Efficiency Of Agricultural Production Research Articles

The influence of online information on consumers’ channel migration behavior of fresh agricultural products

IntroductionCompliance with the latest patterns in online consumption of fresh agricultural products should prioritize the shifts in consumer behavior. This study aimed to clarify the influencing factors of consumers’ channel migration behavior of fresh agricultural products. While the migration of consumers’ consumption of fresh agricultural products to online channels is an undeniable fact, and this trend continues, literature on this topic remains limited.MethodsBased on SOR theory, and from the dual perspectives of information transmission and information reception, this study exploratively introduced the network affinity of consumers, and constructed the concept model of the influencing factors of consumers’ channel migration behavior of fresh agricultural products including information acquisition and risk perception. 416 valid questionnaires were used to conduct structural equation model analysis.ResultsThe results confirm that product information and platform information significantly affect consumers’ channel migration behavior of fresh agricultural products. Product information including feature information and price information has a positive influence on consumers’ channel migration behavior of fresh agricultural products. The same is true for such behavior and the platform information including service information and logistics information. Risk perception plays a partial mediating role in the influence of product information variables and platform information variables on consumers’ online purchasing and migration behavior of fresh agricultural products. Network affinity negatively moderates the causal relationship between product information and risk perception as well as that between platform information and risk perception. The effect is more pronounced for consumers with high network affinity than those with low network affinity.DiscussionThe study presented in this paper offers a replicable theoretical framework for future discussions on consumer channel migration behavior, and enriches the literature on consumer online consumption behavior. It is highly meaningful for further improving the online consumption stickiness, tapping the potential of online consumption and improving the circulation efficiency of fresh agricultural products in the post-pandemic era.

Precision Regulation and Forecasting of Greenhouse Tomato Growth Conditions Using an Improved GA-BP Model

Tomatoes are annual herbaceous plants of the family Solanaceae. They have very stringent requirements for their growing environment and climate conditions. To precisely control the greenhouse environment for tomato growth, this project designed and implemented a monitoring system utilizing programmable logic controllers and a data acquisition system for monitoring. Sensors are installed at key locations in the greenhouse, such as near the ground, in the plant canopy, and under the roof, to monitor environmental parameters such as temperature, humidity, light intensity, and carbon dioxide concentration in real time. A three-layer feedforward GA-BP neural network model was established using soil temperature, soil humidity, air humidity, and illumination as predictive parameters. This technology predicts optimal environmental parameters and performs real-time monitoring and intelligent control, overcoming the traditional BP neural network’s drawbacks of slow convergence, susceptibility to disturbance, and poor generalization ability, with the current model’s average prediction error being less than 5%. It provides a theoretical basis and decision support for precision control and related environmental forecasting in agricultural projects. Based on the growth characteristics, physiological and morphological features of tomatoes, and the comprehensive impact of planting conditions, the technology enhances tomato yield and quality while reducing production costs and labor inputs. It mainly includes the establishment of tomato growth models, measurement and control of environmental parameters, and the design and optimization of intelligent decision control systems. Research outcomes in this field are significant for improving agricultural production efficiency, ensuring food security, and promoting sustainable agricultural development.

Improvement of the organizational structure of management agricultural enterprises according to the principles of the market economy

The materials of the scientific publication define the role of marketing principles in the organization of the management structure of agricultural enterprises in the production process. The works of domestic and foreign scientists devoted to the efficiency of agricultural production, the service sector and the market were analyzed. When conducting research on the state of the organizational structure of management of agricultural enterprises based on the principle of marketing, general scientific research methods were used, in particular: a monographic method to identify the problem of adaptation of agricultural enterprises to the market environment, a method of comparative analysis to study the possibilities of adaptation to the market of agricultural enterprises of different sizes, an abstract-logical method with its methods of generalization analysis and synthesis and the method of induction and deduction for the formation of generalizations, conclusions and propositions. A system of the organizational structure of management of agricultural enterprises was established in accordance with marketing principles. The state and further development of the management structure of agricultural enterprises is determined. Presented are topical issues of forming the implementation of agrarian policy in the field of organizational structure of socio-economic and social-labor relations. The optimal system of labor organization in social and labor relations based on the principle of humanization of labor, which offers wide independence to the production enterprise, has been revealed. The conditions that determine the direction of all production and marketing activities of agricultural enterprises, which are based on the principles of marketing are analyzed. All activities of the agricultural enterprise are subject to this concept. The tactics of the marketing concept of an agricultural enterprise, based on the use of defensive and offensive positions, are also proposed. Appropriate conclusions were made that reflect the assessment of the financial condition of agricultural sector enterprises and offer the most effective method of marketing policy activation, which provides an opportunity to obtain more information about the activities of agricultural enterprises, conduct its analysis, and formulate specific proposals for production.

The synergy effect of agricultural dual-scale management on farmers' income: evidence from rural China

PurposeThis study aims to estimate the synergy effect of agricultural dual-scale management (ADM) on farmers' total household income, its heterogeneous effects and its mechanisms.Design/methodology/approachThis study constructs a theoretical analysis framework based on the division of labor and synergy theory, empirically assesses the impact of ADM on farmers' income, and further discusses the heterogeneity and mechanisms using the propensity score matching (PSM) and quantile treatment effect (QTE) models. Data is collected from 1,076 households across 4 cities in Liaoning Province of China in 2021.FindingsADM can improve the total household income of farmers, and the impact force is greater than that of the single-scale management mode. ADM is more conducive to improving the income of farmers with low income and low labor endowment. Moreover, ADM can improve agriculture production efficiency, increase net grain production income. Nevertheless, it has no significant effect on farmers' off-farm employment income.Originality/valuePrevious studies have mainly focused on the income effect of land scale management or service scale management. To the best of our knowledge, this study is the first to identify the synergy effect of ADM on farmers' income in China. It provides new insights into the process of agricultural production and management mode transitions in rural China.

Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images

Abstract With the modernization of agricultural production and the acceleration of urbanization, agricultural landscape planning and ecological balance control have become important issues in promoting sustainable development. Traditional agricultural production methods have problems such as resource waste, environmental pollution, and ecological damage. This article aimed to achieve scientific planning and management of agricultural landscapes, and promote the efficiency of agricultural production, rational utilization of resources, and protection of the ecological environment, thereby promoting sustainable agricultural development. This study first focused on denoising and feature extraction of agricultural remote sensing data images, using remote sensing technology to obtain agricultural landscape information. After that, artificial intelligence was adopted to achieve intelligent agricultural landscape planning, with the goal of maintaining ecological balance and promoting efficient, eco-friendly, and sustainable agricultural production. This study took the landscape of a certain city as an example to test the processing effect of remote sensing images, and it was proved that the effect was good. We tested the performance of an intelligent agricultural landscape planning and ecological balance control system based on remote sensing images. According to the experimental results, it can be concluded that the resource utilization efficiency of farmland A monitored by the intelligent agricultural landscape planning system using remote sensing image technology was 82%, while the traditional one was only 60%. This indicated that the collection effect of remote sensing image technology was much better than that of traditional technology. This article comprehensively and timely monitored and evaluated farmland through remote sensing image technology, including crop growth status, soil moisture, nutritional status, etc. The system can provide precise planting and management suggestions for farmers based on this information, and help them optimize farmland layout, crop selection, and irrigation management, thereby improving the production efficiency of farmland and crop yield.

Investigating Precise Decision-Making in Greenhouse Environments Based on Intelligent Optimization Algorithms

The precise control of a greenhouse environment is vital in production. Currently, environmental control in traditional greenhouse production relies on experience, making it challenging to accurately control it, leading to environmental stress, resource waste, and pollution. Hence, this paper proposes a decision-making greenhouse environment control strategy that employs an existing monitoring system and intelligent algorithms to enhance greenhouse productivity and reduce costs. Specifically, a model library is created based on machine learning algorithms, and an intelligent optimization algorithm is designed based on the Non-Dominated Sorting Genetic Algorithm III (NSGA-3) and an expert experience knowledge base. Then, optimal environmental decision-making solutions under different greenhouse environments are obtained by adjusting the greenhouse environmental parameters. Our method’s effectiveness is verified through a simulated fertilization plan that was simulated for a real greenhouse tomato environment. The proposed optimization solution can reduce labor and time costs, enable accurate decision-making in the greenhouse environment, and enhance agricultural production efficiency.

The Enabling Effect of Digital Economy on High-Quality Agricultural Development-Evidence from China

The Enabling Effect of Digital Economy on High-Quality Agricultural Development-Evidence from China

DIGITAL INITIATIVES OF HARYANA GOVERNMENT AND FARMER'S WELFARE

The agricultural landscape in Haryana, India, has undergone a transformative shift with the advent of digital technologies, specifically E-Portals encompassing social media and mobile applications. Digitalization presents the opportunity to assist in tackling the agricultural sector's challenges and improve productivity and sustainability. Digital initiatives (E-commerce and E-Portals) in agriculture have a significant positive impact on agricultural production efficiency. It encourages rational allocation of agricultural factors and promotes sustainable development.Based on Available data from national surveys and existing literature on the implementation and effects of digital portals, Mobile applications, and social media in agriculture utilization of digital technologies. The study adopted a mixed-methods approach, data taken from different sources like combining surveys, national surveys, existing literature, and data analytics to evaluate the adoption and utilization patterns of E-Portals, mobile applications and social media among farmers. The study aims to analyze the impact of E-Portals on farmers lives in Haryana. The research paper will focus on the E-Portals, Mobile apps and social media initiatives run by Government of Haryana. This research paper explores the multi-sided impact of these technological involvements on farmers in the region. Through a comprehensive study, we investigate how E-Portals have influenced various facets of farming practices, socio-economic conditions, and overall welfares of farmers in Haryana.Findings of this study reveal the extent to which farmers have integrated digital platforms into their daily routines for tasks such as market information access, crop management, financial transactions, and community engagement. Furthermore, the research explores the implications of E-Portals on improving market linkages, enhancing agricultural productivity, and contributing to sustainable farming practices.In addition to the positive outcomes, challenges and barriers faced by farmers in adopting and adapting to E-Portals are also analyzed. Issues such as digital literacy, connectivity constraints, and the socio-economic divide are examined to provide a holistic understanding of the technology's impact on different segments of the farming community.The research contributes valuable insights for policymakers, technology developers, and stakeholders aiming to enhance the effectiveness of E-Portals in agriculture. By understanding the dynamics of technology adoption among farmers in Haryana, this study aims to inform strategies that can bridge existing gaps, promote inclusivity, and ensure sustainable development in the agricultural sector. The study finds that regional digitalization can significantly raise agricultural total factor productivity, particularly in economically underdeveloped areas.

乡村振兴战略下农产品跨境电商赋能乡村特色产业的研究

China is an agriculture-based country with vast rural areas, a wealth of agricultural products, and a large market. Cross-border e-commerce offers support for the export of agricultural products, which can break through the limitations of time and space, shorten the trade process of agricultural products, enhance the export efficiency of agricultural products, stabilize agricultural product trade, and promote the transformation and upgrading of China’s e-commerce. It also aids in the construction of a long-term mechanism for e-commerce poverty alleviation and agricultural revitalization. However, research has found that despite the rapid development of China’s crossborder e-commerce for agricultural products, there are still some issues, such as non-uniform quality standards for export agricultural products, information asymmetry, an inadequate cross-national logistics system and level of logistics technology, low levels of after-sales service, and a lack of corresponding professional and technical personnel. To address these issues, this article first introduces the current situation of China’s agricultural product export via cross-border e-commerce, then analyzes the development opportunities, and finally proposes the following solutions: aligning with international standards by establishing strict quality control mechanisms; creating a favorable policy environment, including policy support, resource allocation, and organizational guarantees; continuously improving product quality; focusing on the training of professional talent; and strengthening quality supervision and risk prevention. The aim is to promote the development of cross-border ecommerce for agricultural products, empower rural specialty industries, and support the implementation of the rural revitalization strategy.

Plastic film mulch use efficiency in agricultural production: a regional analysis in China

Plastic film mulch use efficiency in agricultural production: a regional analysis in China

Rainfall’s impact on agricultural production and government poverty reduction efficiency in China

The quest to eradicate poverty, central to the United Nations Sustainable Development Goals (SDGs), poses a significant global challenge. Advancement in sustainable rural development is critical to this effort, requiring the seamless integration of environmental, economic, and governmental elements. Previous research often omits the complex interactions among these factors. Addressing this gap, this study evaluates sustainable rural development in China by examining the interconnection between agricultural production and government-led poverty reduction, with annual rainfall considered an influential factor of climate change impacts on these sectors and overall sustainability. Utilizing a Meta-frontier entropy network dynamic Directional Distance Function (DDF) within an exogenous Data Envelopment Analysis (DEA) model, we categorize China’s 27 provinces into southern and northern regions according to the Qinling-Huaihe line for a comparative study of environmental, economic, and governmental efficiency. This innovative approach overcomes the limitations of previous static analyses. The findings reveal: (1) Rainfall, as an exogenous variable, significantly affects agricultural production efficiency. (2) The overall efficiency in both southern and northern regions increases when accounting for rainfall. (3) Government effectiveness in poverty reduction is comparatively lower in the northern region than in the southern region when rainfall is considered. These insights underscore the importance of including climatic variables in sustainable development policies and emphasize the need for region-specific strategies to bolster resilience against climatic challenges.

The effect of AlCrN, TiN and Ni-Cr-Nb coatings on the wear and corrosion performance of 45 # steel in 3.5 % sodium chloride solution

The press bar of the oil press is prone to corrosion and abrasion in the high-temperature and high-pressure environment, which reduces the quality of oil and the efficiency of agricultural production. In this paper, Ni-Cr-Nb, TiN and AlCrN coatings were prepared on the surface of press bar substrate by thermal spraying and multi-arc ion plating technology. The tests were analyzed by modern analytical methods such as HV-1000Z micro Vickers hardness tester, SEM, XRD and electrochemical corrosion. The results show that: Vickers hardness tester analysis shows that the surface hardness of AlCrN coating is 3.6 times higher than that of the base material, which is higher than that of several other coatings; SEM shows that the surfaces of the Ni-Cr-Nb, TiN and AlCrN coatings are smooth and even, the film structure is compact and uniform, and the thickness of the coating film is 5.67μm, 6.31 μm and 6.55 μm, respectively; XRD shows the elemental content of each coating, and the Al atoms in the AlCrN coating have good corrosion resistance; Electrochemical corrosion experiment shows that AlCrN coating has the biggest and most important advantages. It shows that AlCrN coating has the maximum potential and minimum corrosion current density, which indicates that its corrosion resistance is the best, followed by TiN coating, Ni-Cr-Nb layer of the corrosion resistance of the first two coatings, but better than the press bar substrate.

Increasing overall agricultural productivity in the Yellow River Delta Eco-economic Zone in China

AbstractImproving the efficiency of agricultural production in infertile areas contributes to reducing hunger, ensuring food security, and promoting eco-economic development. This study examines the effects and mechanisms of the Yellow River Delta High Efficiency Ecological Economic Zone policy on agricultural total factor productivity. The data from prefecture-level cities and a difference-in-difference model were used, and descriptive statistics and multiple regression analysis were conducted. The results show that the establishment of the zone increased agricultural total factor productivity by 40%. Heterogeneity analysis reveals that this positive effect is particularly pronounced in regions with a high proportion of agriculture and high per capita disposable income. However, this effect has diminished year by year since 2010. Mechanism tests suggest that the increase in agricultural R&D, the improvement in mechanization, and the application of ecological technologies have boosted agricultural total factor productivity. The results confirm the positive effects of the ecological economic zone policy and highlight the need for further measures to maintain and increase these positive effects in the long term. Future research should explore specific micro-management and technological measures to improve agricultural performance.

Productive, Environmental and Economic Effects of Organic and Conventional Farms—Case Study from Poland

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.

Evaluation of Mosaic Image Quality and Analysis of Influencing Factors Based on UAVs

With the growing prominence of UAV-based low-altitude remote sensing in agriculture, the acquisition and processing of high-quality UAV remote sensing images is paramount. The purpose of this study is to investigate the impact of various parameter settings on image quality and optimize these parameters for UAV operations to enhance efficiency and image quality. The study examined the effects of three parameter settings (exposure time, flight altitudes and forward overlap (OF)) on image quality and assessed images obtained under various conditions using signal-to-noise ratio (SNR) and BRISQUE algorithms. The results indicate that the setting of exposure time during UAV image acquisition directly affects image quality, with shorter exposure times resulting in lower SNR. The optimal exposure times for the RGB and MS cameras have been determined as 0.8 ms to 1.1 ms and 4 ms to 16 ms, respectively. Additionally, the best image quality is observed at flight altitudes between 15 and 35 m. The setting of UAV OF complements exposure time and flight altitude; to ensure the completeness of image acquisition, it is suggested that the flight OF is set to approximately 75% at a flight altitude of 25 m. Finally, the proposed image redundancy removal method has been demonstrated as a feasible approach for reducing image mosaicking time (by 84%) and enhancing the quality of stitched images (by 14%). This research has the potential to reduce flight costs, improve image quality, and significantly enhance agricultural production efficiency.

Роль инвестиций в повышении экономической эффективности сельскохозяйственного производства

The research is aimed at studying the role of investments in increasing the economic efficiency of agricultural production. As a result of the analysis, a close relationship was revealed between the index of the physical volume of investments and the increase in gross output. More than 70 % of state support for agriculture is concentrated in the Central Federal District and the Volga Federal District. This fact determines the uneven development of rural areas. The authors note that the livestock industry, due to the high saturation of the domestic market, becomes less attractive to investors, as the risks of non-demand for products increase. A negative situation is also developing in grain production as a result of the lack of opportunities for the development of the production base, high export duties, reduced technological efficiency of cultivation, and high natural and climatic risks. A decrease in investments is also observed in the greenhouse industry, due to the highly competitive market and the lack of state support measures to reimburse capital costs for the construction of greenhouses. There is no stagnation in the industrial segment of dairy production. There is a tendency to suspend investment projects for the construction or modernization of livestock complexes, greenhouse complexes, grain terminals, as well as grain processing plants. The main attractive segments for investment at the moment are the production of fertilizers, grain cultivation, production of oils and fats, and production of dairy products.

Green Fruit Detection with a Small Dataset under a Similar Color Background Based on the Improved YOLOv5-AT.

Green fruit detection is of great significance for estimating orchard yield and the allocation of water and fertilizer. However, due to the similar colors of green fruit and the background of images, the complexity of backgrounds and the difficulty in collecting green fruit datasets, there is currently no accurate and convenient green fruit detection method available for small datasets. The YOLO object detection model, a representative of the single-stage detection framework, has the advantages of a flexible structure, fast inference speed and excellent versatility. In this study, we proposed a model based on the improved YOLOv5 model that combined data augmentation methods to detect green fruit in a small dataset with a background of similar color. In the improved YOLOv5 model (YOLOv5-AT), a Conv-AT block and SA and CA blocks were designed to construct feature information from different perspectives and improve the accuracy by conveying local key information to the deeper layer. The proposed method was applied to green oranges, green tomatoes and green persimmons, and the mAPs were higher than those of other YOLO object detection models, reaching 84.6%, 98.0% and 85.1%, respectively. Furthermore, taking green oranges as an example, a mAP of 82.2% was obtained on the basis of retaining 50% of the original dataset (163 images), which was only 2.4% lower than that obtained when using 100% of the dataset (326 images) for training. Thus, the YOLOv5-AT model combined with data augmentation methods can effectively achieve accurate detection in small green fruit datasets under a similar color background. These research results could provide supportive data for improving the efficiency of agricultural production.

Establishment of deep learning model for the growth of tea cutting seedlings based on hyperspectral imaging technique

The shoot and root growth not only serve as important indicators for measuring the quality of tea cutting seedlings, but also can provide scientific basis for agricultural production and fine seedling management. Currently, manual weighing is the main method used to measure shoot and root growth, which is both destructive and inefficient. The study proposes a method for monitoring the shoot and root growth in tea cutting seedlings using hyperspectral imaging. First, mature leaves and shoots spectra were extracted from tea cutting seedlings using Mask R-CNN (Epoch=20 and Learning-rate=0.001). The spectra were then preprocessed by MSC, S-G, 1-D filtering techniques, with feature bands screened by UVE (Optimal factor number=5), CARS (Monte Carlo sampling times=300), and SPA (Epoch=25). Finally, a CNN-GRU (Epoch=100 and Learning-rate=0.01) network was employed to predict shoot and root biomass, and compared with machine learning methods of SVR (Kernel function=Polynomial), RFR (Ntrees=200), and PLSR (Latent variable=16) and deep learning methods (Epoch=100 and Learning-rate=0.01) of CNN and LSTM. The results show that (i) Mask R-CNN can accurately extract the spectral of mature leaves (precision=97.8 %) and shoots (precision=91.5 %), (ii) The spectral feature bands of shoot (number=212) and root (number=105) biomass screened by UVE were more abundant than CARS and SPA, (iii) The UVE+CNN-GRU model (Rp2=0.90, RMSEP = 0.12, RPD=2.43) based on shoots spectrum provided the optimal estimation of shoot biomass. The SPA+LSTM model (Rp2 = 0.65, RMSEP = 0.05, RPD=1.67) based on the mature leaves spectrum provided the optimal estimation of root biomass. These findings demonstrate that hyperspectral imaging technology combined with deep learning algorithms can accurately monitor the growth of cutting seedlings quickly without causing damage. This not only provides a new data sources along with technical means for efficient screening excellent tea varieties, but also improves agricultural production efficiency and resource utilization.

From the Perspective of Digital Economy, the New Direction of Rural Development in Jiangxi

This study explores the impact of the digital economy on rural development and finds that the digital economy has become an important force in promoting my country's economic development. In Jiangxi, a major agricultural province, digital technology can help improve agricultural production efficiency, reduce production costs, promote agricultural productivity, optimize the agricultural industry chain, and increase farmers' income. However, Jiangxi's digital infrastructure construction is still insufficient, especially in remote and poor areas. Therefore, this study aims to provide targeted policy suggestions for policymakers, promote the transformation and upgrading of the rural economy, and provide a theoretical basis for realizing the rural revitalization strategy. In the context of the digital economy, Jiangxi Province actively promotes rural industrial innovation, financial popularization and digital governance improvements, laying a digital foundation for increasing the income of rural families and achieving the strategic goals of rural revitalization.

Towards Resilient and Sustainable Food Systems: Integrating Agricultural Production Efficiency and Food Security

This study explores the nexus between agricultural production efficiency and food security, globally and within Turkey. It analyzes agricultural data, emphasizing strategies to enhance productivity while ensuring access to nutritious food. Key areas include reducing food loss, promoting sustainable practices, ensuring safety, enhancing consumer awareness, and preserving resources. The article also outlines the six dimensions of food security availability, access, utilization, stability, agency, and sustainability and their policy implications. By integrating insights from diverse studies and emphasizing context-specific approaches, it advocates for holistic strategies tailored to each agricultural landscape’s unique challenges. Ultimately, the pursuit of agricultural efficiency and food security is positioned as both a moral imperative and an economic necessity. Through research, policy reforms, and stakeholder collaboration, nations can work towards resilient and sustainable food systems for present and future generations. In the study, it was determined that labor productivity was not taken into account sufficiently and the data was insufficient to measure labor and labor productivity in agricultural production. The study aims to contribute to strategic decision-making and local-global policies to increase agricultural and resource use efficiency.