create actions that reduce agricultural losses and enhance the health of plants that are prone to disease. [ABSTRACT FROM AUTHOR]

The El Haouz and El Kelaa Des Sraghna region is renowned for its agriculture, but is facing problems of salinisation due to its arid climate and unfavourable weather conditions. To remedy this, localised irrigation systems have been introduced to provide water for crops and improve yields. This study examines the impact of these irrigation systems on soil salinity in the region by comparing upstream and downstream areas. Using remote sensing techniques, we identify areas at risk of high salinity and collect soil samples for physical and chemical analysis in the field. These analyses enable us to monitor changes in salinisation and assess the effectiveness of localised irrigation in the areas concerned. Our results reveal two distinct zones in the region: an upstream zone with low salinity, with electrical conductivity ranging from 66 µS/cm to 345 µS/cm, and a downstream zone with higher salinity, with electrical conductivity ranging from 228 µS/cm to 1.075 µS/cm, attributed to the use of localised irrigation for crops. The remote sensing maps anticipated this difference, which was confirmed by the field analyses. [ABSTRACT FROM AUTHOR]

Precision agriculture is evolving toward a contemporary approach that involves multiple sensing techniques to monitor and enhance crop quality while minimizing losses and waste of no longer considered inexhaustible resources, such as soil and water supplies. To understand crop status, it is necessary to integrate data from heterogeneous sensors and employ advanced sensing devices that can assess crop and water status. This study presents a smart monitoring approach in agriculture, involving sensors that can be both stationary (such as soil moisture sensors) and mobile (such as sensor-equipped unmanned aerial vehicles). These sensors collect information from visual maps of crop production and water conditions, to comprehensively understand the crop area and spot any potential vegetation problems. A modular fuzzy control scheme has been designed to interpret spectral indices and vegetative parameters and, by applying fuzzy rules, return status maps about vegetation status. The rules are applied incrementally per a hierarchical design to correlate lower-level data (e.g., temperature, vegetation indices) with higher-level data (e.g., vapor pressure deficit) to robustly determine the vegetation status and the main parameters that have led to it. A case study was conducted, involving the collection of satellite images from artichoke crops in Salerno, Italy, to demonstrate the potential of incremental design and information integration in crop health monitoring. Subsequently, tests were conducted on vineyard regions of interest in Teano, Italy, to assess the efficacy of the framework in the assessment of plant status and water stress. Indeed, comparing the outcomes of our maps with those of cutting-edge machine learning (ML) semantic segmentation has indeed revealed a promising level of accuracy. Specifically, classification performance was compared to the output of conventional ML methods, demonstrating that our approach is consistent and achieves an accuracy of over 90% throughout various seasons of the year. [ABSTRACT FROM AUTHOR]

The plant‐based protein industry is rapidly growing and is projected to grow to over $27 billion by 2030. In addition to monetary benefits, plant‐based protein crops, particularly pulse crops (i.e., legume species with dry edible seed), can supplement the existing crop biodiversity and break the disease and insect pest cycle in drastically changing climatic conditions. Most commercially available plant‐based protein ingredients come from only 2% of the 150 plant species on which our food supply depends. Therefore, it is imperative to diversify the cropping system with pulse crops that provide a more nutritious, climate‐resilient, sustainable food value chain. At present, a large portion of US pulse crop production is exported, yet the shifting demographics, dietary preferences, and a rise in domestic consumption present enormous potential for existing and emerging pulse crops, as well as their breeding. Despite a rise in demand from consumers and industries, farmers are yet to fully reap the benefits of these crops due to a shortage of improved varieties. These new varieties could lead to a diverse, sustainable protein supply that satisfies the growing domestic and global demand for plant‐based foods. This review intends to comprehensively explore the geographical and cultural acceptance of plant‐based proteins, manufacturing techniques, protein products, anti‐nutritional factors, techniques and tools for protein estimation, high‐throughput estimation of seed protein, protein composition requirements in food, breeding strategies, crop improvement, and resources to improve plant‐based protein pulse crops. [ABSTRACT FROM AUTHOR]

Greenhouse cultivation promotes an efficient and environmentally friendly agricultural production model, significantly enhancing resource sustainability and advancing sustainable agriculture. Traditional greenhouse pollination methods are inefficient and labor-intensive, limiting the economic benefits of greenhouse pear cultivation. To improve pollination efficiency and achieve fully automated mechanized operations, an innovative design method for greenhouse pear pollination drones has been developed. First, design criteria were extracted using Grounded Theory (GT), and the Analytic Hierarchy Process (AHP) was employed to determine the weight of user demand evaluation indicators. Next, the Quality Function Deployment (QFD) method translated user needs into technical requirements, resulting in the final ranking of design element weights. The drone was then designed based on these weighted rankings, yielding an optimal solution. This method quantifies the functional requirements of the product, effectively identifying key needs for the greenhouse pear pollination drones and proposing targeted solutions. Additionally, it provides a design reference for other highly functional agricultural machinery products. [ABSTRACT FROM AUTHOR]

In spatio-temporal plant monitoring, optical sensing (including hyperspectral imaging), is being deployed to, non-invasively, detect and diagnose plant responses to abiotic and biotic stressors. Early and accurate detection and diagnosis of stressors are key objectives. Level of radiometric repeatability of optical sensing data and ability to accurately detect and diagnose biotic stress are inversely correlated. Accordingly, it may be argued that one of the most significant frontiers and challenges regarding widespread adoption of optical sensing in plant research and crop production hinges on methods to maximize radiometric repeatability. In this study, we acquired hyperspectral optical sensing data at noon and midnight from soybean (Glycine max) and coleus wizard velvet red (Solenostemon scutellarioides) plants with/without experimentally infestation of two-spotted spider mites (Tetranychus urticae). We addressed three questions related to optimization of radiometric repeatability: (1) are reflectance-based plant responses affected by time of optical sensing? (2) if so, are plant responses to two-spotted spider mite infestations (biotic stressor) more pronounced at midnight versus at noon? (3) Is detection of biotic stress enhanced by spatial binning (smoothing) of hyperspectral imaging data? Results from this study provide insight into calculations of radiometric repeatability. Results strongly support claims that acquisition of optical sensing data to detect and characterize stress responses by plants to detect biotic stressors should be performed at night. Moreover, the combination of midnight imaging and spatial binning increased classification accuracies with 29% and 31% for soybean and coleus, respectively. Practical implications of these findings are discussed. Study results are relevant to virtually all applications of optical sensing to detect and diagnose abiotic and biotic stress responses by plants in both controlled environments and in outdoor crop production systems. [ABSTRACT FROM AUTHOR]

Vegetation health forecasting (NDVI as a proxy) informs decision‐makers about the end of season crop yield productivity but is not well‐documented. This study tests improvements in vegetation health forecasting by developing a data‐driven Dynamic Agricultural Productivity Indicator (DAPI), which simultaneously incorporates satellite‐based root zone soil moisture (RZSM) and satellite‐based NDVI data. RZSM is estimated via data assimilation of satellite based SMAP SM dataset. We employ the proposed DAPI forecast across four cropland types in the CONUS, including corn, cotton, soybeans, and wheat. Results demonstrate superior performance of the DAPI forecasts compared to climatology‐based NDVI forecasts, with the largest improvements in water‐limited regions. DAPI shows particularly good performance during hydrologic disturbances such as floods and droughts. To this end, the DAPI approach is useful in estimating future vegetation health for identifying potential food‐insecure areas, predicting crop price changes, and projecting expected commodities market trends. Plain Language Summary: Crop vegetation health can impact crop productivity. Monitoring the dynamics of vegetation health during the growing season informs decision‐makers about potential yield productivity. However, research in this area is not well‐documented—most crop forecasting models employ stochastic modeling approaches or are based on simple regression of observed NDVI climatology. This study proposes a method to forecast vegetation health by leveraging satellite‐based soil moisture, vegetation indices, and a strategic regression approach. We use the NDVI from satellite data as a proxy for vegetation health. Additionally, we utilize NASA Soil Moisture Active Passive (SMAP) satellite data to enhance a water balance model that simulates root zone soil moisture (RZSM) in deeper soil layers. We combine RZSM with NDVI values to predict NDVI during the growing season at 16 day intervals. Compared to the long‐term average NDVI, our NDVI forecasting approach shows the largest improvements in water‐limited regions and during extreme events such as floods and droughts. Key Points: SMAP‐based root zone soil moisture is a useful predictor for improving NDVI‐based crop forecastingCompared to long‐term average NDVI, the greatest forecast skill improvements are found in water‐limited environmentsSMAP‐based NDVI forecasting demonstrates significant skill in tracking NDVI dynamics during hydrologic disturbances [ABSTRACT FROM AUTHOR]

Heavy metal (HM) contaminants are the emerging driving force for reshaping the microflora of plants by eradicating the non-tolerance and non-resistant microbes via their lethal effects. Seeds served as a prime source of ancestral microbial diversity hereditary transfer from generation to generation. However, the problem arises when they got exposed to metal contamination, does metal pollutant disrupt the delicate balance of microbial communities within seeds and lead to shifts in their microflora across generations. In this study, the endophytic community within Zea mays seeds was compared across three distinct regions in Yunnan province, China: a HM-contaminated site Ayika (AK), less-contaminated site Sanduoduo (SD), and a non-contaminated Site Dali (DL). High-throughput sequencing techniques were employed to analyze the microbial communities. A total of 492,177 high-quality reads for bacterial communities and 1,001,229 optimized sequences for fungal communities were obtained. These sequences were assigned to 502 and 239 operational taxonomic units (OTUs) for bacteria and fungi, respectively. A higher diversity was recorded in AK samples than in SD and DL. Microbial community structure analysis showed higher diversity and significant fluctuation in specific taxa abundance in the metal-polluted samples exhibiting higher response of microbial flora to HM. In AK samples, bacterial genera such as Gordonia and Burkholderia-Caballeronia-Paraburkholderia were dominant, while in SD Pseudomonas and Streptomyces were dominant. Among the fungal taxa, Fusarium, Saccharomycopsis, and Lecanicillium were prevalent in HM-contaminated sites. Our finding revealed the influential effect of HM contaminants on reshaping the seed microbiome of the Zea mays, showing both the resilience of certain important microbial taxa as well the shifts in the diversity in the contaminated and pristine conditions. The knowledge will benefit to develop effective soil remediation, reclamation, and crop management techniques, and eventually assisting in the extenuation of metal pollution's adverse effects on plant health and agricultural productivity. [ABSTRACT FROM AUTHOR]

Early life environments can have long-lasting effects on adult reproductive performance, but disentangling the influence of early and adult life environments on fitness is challenging, especially for long-lived species. Using a detailed dataset spanning over two centuries, we studied how both early and adult life environments impacted reproductive performance in preindustrial women. Due to a wide geographic range, agricultural production was lower in northern compared to southern parishes, and health conditions were worse in urban than rural parishes. We tested whether reproductive traits and offspring survival varied between early and adult life environments by comparing women who moved between different environments during their lifetime with those who moved parishes but remained in the same environment. Our findings reveal that urban-born women had an earlier age at first reproduction and less offspring surviving to adulthood than rural-born women. Moreover, switching from urban to rural led to increased offspring survival, while switching from rural to urban had the opposite effect. Finally, women who switched from rural to urban and from South to North had their first child at an older age compared to those who stayed in the same environment type. Our study underscores the complex and interactive effects of early and adult life environments on reproductive traits, highlighting the need to consider both when studying environmental effects on reproductive outcomes. [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]

Machine learning (ML) algorithms can be applied to predict the suitability of soil for crop cultivation based on digital soil mapping. We used three distinct models viz. Multinomial Logistic Regression (MnLR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) to predict the suitability of wheat and pearl millet in the Barmer district of the Thar Desert. After the computation of crop suitability classes, ML techniques were used to develop suitability maps of wheat and pearl millet in the study area. The study found that the RF and XGBoost models worked well to classify crop suitability. The RF model showed that 11.9% of the total area was highly suitable, 1.6% was moderately suitable, 14.9% was marginally suitable, and 71.6% was not suitable for wheat crop. RF model for pearl millet showed that 15.5% of the area is highly suitable. Soil suitability mapping for wheat showed a Kappa index ranging from 0.23 to 0.57 and an overall accuracy ranging from 0.79 to 0.86, whereas the prediction of suitability for pearl millet showed a moderate range of Kappa index from 0.31 to 0.58 and accuracy from 0.63 to 0.77. The area under curve (AUC) for wheat crop was 0.72, 0.88, and 0.91 for MnLR, RF, and XGBoost models, respectively. Overall, the RF model performed better than the MnLR model, showing a 16% increase in accuracy. Therefore, the developed suitability maps using ML provide valuable details on agricultural potential in the Indian desert region while harmonizing its impact on the environment and the economy. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is one of the most crucial elements for crop yields. N management is incredibly important because it's a major component of crop productivity. It is challenging to control due to the large field variability of the innate soil N and the differences in crop demand at various crop growth stages. Additionally, N's partial factor production is deteriorating day by day. Furthermore, crop, cultivar, and environmental factors affect how much N is needed. Therefore, crop production depends heavily on applying N at the right rate for the crop's needs. Precision N management increases N use efficiency while reducing N loss from runoff, ammonia volatilization, and leaching. By providing N during crucial growth phases, real-time N management increases use efficiency by applying N based on need at the appropriate time and amount. One aspect of real-time N management is the application of the leaf color chart (LCC). The LCC is a relatively basic, low-cost, portable, and user-friendly gadget that contrasts the color of the leaf with the device's color hues. Because farmers typically prefer dark-colored leaves, they apply N regardless of need, which poses serious risks to the ecosystem and contaminates the surface and groundwater. The sustainability of output is threatened by the declining soil health caused by increased fertilizer application. Therefore, for small and marginal farmers, employing a leaf color chart for site-specific N management is a more practical solution. [ABSTRACT FROM AUTHOR]

In the current context of rapid climate change, water scarcity and soil poverty are becoming increasingly alarming, leading to growing losses of 30-50% of global agricultural production. It is imperative to find environmentally-friendly approaches for improving plant tolerance to drastic conditions, particularly in arid and semi-arid Mediterranean regions. Biostimulants based on symbiotic microbes are emerging as effective strategies for improving tolerance and agricultural productivity. This study aims to evaluate the effects of single and double inoculation of arbuscular mycorrhizal fungi (My) and plant growth-promoting bacteria (Ba) on the growth, physiological and biochemical traits of maize crop grown in compost (Co) amended soil under two irrigation regimes: well-watered (WW: 100% of crop evapotranspiration [ETc]) and drought-stressed (DS: 50% ETc) using drip irrigation system. Reducing irrigation to 50% reduced shoot dry weight (SDW), root dry weight (RDW), 1,000-grains weight (TGW) and grain yield (Y). However, Ba alone increased SDW by 63%, while CoMyBa improved RDW, TGW and Y by 197, 43 and 175%, respectively compared with the control under DS conditions. Dual inoculation boosted root colonization intensity, normalized difference vegetation index (NDVI), total chlorophyll and leaf area of maize seedlings in compost-amended soil, compared to the controls. The application of Ba significantly reduced hydrogen peroxide and malondialdehyde by 46%, in maize seedlings grown in compost-amended soil, compared to the controls under DS. Our results indicated that My and Ba significantly boost the ability of maize to tolerate drought by improving water supply and physiology and stimulating the accumulation of organic and inorganic osmolytes, as well as improving the properties of soils such as cation exchange capacity particularly amended by Co. The dual inoculations were the most effective and represent an environmentally-friendly and relatively inexpensive approach to optimizing agricultural production and soil restoration programs in Mediterranean regions. [ABSTRACT FROM AUTHOR]

137Cs diffused into the environment due to a nuclear power plant accident has caused serious problems for safe crop production. In plants, Cs+ is similar in its ionic form to K+. Cs+ is absorbed and transported mainly by the K+ transport mechanism. However, the full picture of the genes contributing to Cs+ transport and the transport mechanism of rice is still unclear. This study focused on OsHKT2;1, a candidate Cs+ transporter under low K+ conditions. To verify the ability of OsHKT2;1 to transport Cs+, the OsHKT2;1 mutant (hkt2;1) was grown in a 137Cs-contaminated paddy field in Fukushima. The 137Cs concentration in hkt2;1 aboveground was higher than in the wild type (WT), and the K concentration in these samples did not change between WT and hkt2;1, whereas the Na concentration was lower in hkt2;1. Uptake experiments with radioactive tracers (22Na+, 43K+, and 137Cs+) in hydroponic systems with different elemental compositions showed a negative correlation between Na+ and Cs+ accumulation in rice shoot cultivated under low K+ conditions. These results indicated that OsHKT2;1 does not directly contribute to Cs+ uptake but is an important factor in regulating Cs+ translocation by controlling Na+ accumulation. This indicates the possibility of controlling rice Cs content by regulating the Na+ environment during cultivation. [ABSTRACT FROM AUTHOR]

Bioregenerative food systems that routinely produce fresh, safe-to-eat crops onboard spacecraft can supplement the nutrition and variety of shelf-stable spaceflight food systems for use during future exploration missions (i.e., low earth orbit, Mars transit, lunar, and Martian habitats). However, current space crop production systems are not yet sustainable because they primarily utilize consumable granular media and, to date, operate like single crop cycle, space biology experiments where root modules are sanitized prior to launch and discarded after each grow-out. Moreover, real-time detection of the cleanliness of crops produced in spacecraft is not possible. A significant paradigm shift is needed in the design of future space crop production systems, as they transition from operating as single grow-out space biology experiments to becoming sustainable over multiple cropping cycles. Soilless nutrient delivery systems have been used to demonstrate post-harvest sanitization and inflight microbial monitoring technologies to enable sequential cropping cycles in spacecraft. Post-harvest cleaning and sanitization prevent the buildup of biofilms and ensure a favorable environment for seedling establishment of the next crop. Inflight microbial monitoring of food and watering systems ensures food safety in spaceflight food systems. A sanitization protocol, heat sterilization at 60°C for 1 h, and soaking for 12 h in 1% hydrogen peroxide, developed in this study, was compared against a standard hydroponic sanitization protocol during five consecutive crop cycles. Each cropping cycle included protocols for the cultivation of a crop to maturity, followed by post-harvest cleaning and inflight microbial monitoring. Microbial sampling of nutrient solution reservoirs, root modules, and plants demonstrated that the sanitization protocol could be used to grow safe-to-eat produce during multiple crop cycles. The cleanliness of the reservoir and root module surfaces measured with aerobic plate counts was verified in near real time using a qPCR-based inflight microbial monitoring protocol. Post-harvest sanitization and inflight microbial monitoring are expected to significantly transform the design of sustainable bioregenerative food and life support systems for future exploration missions beyond low earth orbit (LEO). [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilizer application ensures crop production and food security worldwide. N-controlled boosting of shoot branching that is also referred as tillering can improve planting density for increasing grain yield of cereals. Here, we report that Sugar Transporter Protein 28 (OsSTP28) as a key regulator of N-responsive tillering and yield formation in rice. N supply inhibits the expression of OsSTP28, resulting in glucose accumulation in the apoplast of tiller buds, which in turn suppresses the expression of a transcriptional inhibitor ORYZA SATIVA HOMEOBOX 15 (OSH15) via an epigenetic mechanism to activate gibberellin 2-oxidases (GA2oxs)-facilitated gibberellin catabolism in shoot base. Thereby, OsSTP28-OSH15-GA2oxs module reduces the level of bioactive gibberellin in shoot base upon increased N supply, and consequently promotes tillering and grain yield. Moreover, we identify an elite allele of OsSTP28 that can effectively promote N-responsive tillering and yield formation, thus representing a valuable breeding target of N use efficiency improvement for agricultural sustainability. A sugar transporter OsSTP28 is identified as a regulator of nitrogen-response tillering and yield formation in rice. Nitrogen supply represses the expression of OsSTP28 to fine turn the level of apoplastic glucose in shoot base, which in turn activates gibberellin catabolism. [ABSTRACT FROM AUTHOR]

Despite the widespread influence of the burgeoning digital economy on agricultural productivity in recent years, China's food system confronts numerous challenges. Notably, research exploring the digital economy's impact on food system resilience remains scarce, and the pivotal role of industrial agglomeration in this context remains unclear. Therefore, this article is based on the panel data of 30 provinces in China from 2011 to 2021, this paper empirically examines the direct effect, the mechanism of action, and the spatial spillover effect of the resilience of a digital economy-enabled food system using a double fixed-effects model, mediated-effects model, and spatial econometric model. The results show the following: (1) The resilience of China's urban food system shows obvious spatial differences, but the overall trend in improvement requires attention. (2) The development of a digital economy has a facilitating effect on the level of resilience of the food system, and industrial agglomeration induces an intermediary effect. (3) The digital economy has a significant positive spatial spillover effect on the resilience of the food system; i.e., the digital economy can improve the resilience of the food system in the region and the neighboring regions. Accordingly, policy recommendations have been put forward to improve infrastructure construction and promote the development of digital villages; strengthen the construction of industrial agglomerations and promote the enhancement of the quality and efficiency of industries; and promote the development of regional linkages and build a solid foundation for food security. [ABSTRACT FROM AUTHOR]

BACKGROUND RESULTS CONCLUSION Metal nanoparticles are widely used in agricultural production. As a new type of molybdenum fertilizer, MoO3NPs have the properties of nanomaterials and the characteristics of molybdenum nutrition. Previous studies have focused on their role in promoting crop growth. However, it is unknown whether excessive MoO3NPs will affect crop quality and nutritional value. In this study, the effects of different concentrations of MoO3NPs (0, 0.15, 0.5, 1.0, 5.0, 10, 50, 100 mg kg−1) on the growth and quality of soybean were investigated by pot experiments to analyze the plant effects caused by MoO3NPs.The results showed that the effects of MoO3NPs treatment on plant biomass and nodule number were promoted at low concentrations (0.15–5 mg kg−1) and inhibited at high concentrations (10–100 mg kg−1). According to the logistic distribution model, it was predicted that MoO3NPs would have the strongest toxic effect on soybean flowering stage. The contents of MoO3NPs which reduced the yield of soybean by 10% and 20% were 12.38 and 30.81 mg kg−1. NP0.15 could significantly improve the total amount of amino acids in grains, while NP100 reduced the total amount of amino acids in grains, both of them significantly increasing the contents of linolenic acid and linoleic acid in soybean seeds.A change of MoO3NPs concentration had no negative effect on the nutritional value of soybean grains. The research could lead to a better understanding of the potential impact of nutritional changes caused by MoO3NPs on human health. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

This study investigates the determinants and extent of crop diversification and its impact on farm households’ income and income diversification in rural Bangladesh, utilizing data from 450 households across the districts of Manikganj, Tangail, and Gaibandha. The findings reveal moderate to high levels of crop and income diversification across these sites. Using a Tobit model, the study identifies significant socio-economic factors influencing crop diversification, including literacy, farm size, and market distance. Additionally, it shows that crop diversification intensity, the household head’s age and education, and on- and off-farm income significantly affect income diversification. These factors, along with farm size, also significantly impact crop income. This research addresses a significant gap in the literature by exploring the underexamined interaction between crop diversification and income diversification in Bangladesh. It contributes to a broader understanding of how diversification strategies can enhance agricultural productivity and income stability and offers valuable policy implications. [ABSTRACT FROM AUTHOR]