Energy is a major component in enhancing agricultural productivity for the rapidly growing world population. From that fact, a comprehensive analysis of energy inputs and outputs is required to conserve energy for future generations without threatening the food supply. Therefore, this study was performed in wheat production across important cropping zones of Punjab, Pakistan. In this study, the energy use pattern of wheat production was analyzed, and the degrees of technical efficiency of Decision Making Units (DMUs) were examined using Data Envelopment Analysis (DEA). Based on the results of the DEA analysis, the inefficient energy inputs were identified and further explored with the core objective of a significant reduction of excess valuable resources. Data were collected from conducting a face-to-face questionnaire of 200 farmers. The farms for sample were chosen randomly by a stratified normal approach. The results disclosed that the input energy of 34,430.98 MJ ha⁻¹ was used up for wheat production with an output energy of 48,267.05 MJ ha⁻¹. Energy use efficiency, specific energy, energy productivity, and net energy gain in wheat production were calculated as 1.4 MJ kg⁻¹, 9.27 MJ kg⁻¹, 0.10 MJ kg⁻¹ and 13,836.07 MJ kg⁻¹, respectively. The average technical, pure technical, and scale efficiency of DMUs were 0.668, 0.776, and 0.828, respectively, and 0.74% of consulted DMUs were functioning at decreasing returns to scale. Additionally, the significant energy consumption belongs to fertilizer, and diesel fuel, which contribute 65% of the total energy input. If these inputs are applied and managed in line with ours optimize value (29,388.5 MJ ha⁻¹) could save 14.65% resources, which will eventually add the equal quantity in wheat-yield. The total Greenhouse Gas (GHG) emissions were calculated to be 866.43 kg CO₂-eq ha⁻¹. In conclusion, the results of the present study suggest that there is sensible capacity for enhancing the energy efficiency of wheat production in Pakistan by accompanying the recommendations for economical energy management, sustainable and efficient use of energy is extremely encouraged.

The impact of agricultural cooperatives on apple farmers’ technical efficiency (TE) in China was examined. The cooperatives were divided into two groups: a collective marketing group for farmers and an equivalent non-marketing group that did not provide a marketing service, although other functions remained the same. Using the propensity score matching (PSM) procedure and stochastic production frontier (SPF) modelling, cooperatives’ key functions that potentially increase farmers’ TE can be identified. The results indicate that membership of either group is positively related to yield. However, cooperatives that were not engaged in marketing achieved higher TE than non-members. This suggests that policy makers should encourage cooperatives to focus on activities that do not include direct marketing to increase TE in apple production in China.

Agricultural industries are the foundation of the modernization of agricultural and rural areas in China. National Modern Agricultural Industrial Parks (NMAIPs) provides a considerable nationwide platform for agricultural industries. We take 200 NMAIPs in China as objects. Through spatial analysis, the Herfindahl–Hirschman index, and the SBM-DEA model, we analyzed the development characteristics and regional differences of NMAIPs from the muti-level perspective of national planning, provincial coordination, and county implementation to propose policy recommendations aimed at sustainable and high-quality development. The results are as follows: (1) Regarding geospatial characteristics, NMAIPs are unevenly distributed, with a decreasing gradient from east to west. The direction is east (northward) to west (southward), consistent with the direction of the Hu line. The distribution density shows that the east is dense and the west is sparse. (2) For industrial concentration, the leading industries in NMAIPs tend to be homogenous. The HHI indicates that the homogenization of leading industries is widely represented in each province. The low oligopolistic areas are in the central and eastern regions of China, while the highly oligopolistic locations are in the western and northeastern provinces. (3) In inputs–outputs efficiency, the comprehensive technical efficiency is high but not optimal, while the distribution of values is high in the south and low in the north. Ten provinces are non-effective. According to inputs and outputs, the ineffective contribution of population of townships covered, occupied area and the capital from the collective economy are development barriers, and the high output value of NMAIPs cannot fully drive the employment and income of farmers. Further improvements are needed in terms of both pure technical efficiency and scale efficiency, and adjustments to scale operations should be in response to different returns to scale. Our research results provide policy recommendations for NMAIPs, including the establishment of a multi-level management mechanism, balancing regional development, diversifying and coordinating regional leading industries, and improving the efficiency of utilization factors.

China’s National Agricultural Science and Technology Parks (NASTPs) play a key role in improving the nation’s agro-industrial structure and regional economic development; notably, NASTPs can demonstrate innovations in modern agricultural science and technology and, relatedly, incubate emerging modern agri-industries. However, after more than 20 years of development, scholars have not yet to confirm whether NASTPs contribute to local economies. This study sought to explore the impact of NASTPs on county economic development, to identify the mechanisms behind this impact, and to verify these effects using a multi-period double difference method based on panel data from 1743 counties in China collected between 2000 and 2019. The study found that the NASTPs significantly improved county economic development. The policy effects were mainly evident in western regions and counties with higher levels of financial resources. No spatial spillover effects were observed. The NASTPs drove county economic growth through three main channels: agglomeration, institutional environment, and innovation effects. These findings provide insights useful for designing policies related to the high-quality construction of agricultural sci-tech parks, the high-quality growth of county economies, and a reduction in regional economic development gaps.

This study aims to analyze the spatial distribution characteristics and innovation efficiency of national agricultural science and technology parks (NASTPs) and identify the main influencing factors on the parks’ innovation and development. The goal is to optimize the allocation of science and technology innovation resources in these parks, promote national agricultural science and technology innovation, and enhance the quality of agricultural development. To achieve this, the paper employs spatial analysis methods and a three-stage DEA-Tobit model to conduct both macro and micro-level analyses. The research findings are as follows: (1) Distribution characteristics: NASTPs tend to exhibit a uniform distribution at the national scale, but at the provincial level, their distribution appears clustered and uneven. Specifically, three high-density areas and two sub-high-density areas have emerged on the eastern side of the Hu line, displaying a decreasing trend from east to west. (2) Innovation efficiency: By excluding the influence of environmental factors and random interference, the lack of scale efficiency (SE) emerges as the primary reason for the generally low innovation efficiency of NASTPs. (3) Environmental factors: Science and technology training exhibits a negative correlation with innovation efficiency in NASTPs. Leading enterprises, income level, innovation support, and demonstration and promotion show positive correlations with IE in NASTPs. To promote national agricultural science and technology innovation and enhance the quality of agricultural development, it is recommended, based on a central-level development perspective, to focus on the layout of the northeast and northwest regions. At the local level, expanding the scale of key enterprise inputs and increasing the demonstration and promotion of scientific and technological achievements are recommended. Additionally, at the NASTPs level, guiding the construction of a national agricultural high-tech industry demonstration zone is advised.

Based on a sample of 412 apple farmer households across Gansu, Shaanxi, Shanxi, and Shandong provinces in China, this study estimates production efficiency and its determinants for apple growers. The stochastic frontier analysis model estimates technical efficiency while the Tobit model identifies influencing factors. Results show that the average production efficiency of smallholder apple farmers is relatively low at 0.45, indicating significant room for improvement. Production efficiency exhibits an inverted “U” relationship with farm scale, and excessive pesticide inputs have a significant negative impact on efficiency. Computer use to search for information among farmers was found to significantly improve apple production efficiency, indicating the potential benefits of ICT adoption. However, membership in cooperatives had no significant effect on efficiency. Overall, these findings suggest approaches to enhance the productivity of China’s apple growers through improved resource allocation, optimized farm scale, and the promotion of information technology.