Traditional pesticide application methods often result in excessive deposition and drift in non-target areas, leading to severe environmental pollution. This study proposes a precision variable-rate spraying system for greenhouse asparagus based on real-time canopy semantic segmentation and volume estimation. To address the challenges of occlusion and sparsity in asparagus point clouds, an improved RangeNet++ architecture is introduced, incorporating Lightweight Channel Attention (LCA) and Efficient Spatial Attention (ESA) mechanisms to optimize feature extraction. An adaptive feature fusion module is further designed to enhance boundary delineation. Based on the semantic segmentation, an octree-based 3D grid model is constructed to calculate canopy volume in real-time, driving a CAN-bus controlled variable-rate spraying robot. Field experiments demonstrated that the proposed method significantly outperforms the standard RangeNet++, particularly in asparagus segmentation, where the Intersection over Union (IoU) increased by 13.2% and overall accuracy improved by 2.1%. For online canopy volume estimation, the system achieved accuracies of 90.07%, 89.73%, and 88.34% at robot travel speeds of 0.2, 0.4, and 0.6 m/s, respectively, demonstrating robust performance under dynamic operational conditions. Pearson correlation analysis confirmed a strong positive correlation between the applied spray volume and canopy density. Furthermore, filter paper deposition tests revealed that variable-rate spraying significantly improved uniformity: the Coefficient of Variation (CV) of deposition in the outer, middle, and inner canopy layers was reduced from 94.2%, 53.9%, and 70.0% (conventional spraying) to 38.5%, 49.8%, and 46.5% (variable spraying), respectively. The proposed system effectively mitigates localized excessive deposition while maintaining adequate coverage, providing a viable engineering solution for precision plant protection in facility agriculture.

In order to better promote the use of intelligent agricultural machinery, enhance the efficiency of grain production, optimize resource utilization, and effectively address the practical problem of the reduction in the rural labor force, while theoretically clarifying the mechanism that affects the adoption of intelligent agricultural machinery by farmers in Changsha County. Based on a questionnaire survey of farmers in Changsha County, Hunan Province, the ordered logit model was used to identify the significant factors influencing farmers’ adoption of intelligent agricultural machinery. The empirical results show that male farmers, farmers with a non-agricultural occupation, and farmers with a lower education level (below high school) have a lower willingness to adopt intelligent agricultural machinery. As the risk of purchasing intelligent agricultural machinery decreases, market demand increases, and the number of agricultural services provided by the government increases, the likelihood of farmers adopting intelligent agricultural machinery also increases. Based on these findings, this paper proposes targeted suggestions aimed at increasing the adoption of intelligent agricultural machinery by farmers in Changsha County, Hunan Province.

The autonomous navigation methodology for greenhouse spraying robots improves operational efficiency and reduces human workload. However, navigation solutions based on Light Detection and Ranging (LiDAR) Simultaneous Localization and Mapping (SLAM) still face challenges such as mapping distortion caused by crop feature similarity, gradual accumulation of positioning errors, and positioning jumps, which fail to meet the positioning accuracy demands in agricultural robotic operations. This paper proposed an autonomous navigation methodology for greenhouse spraying robots that integrated three-dimensional (3D) LiDAR and ultrasonic tags into SLAM technology. The proposed approach generated a 3D point cloud map of the greenhouse environment through loosely coupled data fusion of a 3D LiDAR and an Inertial Measurement Unit (IMU). Robot relocalization and navigation trajectory recording utilized the pre-built point cloud map and ultrasonic tags. To further enhance positioning accuracy and robustness, a tightly-coupled framework combining LiDAR and ultrasonic tags was designed, incorporating an improved Iterative Closest Point (ICP) method and Singular Value Decomposition (SVD) algorithm for precise registration positioning. The SLAM mapping trajectories and navigation performance were validated in a standardized strawberry greenhouse. Results showed that at speeds of 0.2 ​m/s, 0.4 ​m/s, and 0.6 ​m/s, the maximum average absolute pose error between the positioning trajectory and the ground truth was 0.357 ​m, with a standard deviation of 0.148 ​m. Compared with the Cartographer and Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping (LIO-SAM) methods, the improved method reduced the average positioning error by 32.0 ​% and 14.0 ​%, respectively. Navigation tests demonstrated that the robot's maximum lateral error was 0.045 ​m, with a maximum average lateral positioning error of 0.022 ​m. These results confirm that the robot positioning and navigation accuracy satisfies the requirements for autonomous operations in greenhouse spraying, providing a reliable solution for autonomous navigation in structured agricultural environments.

This study investigates the influence of agricultural mechanization on maize productivity in Tanzania’s Ruvuma region, a major maize-producing area vital to national food security. It addresses gaps in understanding the cumulative effects of mechanization across the maize production cycle and identifies region-specific barriers to adoption among smallholder farmers. Focusing on five key stages—land preparation, planting, plant protection, harvesting, and drying—this research evaluated mechanization uptake at each stage and its relationship with yield disparities. Statistical analyses using Python libraries included regression modeling, ANOVA, and hypothesis testing to quantify mechanization–yield relationships, controlling for farm size and socioeconomic factors, revealing a strong positive correlation between mechanization and maize yields (r = 0.86; p < 0.01). Mechanized land preparation, planting, and plant protection significantly boosted productivity (β = 0.75–0.35; p < 0.001). However, harvesting and drying mechanization showed negligible impacts (p > 0.05), likely due to limited adoption by smallholders combined with statistical constraints arising from the small sample size of large-scale farms (n = 20). Large-scale farms achieved 45% higher yields than smallholders (2.9 vs. 2.0 tons/acre; p < 0.001), reflecting systemic inequities in access. These inequities are underscored by the barriers faced by smallholders, who constitute 70% of farmers yet encounter challenges, including high equipment costs, limited credit access, and insufficient technical knowledge. This study advances innovation diffusion theory by demonstrating how inequitable resource access perpetuates low mechanization uptake in smallholder systems. It underscores the need for context-specific, equity-focused interventions. These include cooperative mechanization models for high-impact stages (land preparation and planting); farmer training programs; and policy measures such as targeted subsidies for harvesting equipment and expanded rural credit systems. Public–private partnerships could democratize mechanization access, bridging yield gaps and enhancing food security. These findings advocate for strategies prioritizing smallholder inclusion to sustainably improve Tanzania’s maize productivity.

Agricultural activities are incomplete without the proper wheat storage, and maintaining optimal storage conditions requires an effective management system. This study presents a control system designed to improve the storage conditions of wheat using an Arduino UNO, a DHT22 sensor, and a fan cooling system to manage the environment. The device continually monitors temperature and relative humidity, as well as giving a nondestructive evaluation of the moisture content of wheat kept in silos. During the study, the system confirmed its efficacy by effectively maintaining appropriate storage conditions, such as average temperature and humidity levels, which encourage safe wheat storage. The automatic fan system effectively regulates temperature fluctuations, providing ideal conditions. The study examined the system's capacity to control essential parameters such as moisture content and germination rate of preserved seeds. The results indicated that the temperature dropped by 1.25 degrees C per minute when the fan was activated, with a threshold activation temperature of 30 degrees C. The recorded temperature and humidity of the stored wheat were 34.76 degrees C and 43.33 %, respectively. The moisture content ranged from 15.26 % to 11.73 %, while the seed germination rate ranged from 94.27 % to 75.66 %. Compared to conventional storage methods, the system demonstrated superior performance in reducing moisture levels, stabilizing temperature fluctuations, and preserving wheat quality, ultimately lowering the risk of insect infestation and post-harvest losses. Although its success, issues of scalability, cost-effectiveness, and adaption to varied environmental circumstances were recognized. Future experimental research should concentrate on incorporating modern IoT technologies for real-time monitoring, enhancing energy efficiency, and evaluating the system in bigger storage facilities or with diverse crop varieties. Rectifying these deficiencies will augment the system's relevance and bolster rural food security and economic stability.

ObjectiveFarmland consolidation for agricultural mechanization in hilly and mountainous areas can alter the landscape pattern, elevation, slope and microgeomorphology of cultivated land. It is of great significance to assess the ecological risk of cultivated land to provide data reference for the subsequent farmland consolidation for agricultural mechanization. This study aims to assess the ecological risk of cultivated land before and after farmland consolidation for agricultural mechanization in hilly and mountainous areas, and to explore the relationship between cultivated land ecological risk and cultivated land slope.MethodsTwenty counties in Tongnan district of Chongqing city was selected as the assessment units. Based on the land use data in 2010 and 2020 as two periods, ArcGIS 10.8 and Excel software were used to calculate landscape pattern indices. The weights for each index were determined by entropy weight method, and an ecological risk assessment model was constructed, which was used to reveal the temporal and spatial change characteristics of ecological risk. Based on the principle of mathematical statistics, the correlation analysis between cultivated land ecological risk and cultivated land slope was carried out, which aimed to explore the relationship between cultivated land ecological risk and cultivated land slope.Results and DiscussionsComparing to 2010, patch density (PD), division (D), fractal dimension (FD), and edge density (ED) of cultivated land all decreased in 2020, while meant Patch Size (MPS) increased, indicating an increase in the contiguity of cultivated land. The mean shape index (MSI) of cultivated land increased, indicating that the shape of cultivated land tended to be complicated. The landscape disturbance index (U) decreased from 0.97 to 0.94, indicating that the overall resistance to disturbances in cultivated land has increased. The landscape vulnerability index (V) increased from 2.96 to 3.20, indicating that the structure of cultivated land become more fragile. The ecological risk value of cultivated land decreased from 3.10 to 3.01, indicating the farmland consolidation for agricultural mechanization effectively improved the landscape pattern of cultivated land and enhanced the safety of the agricultural ecosystem. During the two periods, the ecological risk areas were primarily composed of low-risk and relatively low-risk zones. The area of low-risk zones increased by 6.44%, mainly expanding towards the northern part, while the area of relatively low-risk zones increased by 6.17%, primarily spreading towards the central-eastern and southeastern part. The area of moderate-risk zones increased by 24.4%, mainly extending towards the western and northwestern part, while the area of relatively high-risk zones decreased by 60.70%, with some new additions spreading towards the northeastern part. The area of high-risk zones increased by 16.30%, with some new additions extending towards the northwest part. Overall, the ecological safety zones of cultivated relatively increased. The cultivated land slope was primarily concentrated in the range of 2° to 25°. On the one hand, when the cultivated land slope was less than 15°, the proportion of the slope area was negatively correlated with the ecological risk value. On the other hand, when the slope was above 15°, the proportion of the slope area was positively correlated with the ecological risk value. In 2010, there was a highly significant correlation between the proportion of slope area and ecological risk value for cultivated land slope within the ranges of 5° to 8°, 15° to 25°, and above 25°, with corresponding correlation coefficients of 0.592, 0.609, and 0.849, respectively. In 2020, there was a highly significant correlation between the proportion of slope area and ecological risk value for cultivated land slope within the ranges of 2° to 5°, 5° to 8°, 15° to 25°, and above 25°, with corresponding correlation coefficients of 0.534, 0.667, 0.729, and 0.839, respectively.ConclusionsThe assessment of cultivated land ecological risk in Tongnan district of Chongqing city before and after the farmland consolidation for agricultural mechanization, as well as the analysis of the correlation between ecological risk and cultivated land slope, demonstrate that the farmland consolidation for agricultural mechanization can reduce cultivated land ecological risk, and the proportion of cultivated land slope can be an important basis for precision guidance in the farmland consolidation for agricultural mechanization. Considering the occurrence of moderate sheet erosion from a slope of 5° and intense erosion from a slope of 10° to 15°, and taking into account the reduction of ecological risk value and the actual topographic conditions, the subsequent farmland consolidation for agricultural mechanization in Tongnan district should focus on areas with cultivated land slope ranging from 5° to 8° and 15° to 25°.

This study evaluates the economic impact of mechanization adoption in rice farming within the Gujranwala district of Punjab in 2024. A total of 150 rice farmers were surveyed using a structured questionnaire and categorized into mechanized and non-mechanized groups based on their use of machinery. Cost and revenue assessment were carried out for both groups, the comparison of average costs and revenues between mechanized and non-mechanized farmers was performed using a t-test through SPSS software. The mean production cost was estimated to be PKR 84,080.34 per acre. It was found that land preparation, harvesting and threshing, and human labor costs were significantly higher in non-mechanized farming. Mechanized farms had a lower average total cost of production compared to non-mechanized farms. The average revenue from rice production was significantly higher for mechanized farmers (PKR 165,142/acre) compared to nonmechanized farmers (PKR 151,823.33/acre). Additionally, mechanized farms demonstrated a higher net profit and benefit-cost (B:C) ratio (1.56) compared to non-mechanized farms (1.36). The findings demonstrate that mechanized rice farming has lower production costs and higher yields, which increase overall profitability. Therefore, the adoption of mechanization for rice cultivation in the Gujranwala district is strongly recommended.

To address the problem that the low-density canopy of greenhouse crops affects the robustness and accuracy of simultaneous localization and mapping (SLAM) algorithms, a greenhouse map construction method for agricultural robots based on multiline LiDAR was investigated. Based on the Cartographer framework, this paper proposes a map construction and localization method based on spatial downsampling. Taking suspended tomato plants planted in greenhouses as the research object, an adaptive filtering point cloud projection (AF-PCP) SLAM algorithm was designed. Using a wheel odometer, 16-line LiDAR point cloud data based on adaptive vertical projections were linearly interpolated to construct a map and perform high-precision pose estimation in a greenhouse with a low-density canopy environment. Experiments were carried out in canopy environments with leaf area densities (LADs) of 2.945–5.301 m2/m3. The results showed that the AF-PCP SLAM algorithm increased the average mapping area of the crop rows by 155.7% compared with that of the Cartographer algorithm. The mean error and coefficient of variation of the crop row length were 0.019 m and 0.217%, respectively, which were 77.9% and 87.5% lower than those of the Cartographer algorithm. The average maximum void length was 0.124 m, which was 72.8% lower than that of the Cartographer algorithm. The localization experiments were carried out at speeds of 0.2 m/s, 0.4 m/s, and 0.6 m/s. The average relative localization errors at these speeds were respectively 0.026 m, 0.029 m, and 0.046 m, and the standard deviation was less than 0.06 m. Compared with that of the track deduction algorithm, the average localization error was reduced by 79.9% with the proposed algorithm. The results show that our proposed framework can map and localize robots with precision even in low-density canopy environments in greenhouses, demonstrating the satisfactory capability of the proposed approach and highlighting its promising applications in the autonomous navigation of agricultural robots.

［目的/意义］丘陵山区农田宜机化整治会改变耕地景观格局、高程、坡度、微地貌等，评价其生态风险 为后续整治工作提供数据参考具有重要意义。本研究的目的为评价丘陵山区农田宜机化整治对耕地生态风险的改 变情况以及探究生态风险与耕地坡度之间的关系。［方法］以重庆市潼南区20个县为评价单元，基于2010年和 2020年土地利用数据，采用ArcGIS 10.8和Excel软件计算景观格局指数，通过熵权法确定各指数的权重并构建生 态风险评价模型，揭示生态风险时序空间变化特征；基于数理统计原理，对生态风险与坡度进行相关性分析，探 究生态风险与坡度的关系。［结果和讨论］2010年和2020年两个时期，干扰度指数由0.97下降为0.94，耕地整体 抗干扰能力增强；脆弱度指数由2.96增加为3.20，耕地结构更加脆弱；生态风险值由3.10下降为3.01，耕地生态 安全性提高。两个时期生态风险区域主要以低风险区和较低风险区为主，低风险区面积增加6.44%，较低风险区 面积增加6.17%，中风险区面积增加24.4%，较高风险区面积减少60.70%，高风险区面积增加16.30%，耕地生态 安全区域相对增加。耕地坡度主要以2°~25°为主，耕地坡度小于15°时坡度面积占比与生态风险值呈负相关，耕 地坡度大于15°时坡度面积占比与生态风险值呈正相关关系，坡度处于5°~8°、15°~25°、25°以上时坡度面积与生 态风险值呈极显著相关。农田宜机化整治应重点关注潼南区南部区域，并集中于耕地坡度处于5°~8°和15°~25° 区域。［结论］通过评价潼南区农田宜机化整治前后耕地生态风险并分析生态风险与耕地坡度的相关性，表明农田 宜机化整治可以降低耕地生态风险，耕地坡度面积占比可作为精准指导农田宜机化整治的重要依据，潼南区宜机 化整治工作应重点关注耕地坡度处于5°~8°和15°~25°区域。

Soil compaction leads to crop yield reduction in Northeast of China. The interaction mechanism of driveragricultural machinery-black soil is not clear. A comprehensive field experiment of 4 hm2 of maize seeding was carried out in Baiquan County Cooperative. The results showed that the average increase rates of soil compaction before and after sowing were 118.82% and 71.02%. The SEM showed that waist fatigue had the greatest impact on soil compaction, and the unit fatigue of waist caused 1.51 and 1.27 unit compactions to the soil at the depths of 10 cm and 20 cm. The neck, waist, arm and leg fatigue of drivers increased the surface soil compaction by 1.83, 1.76, 1.78 and 1.55 units, and the deep soil compaction by 1.65, 1.58, 1.60 and 1.40 units. The results can provide a reference for the integration of human factor efficiency and conservation tillage.

The rollover problem is prominent for a small tractor under complicated road conditions. The application of active steering (AS) technology is an effective approach to solve this problem. A lateral stability index based on the critical position is proposed and improved. Sliding mode control (SMC) technology based on an exponential terminal sliding mode surface is studied by considering the parameter changes and external disturbances in the rollover process of the tractor, which further accelerates the system's response speed. A real vehicle test platform was built taking into account the limitations of the few real vehicle dynamic tests in current studies. Real vehicle dynamic tests with varying speeds, slopes, and obstacles were conducted for various road pavements and typical off-road pavements. For road pavements, the results demonstrated that the maximum roll angle of the tractor was 15.94 % less than with that under uncontrolled. For typical off-road pavements, AS control effectively restrained rollover accidents under non-extreme conditions, and SMC reduced the time the tractor was in the critical rollover region by 35.98 % on average compared with PID control. The stability region boundary of a small tractor was defined, and the stable driving region of a tractor on various slopes is obtained. This study provides a specific theoretical basis and implementation plan for guiding the research of tractor active safety technology.

In order to explore the influence of different agricultural tires on soil compaction in northeast black soil area， explore effective ways to reduce soil compaction， improve farmland ecology and protect black land， this study took typical black soil cultivated land in northeast China as the object， and carried out field operation comparative experiments based on different agricultural tires in the link of corn seeding. Two types of agricultural tires， ultra-low pressure radial tire and ordinary radial tire， were set up in the experiment. Four key soil physical property parameters， namely soil compactness， soil moisture content， soil bulk density and soil porosity， were calculated by scientific sampling method. On this basis， a comprehensive evaluation model of soil compaction was established based on CRITIC- entropy weight method， and the soil compaction status of ordinary radial tire （CK） and ultra-low pressure radial tire （VF） at the depth of 5cm， 10cm， 15cm and 20cm was evaluated statistically. The test results showed that in 0-20cm soil depth， compared with radial tire， ultra-low pressure radial tire reduced soil compactness by 11.38%， 7.97%， 5.36%， 4.55%， and increased soil moisture content by 11.06%， 10.07%， 7.37%， 5.95%. Soil bulk density was reduced by 3.71%， 3.81%， 3.12% and 2.73%， and soil porosity was increased by 11.13%， 12.25%， 8.92% and 5.86%. The soil comprehensive evaluation scores of different treatments in descending order were CK5， CK10， CK15， CK20， VF5， VF10， VF15 and VF20， indicating that under the same conditions， the soil comprehensive condition of compacting ultra-low pressure radial tire was better than that of ordinary radial tire. The results showed that ultra-low pressure radial tire had positive effects on reducing compaction of black soil and maintaining soil physical environment， which was helpful to protect black soil and ensure national food security.

The corn production cost (CPC) in China is related to national food security. However, there are few studies on the temporal and regional differences (TRD) and sensitive factors in the CPC. In this paper, the TRD of the corn production cost across various regions, as well as over the entirety of the country from 2008 to 2018, is presented. It is based on the GIS exploratory spatial data analysis method (ESDA). Simultaneously, a spatial panel model is established to conduct an empirical analysis of the main factors affecting the CPC. The results from the period in question show that the CPC in China and the three major production regions present a fluctuating growth trend, mainly associated with the increase in labor prices. Moreover, the CPC exhibits significant spatial differences, and demonstrates an overall trend of gradual increase from the east to the west. Over time, the number of relatively high-cost provinces has increased. All are located in southern mountainous and hilly corn areas. In addition, the CPCs of various regions are spatially correlated. Factors such as the scale of land management, the degree of mechanization, and socioeconomic conditions have a significantly negative impact on the CPC in China. Furthermore, the labor structure has a notably positive impact on the CPC.

In this study, we addressed the problem of the spatial variability of plough layer compaction by high-power and no-tillage multifunction units in the management of maize planting in the Great Northern Wilderness in China. A comprehensive field experiment involving high-power and no-tillage multifunction units for 165 acres of maize was conducted and analyzed using GIS. Firstly, the test area was divided into four areas, and points were set at equal horizontal distances to collect data on the compactness, water content, porosity and fatigue of the plough layer at different depths. Secondly, the GIS kriging difference method was used to analyze the impact of longitudinal compaction of the plough layer profile at each depth in different test areas. Thirdly, the GIS kriging difference method was used to analyze the lateral spatial distribution of plough layer compaction. Finally, the spatial longitudinal and transverse variabilities of the plough layer were summarized, and the effect of the high-power and no-tillage multifunction units on the physical ecology of the soil in the plough layer was investigated. The results show that the physical properties of the plough layer can be significantly affected by compaction after spreading in the middle tillage period. The surface soil was most affected, with the greatest change in compactness and porosity; the rate of change of soil compactness reached 143.49% and the rate of change of soil porosity reached 40.57%. With the increase in soil depth, the rate of change of soil compactness and porosity gradually decreased. The greatest variation in soil moisture content was found in the middle layer and reached a maximum of 13.78% at a depth of approximately 20 cm. The results of the spatial variability analysis show that the mean values of c0/(c0 + c) for the spatial semi-variance functions of compactness, water content and porosity of the tilled soil in the longitudinal space of each test area before compaction were approximately 15%, 19% and 20%, respectively; after compaction, the mean values were approximately 33%, 23% and 30%, respectively; the mean values of c0/(c0 + c) for the spatial semi-variance functions of compactness, water content and porosity change of the tilled soil were approximately 24%, 14% and 12%, respectively. The mean values of c0/(c0 + c) for the spatial semi-variance functions of compactness, water content and porosity of the soil at each depth in the lateral space before compaction were approximately 80%, 71% and 78%, respectively, and after compaction the mean values were approximately 40%, 23% and 24%, respectively, with the mean values of c0/(c0 + c) along the east–west direction being approximately 8%, 27% and 18%, and the mean values of c0/(c0 + c) along the north–south direction being approximately 9%, 0% and 20%. The results show that compaction by high-power and no-tillage multifunction units led to a decrease in the spatial variability of soil physical parameters at each depth of tillage in the black soil layer in the longitudinal space, while the spatial variability of the soil physical parameters at each depth of tillage in the black soil layer in the transverse space increased. Moreover, the degree of influence of compaction by high-power and no-tillage multifunction units on soil physical parameters was higher in both vertical and horizontal spaces. This study can provide a theoretical reference for the analysis of the impact of large units on the compaction of black soil layers from the perspective of GIS.

China is a large agricultural country and agriculture is the foundation of the national economy, with hilly and mountainous areas accounting for more than 60%. Most are run by small farmers, but there is also some development of agricultural cooperatives, agricultural machinery cooperatives and family farms. Since 1970, great achievements have been made in the development of agricultural mechanization in China in the past 50 years. China's agricultural machinery and equipment holdings, agricultural mechanization operation level, socialized service level have improved rapidly. China has made major breakthroughs in scientific and technological innovation in agricultural mechanization, and has been significantly enhanced in international cooperation and exchanges. China has a sound legal, regulatory and policy system for agricultural mechanization. Agricultural mechanization has provided strong support for China's food security, the transfer of agricultural labor force, the improvement of agricultural labor productivity, the rapid development of urbanization, and the modernization of agriculture and rural areas. A road of agricultural mechanization has been formed with Chinese characteristics. The environment of China's economic, technological and policy for agricultural mechanization development continue to improve. The priorities of future agricultural mechanization will be placed at developing resource- and labor- saving technologies, shifting focus from production to higher efficiency, as well as from single technologies to integrated technologies, and trend to intelligent agriculture, intelligent agricultural machinery development. The role of agriculture will become much more significant to national economy for it to keep high growth rate.

An efficient assessment of energy consumption, energy flow, and energy use efficiency in crop (maize) production is inevitable to accomplish the intensive demand for energy. Data Envelopment Analysis (DEA) models based on energy input-output analysis are commonly used for the assessment of energy efficiency. However, standard implication of traditional (CCR) and extended (SBM) models has shortcomings in reporting efficiency score; CCR neglects slacks while SBM caused problems when reporting efficiency over time. To overcome this problem, an ensemble approach that compromised the characteristics of two models (CCR-SBM) is proposed in the current study. Based on the weighted average of the relative efficiencies of two contending models, an ensemble efficiency (EE) score was reported for energy efficiency evaluation of considered DMUs. Preliminary analysis ensued average maize yield of 6874 kg ha−1 with an overall energy input of 42,241.45 MJ ha−1, and net energy gain, energy use efficiency (average), specific energy, and energy productivity, were 58,806 MJ ha−1, 2.39, 6.15 MJ kg−1, and 0.16 kg MJ−1, respectively. Using four major shareholders of input energy (i.e., fertilizer, diesel fuel, irrigation water and chemicals) and, maize yield as output, the projected ensemble approach resulted in an unproductive trend of energy use efficiency in Pakistan with an average ensemble efficiency score of 59.67%, and plausible potential of energy saving from 7181.046 to 33,370.74 MJ ha−1. Furthermore, the ensemble approach showed that EE score could help to significantly reduce the shortcomings of slacks and time fluctuation when reporting efficiency score, compared with using individual models. The proposed approach scrutinized and provided a comprehensive state of the actual situation of energy efficiency in maize production of Pakistan that is important in the context of decision-making. Results of the study suggest resource conservation measures through better agricultural management practices, and production methods and extension activities are required to improve the efficiency of energy consumption in maize production of Pakistan.

“十四五”是我国全面建成小康社会后奋力实现2035年“农业农村现代化基本实现”战略同标的第一个五年,新形势、新任务、新需求对农业机械化提出了更高要求.深刻认识新时期农业机械化与农业农村现代化的关系,分析农业机械化面临的重大挑战及迫切需要解决的问题,更好地发挥农业机械化对农业农村现代化和乡村振兴目标的支撑作用意义重大.

This paper aims to point out the necessity and feasibility of the construction of the agricultural manufacturing industrial clusters’ knowledge service platform based on the prior research of clusters’ knowledge service platforms. And then the knowledge service platform of Shandong province has been illustrated as an instance to analyze the current situation of industrial development, the construction and operation aspect of the knowledge service platform. This paper presents several basic recommendations such as the alliance development, professional development, diversified development, sharing development and coordinated development to optimize agricultural machinery manufacturing cluster knowledge service platform, so as to improve the overall level of the knowledge service platform as well as promote the transformation and the upgrade of the agricultural machinery manufacturing industry.