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Plastic mulch is used for agricultural production to improve crop performance and mediate local environmental concerns. Paper mulch is an alternative to plastic mulch, it is effective and more biodegradable. The performance of plastic and paper mulch materials in agricultural production varies according to climatic environments, production practices, and crops. The objective of this study was to investigate the performance of paper mulch compared with plastic mulch and bare soil for tomato (Solanum lycopersicum L.) field production in 2018 and 2021. Data on weed control, soil temperature, and tomato yield were recorded. Weed coverage and weeding time were reduced in paper and plastic mulch treatments compared to bare soil. Soil temperature in 2021 was lower in paper and plastic mulch treatments than in bare soil. Tomato yield was greater in plastic mulch than paper mulch and bare soil. Tomato yield for paper mulch treatments was not different from that of bare soil treatments. Paper mulch offered comparable weed control benefits as plastic mulch, and comparable tomato yield as bare soil. [ABSTRACT FROM AUTHOR]

Producing sugar from lignocellulosic biomass is a promising resilient food solution to counter the near-total global failure of food production due to the agricultural collapse that would likely follow an abrupt sunlight reduction catastrophe such as a nuclear winter, a supervolcanic eruption, or a large asteroid or comet impact. This study examines how quickly edible sugar production could be ramped up globally by repurposing pulp and paper mills, sugarcane biorefineries, corn biorefineries, and breweries for lignocellulosic sugar production. A sub-unit component comparison to the NREL 2017 Biochemical Sugar Model indicates that 84%, 65%, 37%, and 39% of ISBL unit components are present, respectively. Fast construction methods were studied to analyze how this and other industrial foods could be rapidly leveraged in a catastrophe. Results suggest that the world’s current sugar demand could quickly be fulfilled by repurposing pulp and paper mills for lignocellulosic sugar production, given 5 months of production ramp-up and 24/7 construction. This method could reduce construction time to an estimated 32% of the original at an increased labor cost of 1.47 times, resulting in sugar production beginning 5 months after the catastrophe at a retail cost of $0.82 USD/kg. This could not only contribute a significant share of the food requirement after the catastrophe (∼28% within the first year), but also be key to preventing global starvation between the time at which global food storages run dry and other resilient food solutions can scale up significantly. This study aims to serve as the basis for more comprehensive scenario analyses. More research is needed to characterize material and labor constraints to fast response in more depth; repurposing and fast construction pilot studies and food safety studies are recommended. [ABSTRACT FROM AUTHOR]

Sustaining life on the Earth with its ever-growing population is forcing changes in people’s way of life, industrial and agricultural production, exploitation of energy resources, and approaches to ecology. We face continual growth in the world’s population, and the demand for materials is growing even more rapidly. Every manufacturing and consumer sector is looking for ways to save energy and materials, attempting to minimize their negative impacts on the environment. In the pulp and paper industry, one of the segments in which progress can be made and help protect the planet is to reduce the brightness of paper. Such a reduction would lead to a lowering in the energy and material costs associated with paper production. [ABSTRACT FROM AUTHOR]

Bamboo has being used as alternative raw material for construction, reinforcing fibers, paper production, among other applications. Although its recognized potentials as raw material, there are doubts about its environmental performance compared to traditional wood-based products, including paper production, which hinders bamboo-based paper plants in large scales. This study aims to assess the environmental performance of producing office paper from bamboo. Emergy synthesis (with 'm') and global warming potential indicators are calculated and compared with the traditional eucalyptus paper-based production. Results highlights the importance in including the renewability fractions of each input resources into emergy calculations for production systems with high human-labor intensity such as the bamboo agricultural production. Office paper produced from bamboo has similar renewability (28%), moderate environmental load (3.23 vs. 2.49), and emergy unsustainability (0.34 vs. 0.60) compared to paper produced from eucalyptus, but bamboo showed lower performance for global efficiency (568 vs. 442 sej/ton paper), emergy yield (1.09 vs. 1.49), and emergy investment (10.79 vs. 2.05). Focusing on global warming potential, office paper produced from bamboo releases 98 kgCO 2 eq. /ton paper compared to 56–267 kgCO 2 eq. /ton paper for eucalyptus. Notwithstanding, bamboo-based office paper demands four times more land area of agricultural production than eucalyptus, but it has a positive social aspect by requiring higher amount of direct human labor. This work shows the advantages of using eucalyptus rather than bamboo in producing office paper from an emergy and land demand perspectives, while global warming can still be considered inconclusive. Future efforts should consider a quantitative and qualitative analysis of human labor availability in both systems, as well an economic analysis to support discussions towards more sustainable office paper production from different raw materials. • Environmental load of bamboo and eucalyptus for office paper production are compared. • Bamboo has lower emergy performance than eucalyptus. • Including the renewability fraction of labor and services better reflects emergy results. • Bamboo paper emits 98kgCO2eq/ton, eucalyptus paper emits 56–267kgCO2eq/ton. • Bamboo paper needs 4x land compared to eucalyptus and requires more human labor. [ABSTRACT FROM AUTHOR]

The current study was conducted at the different villages of the Arajiline block of Varanasi district, Uttar Pradesh, India during November, 2022-June, 2023 to evaluate the variability of soil properties and nutrient indexof soils. The random sampling technique was used to collect 40 soil samples at different locations with the help of GPS at 0-15 cm depth. The collected soil samples were air-dried in shade at room temperature, passed through a 2 mm filter paper, and analyzed for different physico-chemical properties. The result revealed that the TS (range 8.2-81.3%), VFS (range 4.2-35.5%), Silt (range 10.1-54.2%), Clay (range 7.7-38.8%), BD (range 1.08-1.45 g cm-3), PD (range 2.04-2.33), Porosity (range 30.24-51.56%) pH (range 6.4-7.8), EC (range 0.1-0.3 dS m-1), OC (0.2-0.6%), and available N, P, K, S, Ca, and Mg varied from 130.12-260.30 kg ha-1, 14.2-23.2 kg ha-1, 145.0-240.0 kg ha-1, 7.5-17.6 kg ha-1, 3.8-8.2 cmol(P+)/kg, and 2.1-4.1 cmol(P+)/kg, respectively. The findings indicated that the studied soils were slightly acidic to moderately acidic and free from salinity hazards; 70% of the soil samples were low in organic carbon, 30% were medium in organic carbon, and 100% of the soil samples were low in available N and medium in available P, K, and S. 100% of soil samples were found to be sufficient in exchangeable Ca and Mg. The findings of this research could help in crop nutrient management, fertilizer recommendation, and decision-making for increasing agricultural production and farmer profitability. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic limits many physical activities of the society in public areas. The agricultural production sector is one of the important sectors in supporting the country’s nutrition demand. Research is a way to maintain the productivity of the agricultural sector. This study has a purpose to analyze if pandemic COVID-19 has an impact on the number of papers about agriculture recorded by Scopus. This study uses a quantitative with secondary data analysis approach in collecting data. The samples are paper on the Scopus website contains keywords “agriculture& meat”, and “agriculture&egg”. the period of samples are during 2019-2020. The data are analyzed using Vosviewer software to show the institution with the most related topic paper. The result shows that some papers are decreasing while others are increase based on the document type. For paper related to “agriculture” meat”, article as full type research paper increases along with review type paper. For a paper about “agriculture & egg”, conference type paper and review increase, while other decreases. It can be concluded that the type of paper along with the topic affects the institutions’ productivity in publishing papers. [ABSTRACT FROM AUTHOR]

A completely lab-made paper/graphene-based 3D pop-up device (3D-PP) for the analysis of carbaryl (CBR), a pesticide widely used in crop production, is proposed. The device is composed of a nitrocellulose sensor equipped with reduced graphene oxide (rGO) and a foldable 3D paper pop-up. The rationale of the device is based on 3D and 2D configurations to allow the whole analytical procedure. In the 3D arrangement sample pre-concentration and hydrolysis occur; after folding (2D), contact with the complementary nitrocellulose-based sensor is ensured. The sensor, constituted by nanostructured graphene film, allows to obtain the necessary electroanalytical performance. 3D-PP has been shaped and nanostructured using a CO 2 -laser plotter and finished using low-cost benchtop instruments, ensuring in-series manufacturing of the device modules. 3D-PP includes the main steps required for CBR determination, i.e. (i) pre-concentration/purification, (ii) hydrolysis, (iii) medium neutralization, and (iv) electrochemical detection. 3D-PP was challenged for CBR quantification in model solutions and different grain samples. The response linearity (1.5–33 μM) and LOD (0.4 μM) obtained ensures CBR determination at the European-law admitted maximum residue levels (MRL). As proof of applicability, to simulate contaminates samples, different grains (i.e. soft and durum wheat, kamut, and barley) were spiked, before extraction, with CBR at three concentration levels corresponding to 0.5x, 1x, and 1.5x MRL; in all cases, quantitative and reproducible recoveries were obtained (93–109%; RSD ≤ 6%, n = 3). 3D-PP is produced using cellulosic components and solvent-free approaches, includes all CBR analysis steps, and returns reliable results in 15 min, resulting portable and usable with a smartphone [Display omitted] • A paper/graphene-based device for integrated carbaryl (CBR) analysis is proposed. • CO 2 -laser was used to shape and nanostructure the paper-based platform. • Complete CBR analysis is strategically enclosed in a 3D foldable paper pop-up (3D-PP). • 3D-PP design and sensing ability allow CBR residues analysis at EU-law limits. • 3D-PP analysis ability was proven in soft and durum wheat, kamut, and barley. [ABSTRACT FROM AUTHOR]

Climate-change-induced unpredictable weather patterns are adversely affecting global agricultural productivity, posing a significant threat to sustainability and food security, particularly in developing regions. Wealthier nations can invest substantially in measures to mitigate climate change's impact on food production, but economically disadvantaged countries face challenges due to limited resources and heightened susceptibility to climate change. To enhance climate resilience in agriculture, technological solutions such as the Internet of Things (IoT) are being explored. This paper introduces a digital twin as a technological solution for monitoring and controlling temperatures in a greenhouse tunnel situated in Stellenbosch, South Africa. The study incorporates an aeroponics trial within the tunnel, analysing temperature variations caused by the fan and wet wall temperature regulatory systems. The research develops an analytical model and employs a support vector regression algorithm as an empirical model, successfully achieving accurate predictions. The analytical model demonstrated a root mean square error (RMSE) of 2.93 °C and an R 2 value of 0.8, while the empirical model outperformed it with an RMSE of 1.76 °C and an R 2 value of 0.9 for a one-hour-ahead simulation. Potential applications and future work using these modelling techniques are then discussed. [ABSTRACT FROM AUTHOR]

An efficient plant disease identification is prime important for Agricultural productivity. This paper proposes a method of automatic leaf extraction and classification with improved accuracy compared with existing techniques. Images acquired from natural fields are complex, with background information that needs to be accurately segmented to identify areas of interest. Grab cut is a semi-automatic approach to extract foreground objects, which might occasionally degrade an object's properties. This paper suggests a better Grab cut for automatically extracting leaves from real-field images. The enhanced dataset of 23,617 images with eleven tomato leaf classes are created using the plant village dataset and actual field images. This paper addresses a wide range of issues related to convolutional neural network optimization, including how the number of layers affects the results of leaf disease detection and the creation of tiny models for portable devices. Five models, VGG 16, MobileNet, and custom architecture with input sizes of 98 × 98, 160 × 160, and 256 × 256, have been optimized and evaluated through several trials. Training and testing involve varying the input size, the number of layers, the optimizer, the dropout, the batch normalization, and the transfer learning. This paper presents and analyzes the findings of thirty experiments on various architecture. The proposed modified sequential eleven-layer architecture achieves accuracy compared with MobileNet and a reduced model size of 3.9 MB for input size 160 and 4.5 MB for input size 98. [ABSTRACT FROM AUTHOR]

The accurate identification of crop aphids is an important aspect of improving agricultural productivity. Aphids are characterised by small targets and a body colour similar to their surroundings. Even the most advanced detectors can experience problems such as low detection accuracy and a high number of missed detections. In this paper, a multi-stream target detection model is proposed for fast and accurate detection of crop aphids in complex backgrounds. First, inspired by the human visual system, we propose a bionic attention (BA) approach. Unlike previous strategies, we do not improve the model but input additional category labels as bionic information streams into the network at the network input stage to support mainstream recognition, which improves the detection effect. In addition, through web crawling and manual screening, we construct an aphid dataset containing 2059 images, named IP_Aphids, based on IP102. In this paper, we combine the proposed BA with a number of classical target detection models, including YOLOv5s, YOLOv7-tiny, YOLOv8n, SSD, and faster R-CNN, and we also compare the BA with the classical attention mechanisms CBAM and SE. This approach allows the effectiveness of the method to be evaluated from multiple perspectives. The results show that combining the bionic information flow of BA with the original mainstream information flow as inputs to the five target detection models improves the mAP by 2.2%, 7%, 2.7%, 1.78%, and 1.12%, respectively, compared to the models using only the original inputs. In addition, the mAP of the YOLOv8n_BA model is higher than that of the YOLOv8n, YOLOv8n_CBAM, and YOLOv8n_SE models by 4.6%, 3.3%, and 2.7%, respectively. This indicates that the BA proposed in this study is significantly better than the classical attention to improve crop aphid detection, which provides a reference for crop aphid-related research. [ABSTRACT FROM AUTHOR]

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

Using the CRISPR-Cas9 system to perform base substitutions at the target site is a typical technique for genome editing with the potential for applications in gene therapy and agricultural productivity. When the CRISPR-Cas9 system uses guide RNA to direct the Cas9 endonuclease to the target site, it may misdirect it to a potential off-target site, resulting in an unintended genome editing. Although several computational methods have been proposed to predict off-target effects, there is still room for improvement in the off-target effect prediction capability. In this paper, we present an effective approach called CRISPR-M with a new encoding scheme and a novel multi-view deep learning model to predict the sgRNA off-target effects for target sites containing indels and mismatches. CRISPR-M takes advantage of convolutional neural networks and bidirectional long short-term memory recurrent neural networks to construct a three-branch network towards multi-views. Compared with existing methods, CRISPR-M demonstrates significant performance advantages running on real-world datasets. Furthermore, experimental analysis of CRISPR-M under multiple metrics reveals its capability to extract features and validates its superiority on sgRNA off-target effect predictions. Author summary: Genome editing using the CRISPR-Cas9 system, particularly base substitutions directed by guide RNA, holds immense potential for applications in gene therapy and agricultural productivity. However, the risk of unintended off-target effects poses a challenge, as misdirection of the Cas9 endonuclease can lead to unintended genome alterations. While computational methods exist for predicting off-target effects, there remains a need for encoding methods with more representation space and deep learning models with generalization capability and the adaptability. This paper introduces CRISPR-M, an innovative approach addressing the limitations of existing methods in predicting off-target effects, especially for target sites with indels and mismatches. CRISPR-M employs a novel encoding scheme and a multi-view deep learning model, combining convolutional neural networks and bidirectional long short-term memory recurrent neural networks. The three-branch network structure enhances the prediction accuracy by considering multiple perspectives. Compared with previous representative methods, CRISPR-M exhibits remarkable performance advantages when applied to real-world datasets. The experimental evaluation of CRISPR-M, assessed by various metrics such as ROC, PRC, GC content and melting temperature, demonstrates its ability to extract meaningful features and establishes its superiority in predicting off-target effects of sgRNA. [ABSTRACT FROM AUTHOR]

In India agricultural and packaging technology practices are constantly evolving to enhance crop production by improving soil quality and creating suitable environments, respectively. Mulching and improved packaging films have emerged as popular methods, but the use of non-biodegradable polyethylene (PE) for both poses disposal challenges. To address this, the focus has shifted to the biodegradable polymer, polylactic acid (PLA), in combination with fruit peel waste powder as filler. This literature review paper was written to describe a detailed survey about PLA with the incorporation of increasing amounts of fruit peel waste to enhance the properties of the PLA film. The primary aim was to explore the potential of PLA mulch film with the incorporation of fruit peel waste as an environmentally friendly alternative for mulching application in agriculture. To date we know of no review article published regarding the incorporation of fruit peel waste as a filler within the PLA matrix to enhance the properties of the films used in agriculture and the packaging industry. Moreover, this review paper also describes recent trends in the application and methods of preparation of PLA mulch films. [ABSTRACT FROM AUTHOR]

This paper aims to present an updated evolution of vegetable agricultural production in Vrancea county, during the period 2017-2021, with focus on the county's contributions in total at the country level, using the National Institute of Statistics (NIS) as principal data source. In order to meet the objectives, the methodology of research was based on indicators frequently used in papers about vegetable agricultural production, represented as values and/or percentage units. In 2021, Vrancea county detained 108 civil employment population (with 17% less than in 2017), through 22 employers in agriculture (52% less than in 2017). Among the main findings from the analyse are the following: the areas cultivated with corn grains, oat, sunflower, vegetables (all), dried onion, tomatoes, total fruits trees, plum, apples, pears, cherries and burgundy decreased among the county between 2017 and 2021 period and the areas cultivated with wheat, barley and vineyards in bearing increased. About the production, at the county level, the production of wheat, oat, barley, total fruit trees, plum, apple, pears, cherries, burgundy and grapes increased and the productions like: corn grains, sunflowers, vegetables (all), dried onion, tomatoes, decreased in the analysed period (2017-2021). From the conclusions of this paper, we found out that besides the good image in terms of wine fields, is observed that total fruit production increased by 50%, which can mean a new growth area of the county, regarding of vegetable agricultural production. [ABSTRACT FROM AUTHOR]

A review of the article "Agricultural biotechnology and crop productivity: macro-level evidences on contribution of Bt cotton in India" by S.K. Srivastava and D. Kolady, is presented.

Increasing agricultural productivity and reducing carbon emissions are two major challenges that China faces. This paper explores how agricultural insurance affects agricultural green total factor productivity (AGTFP) that addresses these two challenges. First, we adopt DDF-GML to measure AGTFP, and the Dagum's Gini decompositions results show the large differences in AGTFP, with transvariation between subregions contributing the most. Second, we find the U-shaped effect of agricultural insurance on AGTFP in a large country context. The result remains robust after adjusting for time, sample and estimation method of AGTFP. We also construct instrumental variables from the minimum distance from the centroid of counties within a province to the 45 ports in China and two-stage lagged agricultural insurance penetration (AIP) for AIP, and their squares as instrumental variables for AIP2. The conclusion remains robust in 2SLS model. Third, the findings confirm three channels for agricultural insurance to influence the AGTFP: environmentally friendly production, labor inputs and operation scale. We further propose policy advice to promote China's agricultural modernization and point out further research directions in this field. [ABSTRACT FROM AUTHOR]

The ethnohistory of the Colorado River delta has been substantively misunderstood, owing to the widespread neglect and/or misinterpretations of the writings of Francisco Garcés. In 1771, 1774, and 1775–1776, Garcés undertook three entradas into the delta, and wrote a series of valuable ethnographic accounts. Not only have Garcés's locations and routes frequently been misidentified by earlier scholars, his observations on agricultural production and population size have been ignored or marginalized, enabling misconceptions about delta historical demography and adaptation to flourish. The present paper seeks to restore Garcés's accounts, making his locations and ethnographic observation intelligible and interpretable, and to show how these can help resolve extant misconceptions. Part I focuses on some key texts, tying his locations to a master map. Part II focuses on ethnolinguistic groups and settlement sites, discusses the implications for a better understanding of historical demography and agricultural adaptation in the delta. [ABSTRACT FROM AUTHOR]

Global food security basically depends on potential yields of staple grain crops worldwide, especially under climate change. However, most scholars use various models of production function in which climatic factors are often considered to estimate crop yield mostly at local or regional level. Therefore, in this paper: Potential yields of rice, wheat, maize and soybean worldwide by 2030 are projected creatively using Auto-regressive Integrated Moving Average and Trend Regressed (ARIMA-TR) model in which actual yields in recent two years are used for testing the reliability of projection and Gray System (GS) model for validating the test; Especially individual impacts of climate change on the productions of rice, wheat, maize and soybean worldwide since 1961 are analyzed by using unary regression model in which global mean temperature and land precipitation are independent variable while the yield of crop being dependent one, respectively. Results show that: by 2030, the ratio between average and top yields of world rice is projected to be 50.6% increasing, while those of world wheat, world maize and world soybean are projected to be 38.0% increasing, 14.7% decreasing and 72.5% increasing, respectively. Since 1961 global warming has exerted a negative impact on average yield of world rice less than on its top, a positive effect on average yield of world wheat while a negative impact on its top, a positive effect on average yield of world maize less than on its top, and a positive influence on average yield of world soybean while a negative one on its top, which might be slightly mitigated by 'Carbon Peak' target. The fluctuation of global rainfall contributes to the productions of these crops much less than global warming during same period. Our findings indicate that: to improve global production of four staple grain crops by 2030, the priorities of input should be given to either rice or wheat in both high and low yield countries, whereas to maize in high yield countries and to soybean in low yield countries. These insights highlight some difference from previous studies, and provide academia with innovative comprehension and policy-decision makers with supportive information on sustainable production of these four staple grain crops for global food security under climate change in the future. [ABSTRACT FROM AUTHOR]

Farmland transfer is a critical component in facilitating agricultural scale management and improving agricultural production efficiency. This study examines the spatial distribution of farmland transfer in China and identifies the factors influencing it, offering valuable guidance for advancing China's farmland transfer practices. Through the application of mathematical statistics and GIS spatial analysis, the study investigates changes in spatial patterns related to the scale, rate, mode, and recipients of farmland transfer across China's 30 provinces from 2015 to 2020. Geographical detectors are also employed to identify the key factors influencing the extent and pace of farmland transfer. The study reveals that between 2015 and 2020, China's farmland transfer area increased from 29,789 to 37,638 million hectares. Provinces with abundant farmland resources generally experienced larger farmland transfers, while economically developed regions and major grain-producing areas saw higher rates of farmland transfers. The predominant mode of farmland transfer in China was leasing (subcontracting), accounting for over 80% of the total transferred area. Large-scale grain growers and family farms were significant participants in farmland transfers, acquiring approximately 60.1% of the transferred lands, followed by professional cooperatives (21.5%), enterprises (10.4%), and other entities (7.9%). Key factors influencing the farmland transfer area include the "regional farmland area", the "proportion of family farms supported by loans", and the "proportion of non-agricultural population", with explanatory powers of 0.663, 0.319, and 0.225, respectively. Notably, there is a substantial interaction between the "regional farmland area" and factors such as the "proportion of family farms supported by loans" and the "grain yield per unit area", with explanatory powers reaching 0.957 and 0.901, respectively. These findings offer valuable insights for promoting farmland transfer in agriculturally rich regions. Factors affecting the farmland transfer rate include "grain yield per unit area", "GDP per capita", and the "proportion of non-agricultural population", each with an explanatory power above 0.500. Moreover, their interactive explanatory powers with other indicators exceed 0.600, indicating that provinces with high agricultural productivity or economic development levels are more likely to undergo farmland transfer. The paper concludes by proposing strategies and recommendations to promote farmland transfer in both "large agricultural areas" and "metropolitan suburbs." [ABSTRACT FROM AUTHOR]

The paper is devoted to crop production adaptation to climate change. It considers the problem of finding the future optimal structure of the sowing area, considering the possible climate change scenario. It implies finding a distribution of the sowing area for different groups of crops that would maximize the average annual yield while limiting the risk of shortfall in crop production due to adverse weather conditions. The authors have developed a mathematical model to solve this problem and used it for computations. [ABSTRACT FROM AUTHOR]

China has recently become an agent of intensified agricultural production in Southeast Asia by constructing large‐scale irrigation systems. Funded with Chinese development finance, such infrastructure projects have been interpreted as a 'spatial fix' for capital accumulation in China, which helps explain the shifting balance of power within the region's political economy. However, we argue that explaining the local outcomes of these projects requires mapping out Chinese development finance in relation to the multi‐scalar network of actors, circuits of capital, and struggles over water that produce irrigated landscapes. We draw on our joint research about the Chinese‐funded and built Kanghot Irrigation Development Project in Cambodia. We explain how the construction of Kanghot was shaped by the historical and political relations between China and Cambodia. Since completion in 2016, Kanghot irrigation has transformed agricultural production by enrolling farmers into a network of volatile commodity markets and harmful pest ecologies. There have also been ongoing community struggles over Kanghot's water due to the project's design and institutional management. By broadening the idea of infrastructure as spatial fix to include these material and social processes of agrarian landscape production, this paper advances a political ecology of Chinese development finance in Southeast Asia. [ABSTRACT FROM AUTHOR]

Human-wildlife interactions can affect human wellbeing and wildlife population persistence. This paper addresses the perceived impacts of wildlife on agropastoral food production in the Tarangire ecosystem of northern Tanzania. It is based on sixteen months of collaborative ethnographic fieldwork with agropastoral Maasai communities (2019–2020; 2022; 2023), 240 semi-structured interviews, and a household survey (n = 1076). People felt that caterpillars, elephants, and zebras had the most significant effects on crop production, while hyenas were responsible for the bulk of livestock depredation by carnivores. These social costs of wildlife merit further attention from conservation policy makers. [ABSTRACT FROM AUTHOR]

Agricultural production has both increased and become more efficient with the development of technology. However, greenhouse gases such as CO2 released into the air during production cause climate change. This situation also affects agricultural productivity. Therefore, the main objective of this paper is the examine the interaction between agricultural sector activity and CO2 emissions in Türkiye in a non-linear framework. For this purpose, the Maki cointegration test and the Single Fourier frequency Toda & Yamamoto causality test were used to investigate the interplay between agricultural value added and CO2 using time series data covering the period from 1968 to 2018. In addition to the empirical analysis developed in the paper, our study adds to the literature by studying the relationship between CO2 and energy consumption in the agricultural sector, as opposed to studies that use aggregate CO2 emissions as an indicator of climate change. In addition, the short- and long-run interactions between CO2 and agricultural productivity were investigated by estimating two separate equations where agricultural productivity and CO2 emissions are used as dependent variables. The Maki cointegration test cointegration test shows the existence of a long-run relationship between agricultural value added and CO2 emissions under structural breaks. The detected significant breaks are associated with significant events affecting the Türkiye economy. For instance, when agricultural value added is the dependent variable, the break dates of 1971 and 1974 coincide with the oil crisis, while the breaking dates of 2002 and 2008 coincide with Türkiye's 2001 financial crisis and the 2008 global financial crisis. Similarly, the break dates of 1973 and 1977 obtained in the CO2 equation are associated with the 1970s' global oil crisis. Long-run parameter estimates derived from FMOLS and CCR estimators indicated that CO2 emissions have a long-run, positive and significant impact on agricultural productivity. In addition, the long-run results support the existence of a positive and significant impact of agricultural productivity on environmental degradation. The gradual shift causality test also supports the presence of one-way causality, running from agriculture output to CO2. [ABSTRACT FROM AUTHOR]

Food security, a vital determinant of overall health and well-being, hinges on the simultaneous achievement of four dimensions: physical availability of food, economic and physical access to food, utilization of nutrients, and stability over time. This paper explores the complex and multi-faceted food security situations in Kenya and Zambia, emphasizing key factors such as agricultural production, government policies, and socio-economic conditions. [ABSTRACT FROM AUTHOR]

The purpose of the paper was to assess the impact of climate changes on agricultural development and food security in Ukraine and Slovakia using statistical data from Statistical Office of the Slovak Republic, State Statistics Service of Ukraine, Eurostat, Food and Agriculture Organization and other sources. The comparison method was used to evaluate changes in agricultural development indicators, as well as climate changes in 1998-2021 in Ukraine and Slovakia. The main indicators of agricultural development used in the research were agricultural raw materials exports(%), agricultural raw materials imports (%), agriculture value added (% of GDP), agriculture value added (annual % growth), agriculture value added (current US$), cereal production (metric tons), cereal yield (kg per hectare), crop production index, food production index. Correlation and regression equations were used to establish the relationship between climatic factors and agricultural development indicators. The multiple correlations between air temperature and indicators of agricultural development was r=0.75 for Ukraine, r=0.69 for Slovakia. Using neuromodeling tools, the indicators of cereal production volumes and cereals yields in Ukraine and Slovakia in 2024-2033 were predicted. Tables were used to summarize the results. In conclusion, it should be noted that climatic conditions should be analyzed in each sector of crop production, and measures should be taken to adapt technologies for the gradual expansion of obligations for the production and export of agricultural products to world markets. [ABSTRACT FROM AUTHOR]

The non-judicious use of water at the farm level in traditional irrigation application methods is a present-day concern across the world that can be resolved by enhancing application efficiency through the adoption of advanced irrigation techniques. Sprinkler irrigation is a method that has high application efficiency, which can be further increased when coupled with automation toward precision irrigation. The objectives of this review are to summarize the main aspects of sprinkler and precision irrigation and their development, scope, and future prospects specifically in Asian countries. In this paper, a modified methodology, inspired by PRISMA guidelines, was used to explore the available literature to summarize the existing knowledge in the field. Regarding the technological aspects of the analyzed works, it became evident that sprinkler systems are an efficient method to not only irrigate crops (with 39% water saving) but also for the application of fertilizers with higher efficiency (>35%) and water productivity (>14.1%) compared with gravity irrigation systems. Moreover, this paper highlights the prominent features of precision irrigation for maximizing agricultural productivity. The use of sprinkler irrigation with precision applications using automation with a sensor-based mechanism for field data collection, data transformation, data analysis, and operation of IoT-based automatic solenoid valves can save 20–30% more irrigation water and increase crop yield by 20–27%. An analytical understanding and knowledge of the field were used to draw conclusions that are thought-provoking for scientists, researchers, and other stakeholders. [ABSTRACT FROM AUTHOR]

The present paper deals with the kinetic-theoretic description of the evolution of systems consisting of many particles interacting not only with each other but also with the external world, so that the equation governing their evolution contains an additional term representing such interaction, called the 'forcing term'. Firstly, the interactions between pairs of particles are both conservative and nonconservative; the latter represents, among others, birth/death rates. The 'forcing term' does not express a 'classical' force exerted by the external world on the particles, but a more general influence on the effects of mutual interactions of particles, for instance, climate changes, that increase or decrease the different agricultural productions at different times, thus altering the economic relationships between different subsystems, that in turn can be also perturbed by stock market fluctuations, sudden wars, periodic epidemics, and so on. Thus, the interest towards these problems moves the mathematical analysis of the effects of different kinds of forcing terms on solutions to equations governing the collective (that is statistical) behaviour of such nonconservative many-particle systems. In the present paper, we offer a study of the basic mathematical properties of such solutions, along with some numerical simulations to show the effects of forcing terms for a classical prey–predator model in ecology. [ABSTRACT FROM AUTHOR]

This paper summarizes key findings from the recent literature on agricultural productivity and structural transformation and then identifies priority areas for further research. The paper discusses the macro relevance of agricultural productivity for growth and structural transformation. New theory and data have underscored the importance of agricultural productivity as a proximate cause of low aggregate productivity in the world's poorest countries, including many in sub-Saharan Africa. Evidence has also emerged on the importance of agricultural productivity growth as a driver of development and growth in the past. But micro evidence and changes in the global context suggest that today's low-income countries may face a different set of challenges in the years ahead. [ABSTRACT FROM AUTHOR]

The article discusses the importance of crop tolerance to both abiotic and biotic stresses in agricultural research. Abiotic stresses include environmental factors like drought and extreme temperatures, while biotic stresses involve pests, diseases, and pathogens. Understanding and enhancing crop tolerance to these stresses is crucial for global food security and sustainable crop production. The article highlights various research papers from different countries that focus on topics such as abiotic stress (salinity, drought) and biotic stress (pests, diseases). The research papers explore different strategies, including breeding and genetic engineering, to enhance crop tolerance. [Extracted from the article]

The maturity of fruits and vegetables such as tomatoes significantly impacts indicators of their quality, such as taste, nutritional value, and shelf life, making maturity determination vital in agricultural production and the food processing industry. Tomatoes mature from the inside out, leading to an uneven ripening process inside and outside, and these situations make it very challenging to judge their maturity with the help of a single modality. In this paper, we propose a deep learning-assisted multimodal data fusion technique combining color imaging, spectroscopy, and haptic sensing for the maturity assessment of tomatoes. The method uses feature fusion to integrate feature information from images, near-infrared spectra, and haptic modalities into a unified feature set and then classifies the maturity of tomatoes through deep learning. Each modality independently extracts features, capturing the tomatoes' exterior color from color images, internal and surface spectral features linked to chemical compositions in the visible and near-infrared spectra (350 nm to 1100 nm), and physical firmness using haptic sensing. By combining preprocessed and extracted features from multiple modalities, data fusion creates a comprehensive representation of information from all three modalities using an eigenvector in an eigenspace suitable for tomato maturity assessment. Then, a fully connected neural network is constructed to process these fused data. This neural network model achieves 99.4% accuracy in tomato maturity classification, surpassing single-modal methods (color imaging: 94.2%; spectroscopy: 87.8%; haptics: 87.2%). For internal and external maturity unevenness, the classification accuracy reaches 94.4%, demonstrating effective results. A comparative analysis of performance between multimodal fusion and single-modal methods validates the stability and applicability of the multimodal fusion technique. These findings demonstrate the key benefits of multimodal fusion in terms of improving the accuracy of tomato ripening classification and provide a strong theoretical and practical basis for applying multimodal fusion technology to classify the quality and maturity of other fruits and vegetables. Utilizing deep learning (a fully connected neural network) for processing multimodal data provides a new and efficient non-destructive approach for the massive classification of agricultural and food products. [ABSTRACT FROM AUTHOR]

Continuous cropping has become a common form of agricultural production at present, but with the increase of continuous cropping years, continuous cropping obstacles such as soil-borne diseases and plant growth potential decline are becoming more and more common. At present, the causes of continuous cropping obstacles and continuous cropping restoration have become a hot issue in agricultural research. This paper summarized the effects of continuous cropping obstacles on soil microbial community structure and main technical methods to repair continuous cropping obstacles, such as agricultural measure management, microbial balance adjustment and soil improvement, aiming to provide theoretical reference for protecting the sustainable utilization of soil ecosystem and ensuring the stability of crop production [ABSTRACT FROM AUTHOR]

Agriculture plays a vital role in driving economic output and employment in SubSaharan African (SSA) countries. Despite some progress, agricultural productivity in SSA still lags behind other regions. Limited access to finance remains a significant impediment to improving agricultural productivity in Sub-Saharan Africa. This paper investigates the effect of financial proximity on agricultural productivity in Sub-Saharan African countries. The study primarily employs the system GMM estimator, chosen to address the endogeneity issue typical in macro panel data. This method is also wellsuited to our study because it accommodates a high number of cross-sections relative to the number of periods within each cross-section. Additionally, the IV-2SLS method is employed to check the robustness of the findings. The study uses an unbalanced panel for the 36 African countries with data for the period 2004-2019. Our findings show that increasing the financial proximity favors agricultural productivity in SSA countries. Specifically, the number of commercial bank branches (CBB) and the number of automated teller machines (ATM) per 100 000 adults, as indicators of financial proximity, have positive and significant effects on agricultural value added per worker in SSA. Additionally, our findings show that rainfall, arable land, and institutional quality are robust determinants of agricultural productivity. The positive effects of the number of CBB and the number of ATM are even more pronounced on agricultural productivity when coupled with strong institutional quality. Our findings suggest that improving financial services' accessibility in rural areas, coupled with enhanced institutional quality, regular rainfall, ample arable land, and increased access to water and land, are pivotal steps for achieving sustainable enhancements in labor productivity. This, in turn, leads to increased returns through value-added growth and expanded employment in the agricultural sector. [ABSTRACT FROM AUTHOR]

The use of biostimulants in plant production is an agricultural practice friendly to environment and one of the tools employed in the sustainable agriculture. The present paper was to determine the influence that the application of products based in oligosaccharines exerted on plant growth and development of garlic (Allium ampeloprasum L.) cv. 'Fredy'. The present work was performed, under field conditions, during the period October 2020 - February 2021 with the objective of determining the influence of the application of products based in oligosaccharines on the growth and development of elephant garlic plants (Allium ampeloprasum L.) cv. 'Fredy'. The effect of determined doses of QuitoMax® and PectiMorf® products, in different ways of application ("seed" imbibition, foliar spray at 80 DAP and the combination of both with the particularity was evaluated of also, combining the products) on the behavior of emergence percentage at 7 and 14 DAP. Besides, plant height (cm) and leaf number at 70, 90 and 110 DAP; as well as, the bulb characteristics and the survival percentage at harvest time was evaluated too. In addition, plant yield was estimated. Results shown that, in general, the application of QuitoMax® was more efficient than that of PectiMorf® in stimulating all the indicators evaluated, although the best results were obtained when both products were used in combination, that is, the "seed" imbibition with QuitoMax® and the foliar spray of the plants with PectiMorf® or viceversa. [ABSTRACT FROM AUTHOR]

Due to the changes in the agricultural sector, there is a demand among policymakers, administration, advisors and farmers for comparisons of the economic efficiency of organic versus conventional farms and their environmental impact. The authors of the paper hypothesised that in some conditions, organic farms can reach similar productive and economic results as conventional farms and, at the same time, achieve better environmental effects. The aim of the research was to compare the production, environmental and economic effects of selected organic and conventional farms from eastern Poland (mixed, crop production, animal production). The basis for the comparative analysis was the data from 12 farms obtained using the questionnaire method (direct interview) from the years 2020 to 2021. The yields of cereals in the tested organic farms were about one-third lower than the average obtained on conventional farms. Total organic crop production in cereal units per ha was 43% of conventional production. Balances of NPK indicated surpluses or deficiency, which suggested that in both systems nutrient management should be improved and optimised. The compared groups of organic farms generally had higher economic efficiency—both with and without subsidies—than conventional farms, despite the fact that the latter obtained significantly higher incomes. Gross farm income on conventional farms was higher than on organic farms by 28%, but conventional farms had higher direct costs by 332% than organic ones. As a result, the economic efficiency of agricultural production of organic farms was higher by 59% than conventional farms. The lower level of inputs incurred on organic farms was the main factor determining their high economic efficiency. Organic farms pursuing an intensive model of agricultural production (milk production), but also with specialisation in crop production, proved to be the most economically efficient. Despite diversified production, reducing the income risk, the mixed production, both organic and conventional, in the studied set of farms turned out to be the least profitable, indicating the need to support it. It is suggested that moderate specialisation increases the efficiency of management in organic farming. [ABSTRACT FROM AUTHOR]

Abiotic stresses occur more often in combination than alone under regular field conditions limiting in more severe way crop production. Stress recognition in plants primarily occurs in the plasma membrane, modification of which is necessary to maintain homeostasis in response to it. It is known that lipid transport proteins (ns-LTPs) participate in modification of the lipidome of cell membranes. Representative of this group, ns-LTP2.8, may be involved in the reaction to abiotic stress of germinating barley plants by mediating the intracellular transport of hydrophobic particles, such as lipids, helping to maintain homeostasis. The ns-LTP2.8 protein was selected for analysis due to its ability to transport not only linear hydrophobic molecules but also compounds with a more complex spatial structure. Moreover, ns-LTP2.8 has been qualified as a member of pathogenesis-related proteins, which makes it particularly important in relation to its high allergenic potential. This paper demonstrates for the first time the influence of various abiotic stresses acting separately as well as in their combinations on the change in the ns-LTP2.8 transcript, ns-LTP2.8 protein and total soluble protein content in the embryonal axes of germinating spring barley genotypes with different ns-LTP2.8 allelic forms and stress tolerance. Tissue localization of ns-LTP2.8 transcript as well as ns-LTP2.8 protein were also examined. Although the impact of abiotic stresses on the regulation of gene transcription and translation processes remains not fully recognized, in this work we managed to demonstrate different impact on applied stresses on the fundamental cellular processes in very little studied tissue of the embryonal axis of barley. [ABSTRACT FROM AUTHOR]

Aflatoxins, including aflatoxin B1, B2, G1, G2, M1, and M2, are one of the major types of mycotoxins that endangers food safety, human health, and contribute to the immeasurable loss of food and agricultural production in the world yearly. In addition, aflatoxin B1 (AFB1) mainly produced by Aspergilus sp. is the most potent of these compounds and has been well documented to cause the development of hepatocellular carcinoma in humans and animals. This paper reviewed the detoxification and degradation of AFB1, including analysis and summary of the major technologies in physics, chemistry, and biology in recent years. The chemical structure and toxicity of the transformed products, and the degradation mechanisms of AFB1 are overviewed and discussed in this presented review. In addition to the traditional techniques, we also provide a prospective study on the use of emerging detoxification methods such as natural products and photocatalysis. The purpose of this work is to provide reference for AFB1 control and detoxification, and to promote the development of follow-up research. [ABSTRACT FROM AUTHOR]

Based on the data of 2015 China Household Finance Survey (CHFS), this paper applies the intermediary effect model to identify the intermediate transmission mechanism in which farmland transfers affect agricultural production efficiency. The results show that the output value of households that have transferred farmland is increased by about 27% more than those that have not. In addition, the transfer of farmland has a more significant impact on the agricultural production efficiency of young and middle --aged families. The transfer of farmland from grain production areas has an increased tendency to household output value. The mechanism analysis shows that the transfer of farmland affects agricultural production efficiency in the following two ways. On the one hand, the transfer of farmland can help realize the effective replacement of labor by machinery, increase the mechanization degree of agricultural production, and realize the scale effect of farmland. On the other hand, based on the maximization of their own interests, farmers prefer to plant cash crops and improve agricultural production efficiency through the selection effect. By comparing the above two effects, we found that the planting selection behavior of compacting grain and expanding economic growth is more prominent. Therefore, this article proposes to promote the development of the farmland transfer market and make use of scale advantage. Meanwhile, the self-selection behavior of transferred farmers in planting crops should be valued and young people with advanced concepts to engage in agricultural production activities should be introduced, which inject "fresh blood" into agricultural modernization. However, we should also keep the red line of farmland and alert the phenomenon of "non-agricultural" and "non-grain" in the transfer of farmland. [ABSTRACT FROM AUTHOR]

Tomato is a most economic vegetable in India. Covers major area in its cultivation during crop production, it is threatened by major viral disease i.e tomato leaf curl disease, caused by begomovirus and transmitted by the vector. It causes yield loss up to 90-100 per cent, application of insecticide for the control of vector causes regular outbreak. Identification of resistant source from wild species and their introgression with susceptible source, development of lines/varieties, resistant/tolerant to Tomato leaf curl disease is the safest and long term alternative for solving this problem. This paper covers the major aspect related to virus, virus causing factors, vectors and sources of disease resistance and also breeding tools employed for its resistance and some of the barriers in breeding programme. [ABSTRACT FROM AUTHOR]

Cuba is struggling with a growing environmental problem: the uncontrolled spread of the allochthonous weed species marabou (Dichrostachys cinerea) throughout the country. Over the last 70 years, marabou has become a formidable invasive species that poses a threat to Cuban biodiversity and agricultural productivity. In this paper, we present a free and affordable method for regularly mapping the spatial distribution of the marabou based on the Google Earth Engine platform and ecological surveys. To test its accuracy, we develop an 18-year remote sensing analysis (2000–2018) of marabou dynamics using the Valle de los Ingenios, a Cuban UNESCO World Heritage Site, as an experimental model. Our spatial analysis reveals clear patterns of marabou distribution and highlights areas of concentrated growth. Temporal trends illustrate the aggressive nature of the species, identifying periods of expansion and decline. In addition, our system is able to detect specific, large-scale human interventions against the marabou plague in the area. The results highlight the urgent need for remedial strategies to maintain the fragile ecological balance in the region. [ABSTRACT FROM AUTHOR]

Pollinators are critical for agricultural production and food security, leading to many ongoing surveys of pollinators (especially bees) in crop and adjacent landscapes. These surveys have become increasingly important to better understand the community of potential pollinators, quantify relative insect abundance, and secure crop ecosystem services. However, as some bee populations are declining, there is a need to align and improve bee survey efforts, so that they can best meet research and conservation goals, particularly in light of the logistical and financial constraints of conducting such studies. Here, we mined the existing literature on bee surveys in or around agricultural lands to better understand how sampling methods can be optimized to maximize estimates of 2 key measures of bee communities (abundance and richness). After reviewing 72 papers spanning 20 yr of publication, we found that study duration, number of sites, sampling time, and sampling method most significantly influenced abundance, while the number of trips per year and collection method significantly influenced richness. Our analysis helps to derive thresholds, priorities, and recommendations that can be applied to future studies describing bee communities in agroecosystems. [ABSTRACT FROM AUTHOR]

This paper discusses the interrelations between migration, agricultural production, class, and cultural belonging, focusing on the economic and demographic transformation of Gemlik, an Ottoman district that underwent substantial change over the course of the nineteenth century. Based on the mid-nineteenth-century population and tax registers of the town of Gemlik and of two villages in the district, Kurşunlu and Kumla-i Sagir, we demonstrate that the agricultural economy in the district was heavily shaped by commodity production in the context of the district's increasing integration into global markets. By tracing specific patterns of mobility and settlement over time, we show that the process of global integration was entangled with class and cultural differentiation in the region. [ABSTRACT FROM AUTHOR]

The availability of coherent time series of crop statistics is essential for better analyzing the past, understanding the present, and predicting future trends in yield, area, and production. Importantly, such data also underpin assessments and subsequent policy actions that can shape future food systems that are more resilient in the face of climate change and that are sustainable in terms of resource use efficiency. In the European Union (EU), there currently is no legal obligation for EU countries to provide subnational crop statistics. However, such data could improve in-season crop forecasts, climate change impacts and adaption need assessments, and evaluation of agri-environmental schemes. The dataset described in this paper includes a harmonized collection of subnational crop statistics on area, production, and yield, collected for the EU from National Statistical Institutes (NSIs) and the EUROSTAT REGIO database – subnational crop statistics voluntarily contributed by EU countries. The crops considered are wheat (including soft and durum wheat), barley (including winter and spring barley), grain maize, sunflower, and sugar beet. All data are harmonized towards the hierarchical structure of the EUROSTAT legend and the regional classification of NUTS (Nomenclature of Territorial Units for Statistics) version 2016, to provide coherent time series. A total of 344 282 records is presented here (115 974 for wheat, 122 705 for barley, 35 274 for grain maize, 34 916 for sugar beet, and 35 413 for sunflower) for a total of 961 regions in 27 EU countries. Statistics are reported from 1975 to 2020, with a median time-span range of 21 years. A flagging system details, for each data record, information on data sources, processing steps, and quality-checking results. This includes consistency checks between reported values for area, yield and production, identification of null values, missing and calculated data, information on crop legend matching, and NUTS versioning. We illustrate the value of this dataset by analyzing impacts on crops and production zone shifts in Europe due to climatic and economic factors. Recommendations and future developments of collecting subnational statistics at the EU level are briefly discussed. The dataset is accessible with European Commission Authentication Service (ECAS) login at 10.2905/685949ff-56de-4646-a8df-844b5bb5f835. [ABSTRACT FROM AUTHOR]

The ethnohistory of the Colorado River delta has been substantively misunderstood, owing to the widespread neglect and/or misinterpretations of the writings of Francisco Garcés. In 1771, 1774, and 1775–76, Garcés undertook three entradas into the delta, and wrote a series of valuable ethnographic accounts. Not only have Garcés's locations and routes frequently been misidentified by earlier scholars, his observations on agricultural production and population size have been ignored or marginalized, enabling misconceptions about delta historical demography and adaptation to flourish. The present paper seeks to restore Garcés's accounts, making his locations and ethnographic observations intelligible and interpretable, and to show how these can help resolve extant misconceptions. Part I focuses on some key texts, tying his locations to a master map. Part II focuses on ethnolinguistic groups and settlement sites, and discusses the implications for a better understanding of historical demography and agricultural adaptation in the delta. [ABSTRACT FROM AUTHOR]

This paper analyzes changes in agricultural productivity gender gaps in Côte d'Ivoire between 2008 and 2016 using decomposition methods. The analysis finds that the gender gap went from 40% in food crops and 17% in exports crops in 2008, to 19% in food crops and a statistical zero in export crops in 2016. The overall gender gap decreased by 15 percentage points over this period, and is statistically insignificant in 2016 once accounting for whether households farm export crops. Moreover, our results show that while some drivers of the gender gap remain stable across the decade (including total land cultivated, and pesticide and fertilizer use), others change their contribution (number of plots, crop choice and household labor). Despite substantial improvements, female‐headed households in the bottom half of the distribution remain disadvantaged. Our results indicate that strengthening women's access to agricultural labor and adoption of export crops are policy priorities to reach gender parity. [ABSTRACT FROM AUTHOR]