Agriculture, Volume 14, Issue 5 (May 2024) – 140 articles

In order to improve the obstacle avoidance control performance and anti-interference ability of a stubble breaking device of a no-tillage planter, a back-propagation neural network (BPNN)-optimized fuzzy active disturbance rejection control (ADRC) controller was designed to optimize the control performance of a servo motor. Firstly, a negative feedback mathematical model was established for the obstacle avoidance control system. Then, the nonlinear state error feedback (NLSEF) parameters in the fuzzy ADRC were intelligently optimized by the BPNN algorithm. In this way, a fuzzy ADRC controller based on BPNN optimization was formed to optimize the control process of a servo motor. Matlab/Simulink (R2022b) was used to complete the simulation model design and parameter adjustment. Consequently, the response time was 0.089 s using the BPNN fuzzy ADRC controller, which was shorter than the 0.303 s of the ADRC controller and the 0.100 s of the fuzzy ADRC controller. The overshoot was 0.1% using a BPNN fuzzy ADRC controller, which was less than the 2% of the ADRC controller and the 1% of the fuzzy ADRC controller. After noise signal interference was introduced into the control system, the regression steady state time of the BPNN fuzzy ADRC controller was 0.22 s, which was shorter than the 0.56 s of the ADRC controller and the 0.45 s of the fuzzy ADRC controller. A hardware-in-the-loop simulation experimental platform of the obstacle avoidance control system was constructed. The experiment results show that the servo motor control system has a fast dynamic response, small steady-state error and strong anti-interference ability for obstacle avoidance at the target height. Then, the control system error was within the allowable range. The servo motor control effect of the BPNN fuzzy ADRC was better than the ADRC and fuzzy ADRC. This optimized servo motor control method can provide a reference for improving the obstacle avoidance control effect problem of no-tillage seeders in stubble breaking operations on rocky desertification areas. Full article

Although China’s grain production has reached nineteen consecutive harvests, the uncertainty of the current domestic and international environment has put more pressure on further increasing grain production in the future. For the past few years, agricultural socialization services have been crucial in boosting grain production and farmers’ revenue by addressing the issue of land cultivation and farming methods. In this regard, the question of whether and how agricultural socialized services may resolve the present grain production conundrum is extremely practical. Therefore, the study employs the China Rural Revitalization Survey data of 3709 households. Based on the 2SLS model, stepwise regression method, and moderated effects model, it creatively takes into account a variety of agricultural production segments, investigates the mechanism of services on grain production from the standpoint of improved production efficiency and plot concentration, and further examines the effects of aging populations and regional variations in grain production areas. The study found the following: (1) The average proportion of grain production area of farmers in the sample is 49%, and 42% of farmers have purchased agricultural socialization services. (2) Agricultural socialization services can significantly promote farmers’ grain cultivation behavior by facilitating connected transfers in and inhibiting connected transfers out to take advantage of plot concentration, and boosting the use of agricultural machines to enhance output efficiency. (3) The aging of the agricultural population will, to a certain extent, strengthen the promoting effect of agricultural socialization services on grain cultivation. Agricultural socialization services affect grain cultivation more in main grain-producing areas. Therefore, emphasizing the role of agricultural socialization services in accelerating the shift to moderate-scale operations, decreasing the non-grain component of the planting structure, and promoting the implementation of policies tailored to actual production needs are important steps to safeguard the production capacity of grain in different regions. Full article

Crop yield estimation plays a crucial role in agricultural production planning and risk management. Utilizing simultaneous localization and mapping (SLAM) technology for the three-dimensional reconstruction of crops allows for an intuitive understanding of their growth status and facilitates yield estimation. Therefore, this paper proposes a VINS-RGBD system incorporating a semantic segmentation module to enrich the information representation of a 3D reconstruction map. Additionally, image matching using L_SuperPoint feature points is employed to achieve higher localization accuracy and obtain better map quality. Moreover, Voxblox is proposed for storing and representing the maps, which facilitates the storage of large-scale maps. Furthermore, yield estimation is conducted using conditional filtering and RANSAC spherical fitting. The results show that the proposed system achieves an average relative error of 10.87% in yield estimation. The semantic segmentation accuracy of the system reaches 73.2% mIoU, and it can save an average of 96.91% memory for point cloud map storage. Localization accuracy tests on public datasets demonstrate that, compared to Shi–Tomasi corner points, using L_SuperPoint feature points reduces the average ATE by 1.933 and the average RPE by 0.042. Through field experiments and evaluations in a strawberry field, the proposed system demonstrates reliability in yield estimation, providing guidance and support for agricultural production planning and risk management. Full article

The identification of seedling numbers is directly related to the acquisition of seedling information, such as survival rate and emergence rate. It indirectly affects detection efficiency and yield evaluation. Manual counting methods are time-consuming and laborious, and the accuracy is not high in complex backgrounds or high-density environments. It is challenging to achieve improved results using traditional target detection methods and improved methods. Therefore, this paper adopted the density estimation method and improved the population density counting network to obtain the rapeseed seedling counting network named BCNet. BCNet uses spatial attention and channel attention modules and enhances feature information and concatenation to improve the expressiveness of the entire feature map. In addition, BCNet uses a 1 × 1 convolutional layer for additional feature extraction and introduces the torch.abs function at the network output port. In this study, distribution experiments and seedling prediction were conducted. The results indicate that BCNet exhibits the smallest counting error compared to the CSRNet and the Bayesian algorithm. The MAE and MSE reach 3.40 and 4.99, respectively, with the highest counting accuracy. The distribution experiment and seedling prediction showed that, compared with the other density maps, the density response points corresponding to the characteristics of the seedling region were more prominent. The predicted number of the BCNet algorithm was closer to the actual number, verifying the feasibility of the improved method. This could provide a reference for the identification and counting of rapeseed seedlings. Full article

This study aims to analyze the drivers behind price changes in agricultural products in Türkiye from 2002 to 2021, considering the impacts of three crises of different causes which are the global food crisis, the Russia–Türkiye aircraft crisis, and the COVID-19 pandemic. The potential factors are categorized into four subgroups: governmental effects, agricultural inputs, macroeconomic indicators, and climatic conditions. The selected agricultural goods for price change measurement include wheat and maize representing subsistence goods, and olive oil and cotton as marketing goods. The autoregressive distributed lag (ARDL) model is applied to observe both the short- and long-term impacts of the variables on price developments. The results suggest that government effectiveness, regulatory quality, nitrogen use, water price, money supply, exchange rate, and GDP under the related categories are the most effective factors in price changes. Among the variables under the category of climatic conditions, significant values are obtained only in the analysis of the temperature impact on olive oil. The analysis also reveals the variable impact of crises on the prices of the chosen products, depending on the goods involved. The maize and wheat analyses yield particularly noteworthy results. In the long run, nitrogen use demonstrates a substantial positive impact, registering at 29% for wheat and 19.47% for maize, respectively. Conversely, GDP exhibits a significant negative impact, with 26.15% and 20.08%. Short-term observations reveal that a unit increase in the governmental effect leads to a reduction in inflation for these products by 17.01% and 21.42%. However, changes in regulatory quality result in an increase in inflation by 25.45% and 20.77% for these products, respectively. Full article

When studying the coupling coordination relationship between agricultural eco-efficiency and urbanization, it is crucial to consider food security, especially in a populous country like China. This paper focuses on 31 provinces in China as the research units, covering the time period from 2000 to 2020. Based on the concept of agricultural eco-efficiency, an evaluation index system was developed to include undesirable outputs (carbon emissions), and agricultural eco-efficiency scores were calculated using the SBM–DEA model. An urbanization evaluation index system, covering six dimensions and twelve indexes, was constructed. A comprehensive index of urbanization is measured using the entropy method. On this basis, a coupling coordination model was applied to quantify the relationship between agricultural eco-efficiency and urbanization at the provincial scale in China. The results showed that the agricultural eco-efficiency of all provincial units in China exhibited an overall trend of improvement. Average efficiency followed a spatial pattern of majority grain-consuming areas > grain production–consumption balance areas > majority grain-producing areas. The level of coupling between agricultural eco-efficiency and urbanization is generally low. Currently, no regions have reached the stage of synergy or high-level coupling. Most regions are currently in an antagonistic stage with a coupling degree of 0.3 < C ≤ 0.5. The classification of coupling coordination levels changed from four levels of “severe imbalance”, “moderate imbalance”, “mild imbalance”, and “primary coordination” to “moderate imbalance”, “mild imbalance”, “primary coordination”, and “intermediate coordination”. The level of “severe imbalance” disappeared, the level of “intermediate coordination” appeared, and the level of “mild imbalance” became the largest scale level. From the perspective of food security, the proportion of grain production in the categories of “primary coordination” and “intermediate coordination” was less than 10%, and these provinces never achieved self-sufficiency in food production. The proportion of grain production at the “mild imbalance” level reached 62.4%, while the per capita grain production at the “moderate imbalance” level reached 846.7 kg. Provinces with lower levels of coupling coordination have stronger food security capabilities. It can be observed that the weaker the coupling coordination between agricultural eco-efficiency and urbanization, the higher the food self-sufficiency. Based on the research results above, we discussed strategies to enhance agricultural eco-efficiency in majority grain-producing regions by focusing on technological progress and technical efficiency. Additionally, we analyzed approaches to achieve grain self-sufficiency in regions characterized by a high level of coordination between agricultural eco-efficiency and urbanization, considering both production and trade dimensions. Full article

Chickpeas hold significant nutritional and cultural importance, being a rich source of protein, fiber, and essential vitamins and minerals. They are a staple ingredient in various cuisines worldwide. Peeling chickpeas is considered a crucial pre-consumption operation due to the undesirability of peels for some uses. This study aimed to design, test, and evaluate a small chickpea seed peeling machine. The peeling prototype was designed in accordance with the chickpeas’ measured properties; the seeds’ moisture content was determined to be 6.96% (d.b.). The prototype was examined under four different levels of drum revolving speeds (100, 200, 300, and 400 rpm), and three different numbers of brush peeling rows. The prototype was tested with rotors of four, eight, and twelve rows of brushes. The evaluation of the chickpea peeling machine encompassed several parameters, including the machine’s throughput (kg/h), energy consumption (kW), broken seeds percentage (%), unpeeled seeds percentage (%), and peeling efficiency (%). The obtained results revealed that the peeling machine throughput (kg/h) exhibited an upward trend with increases in the rotation speed of the peeling drum. Meanwhile, the throughput decreased as the number of peeling brushes installed on the roller increased. The highest recorded productivity of 71.29 kg/h was achieved under the operational condition of 400 rpm and four peeling brush rows. At the same time, the peeling efficiency increased with the increase in both of peeling drum rotational speed and number of peeling brush rows. The highest peeling efficiency (97.2%) was recorded at the rotational speed of 400 rpm and twelve peeling brush rows. On the other hand, the lowest peeling efficiency (92.85%) was recorded at the lowest drum rotational speed (100 rpm) and number of peeling brush rows (4 rows). In the optimal operational condition, the machines achieved a throughput of 71.29 kg/h, resulting in a peeling cost of 0.001 USD per kilogram. This small-scale chickpea peeling machine is a suitable selection for small and medium producers. Full article

The wind sieve cleaner is widely used in the screening system of combine harvesters due to its compact structure and efficient screening capability. In order to study more deeply the feeding load distribution of the combine harvester and the influence of the airflow field on the clearing effect, a mechanical analysis method was adopted to analyze the dynamics of the material in the inclined airflow, and a kinetic model was established. At the same time, the motion state of the material in the airflow field was explored, and combined with the actual orthogonal test, the response surface model of factors and indicators was established. Experimental validation was carried out. It provides an important research foundation and theoretical basis for optimizing the structural parameters of the screening system and improving its operational performance. Full article

This study aimed to investigate dust and bacterial air contamination in a broiler house during different seasons. The study was carried out in commercial housing conditions during five weeks of the rearing cycle in summer and winter. The total dust concentration ranged from 1.90 to 4.50 mg/m³ in summer and from 2.80 to 5.10 mg/m³ in winter. The total bacterial count ranged from 2.85 × 10⁴ to 1.03 × 10⁵ CFU/m³ in summer and from 2.12 × 10⁴ to 2.28 × 10⁵ CFU/m³ in winter. The study results showed the dust concentration to be increased in winter as compared to summer, yielding a significant correlation (r = 0.602, p < 0.05) with a significantly higher airborne bacterial count in winter (p < 0.001). Furthermore, dust concentration showed significant correlations (p < 0.05) with air temperature (r = −0.418), relative humidity (r = 0.673), and broiler activity (r = 0.709), while bacterial count yielded significant correlations (p < 0.05) with air temperature (r = −0.756), relative humidity (r = 0.831), and airflow rate (r = 0.511). The results obtained in the study can prove useful in the field. Seasonal variability in dust and bacterial air contamination should be considered in the development of guidelines or standards of air quality in broiler housing and evaluation of the effectiveness of remedial strategies. Full article

As a result of the uneven growth of rice, unbalanced vibration of threshing drum caused by stalk entanglement in combine harvester is more and more severe. In order to reveal the influence of unbalanced excitation on the roller axis locus during rice threshing, the stability of threshing drum was studied. The dynamic signal test and analysis system are used to test the axial trajectory of threshing drum. At the same time, the influence of the unbalanced excitation caused by the axis winding on the axis trajectory is analyzed by the experimental results. Axis locus rules under no-load and threshing conditions are obtained. In order to simulate the axial and radial distribution of unbalanced excitation along the threshing drum, the counterweight was distributed on the threshing drum instead of the entangled stalk. Then, the definite effect of unbalanced excitation on the rotating stability of threshing drum is analyzed. Results show that the amplitude of stem winding along the grain drum is larger in the vertical direction and smaller in the horizontal direction when compared with the unloaded state under 200 g weight. It was found that the amplitude in both horizontal and vertical directions decreased after 400 g and 600 g counterweights were added, respectively, to simulate the radial distribution of stalk winding along the grain barrel. Finally, it can be seen that with the increase in the weight of the counterweight, the characteristics of the trajectory misalignment of the threshing cylinder axis become more and more obvious. This study can provide reference for reducing the unbalanced excitation signal of threshing drum and improving driving comfort. Full article

Okra (Abelmoschus esculentus L.) is a highly nutritious vegetable rich in vitamins, minerals, and bioactive compounds, including polyphenols, offering numerous health benefits. Despite its nutritional value, okra remains underutilized in Europe; however, its cultivation and popularity may rise in the future with increasing awareness of its advantages. In agricultural practices, beneficial soil microorganisms, such as arbuscular mycorrhizal fungi (AMF), Trichoderma spp., Streptomyces spp., and Aureobasidium spp., play crucial roles in promoting plant health, enhancing agricultural productivity together with improved crop nutritional value. This study aimed to investigate the effects of individual and combined inoculation on the polyphenol content of okra fruits, as analyzed by HPLC. Moreover, growth parameters and glutathione-S-transferase enzyme (GST) activities of okra leaves were also estimated. Tested microorganisms significantly increased the yield of okra plants except for A. pullulans strain DSM 14950 applied individually. All microorganisms led to increased GST enzyme activity of leaves, suggesting a general response to biotic impacts, with individual inoculation showing higher enzyme activity globally compared to combined treatments. According to the polyphenol compound analysis, the application of tested microorganisms held various but generally positive effects on it. Only the combined treatment of F. mosseae and Streptomyces strain K61 significantly increased the coumaric acid content, and the application of Aureobasidium strain DSM 14950 had a positive influence on the levels of quercetin and quercetin-3-diglucoside. Our preliminary results show how distinct polyphenolic compound contents can be selectively altered via precise inoculation with different beneficial microorganisms. Full article

Digital village construction is not only a vital component of the digital China strategy but also a crucial measure by which to realize common prosperity. This study theoretically elaborates the influence of digital village construction on the urban–rural income gap (URIG) and its mechanism and empirically tests it by using a panel fixed-effect model, a mediating-effect model, and a moderating-effect model based on the provincial data of major producing areas from 2011 to 2020. The results show that digital village construction can significantly narrow the URIG, and rural industry revitalization is a vital channel for digital village construction in driving the decline of the URIG. The construction of transportation infrastructure can significantly enhance the inhibition effect of digital village construction on the URIG. Moreover, there is a human capital threshold for the impact of digital village construction on the URIG; after crossing the threshold, digital village construction better suppresses the URIG. So, the government should increase the financial support and technical support for digital village construction, improving the rural production conditions and industrial development environment and establishing a rural digital talent cultivation mechanism so as to achieve the goal of common prosperity. Full article

Mechanized harvesting is the key technology to solving the high cost and low efficiency of manual harvesting, and the key to realizing mechanized harvesting lies in the accurate and fast identification and localization of targets. In this paper, a lightweight YOLOv5s model is improved for efficiently identifying grape fruits and stems. On the one hand, it improves the CSP module in YOLOv5s using the Ghost module, reducing model parameters through ghost feature maps and cost-effective linear operations. On the other hand, it replaces traditional convolutions with deep convolutions to further reduce the model’s computational load. The model is trained on datasets under different environments (normal light, low light, strong light, noise) to enhance the model’s generalization and robustness. The model is applied to the recognition of grape fruits and stems, and the experimental results show that the overall accuracy, recall rate, mAP, and F1 score of the model are 96.8%, 97.7%, 98.6%, and 97.2% respectively. The average detection time on a GPU is 4.5 ms, with a frame rate of 221 FPS, and the weight size generated during training is 5.8 MB. Compared to the original YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x models under the specific orchard environment of a grape greenhouse, the proposed model improves accuracy by 1%, decreases the recall rate by 0.2%, increases the F1 score by 0.4%, and maintains the same mAP. In terms of weight size, it is reduced by 61.1% compared to the original model, and is only 1.8% and 5.5% of the Faster-RCNN and SSD models, respectively. The FPS is increased by 43.5% compared to the original model, and is 11.05 times and 8.84 times that of the Faster-RCNN and SSD models, respectively. On a CPU, the average detection time is 23.9 ms, with a frame rate of 41.9 FPS, representing a 31% improvement over the original model. The test results demonstrate that the lightweight-improved YOLOv5s model proposed in the study, while maintaining accuracy, significantly reduces the model size, enhances recognition speed, and can provide fast and accurate identification and localization for robotic harvesting. Full article

Accurate estimation of soil water content (SWC) is crucial for effective irrigation management and maximizing crop yields. Although dielectric property-based SWC measurements are widely used, their accuracy is still affected by soil variability, soil–sensor contact, and other factors, making the development of convenient and accurate soil-specific calibration methods a major challenge. This study aims to propose a plate compression filling technique for soil-specific calibrations and to monitor the extent of soil biomass degradation using dielectric properties. Before and after biodegradation, dielectric measurements of quartz sand and silt loam were made at seven different water contents with three different filling techniques. A third-order polynomial fitting equation explaining the dependence of the dielectric constant on the volumetric water content was obtained using the least-squares method. The suggested plate compression filling method has a maximum mean bias error (MBE) of less than 0.5%, according to experimental results. Depending on the water content, silt loam’s dielectric characteristics change significantly before and after biodegradation. The best water content, measured in gravimetric units, to encourage the decomposition of biomass was discovered to be 24%. It has been demonstrated that the plate compression filling method serves as a simple, convenient, and accurate alternative to the uniform compaction method, while the dielectric method is a reliable indicator for evaluating biomass degradation. This exploration provides valuable insights into the complex relationship between SWC, biomass degradation, and soil dielectric properties. Full article

Effective scheduling of multiple agricultural machines in emergencies can reduce crop losses to a great extent. In this paper, cooperative scheduling based on deep reinforcement learning for multi-agricultural machines with deadlines is designed to minimize makespan. With the asymmetric transfer paths among farmlands, the problem of agricultural machinery scheduling under emergencies is modeled as an asymmetric multiple traveling salesman problem with time windows (AMTSPTW). With the popular encoder-decoder structure, heterogeneous feature fusion attention is designed in the encoder to integrate time windows and asymmetric transfer paths for more comprehensive and better feature extraction. Meanwhile, a path segmentation mask mechanism in the decoder is proposed to divide solutions efficiently by adding virtual depots to assign work to each agricultural machinery. Experimental results show that our proposal outperforms existing modified baselines for the studied problem. Especially, the measurements of computation ratio and makespan are improved by 26.7% and 21.9% on average, respectively. The computation time of our proposed strategy has a significant improvement over these comparisons. Meanwhile, our strategy has a better generalization for larger problems. Full article

The BTB (broad-complex, tramtrack, and bric-a-brac) domain, also known as the POZ (POX virus and zinc finger) domain, is a conserved protein–protein interaction domain present in various organisms. In this study, we conducted a genome-wide search to identify and characterize BTB genes in Solanum tuberosum. A total of 57 StBTBs were identified and analyzed for their physicochemical properties, chromosomal distribution, gene structure, conserved motifs, phylogenetic relationships, tissue-specific expression patterns, and responses to hormonal and stress treatments. We found that StBTBs were unevenly distributed across potato chromosomes and exhibited diverse gene structures and conserved motifs. Tissue-specific expression analysis revealed differential expression patterns across various potato tissues, implying their roles in plant growth and development. Furthermore, differential expression analysis under hormonal and stress treatments indicated the involvement of StBTBs in abiotic and biotic stress responses and hormone signaling pathways. Protein–protein interaction analysis identified potential interactions with ribosomal proteins, suggesting roles in translational regulation. Additionally, microRNA target site analysis revealed regulatory relationships between StBTBs and miRNAs. Our study provides a comprehensive understanding of the StBTB gene family in potato, laying the groundwork for further functional characterization and manipulation of these genes to improve stress tolerance and agricultural productivity in potato and related plant species. Full article

The study assesses the direct effects of climate change by 2060, including extreme events, on the productivity of regional crop farming and livestock in Greece, and the broader socio-economic effects on the agri-food and other sectors. Different approaches (i.e., agronomic models, statistical regression models, and equations linking thermal stress to livestock output) were combined to estimate the effects on productivity from changes in the average values of climatic parameters, and subsequently the direct economic effects from this long-term climate change. Recorded damages from extreme events together with climatic thresholds per event and crop were combined to estimate the direct economic effects of these extremes. The broader socio-economic effects were then estimated through input–output analysis. Under average levels of future extreme events, the total direct economic losses for Greek agriculture due to climate change will be significant, from EUR 437 million/year to EUR 1 billion/year. These losses approximately double when indirect effects on other sectors using agricultural products as inputs (e.g., food and beverage, hotels, and restaurants) are considered, and escalate further under a tenfold impact of extreme events. Losses in the GDP and employment are moderate at the national level, but significant in regions where the contribution of agriculture is high. Full article

Drought and salinity stresses significantly threaten global wheat productivity, limiting growth and reducing yields, thus endangering food security worldwide. These stresses disrupt physiological processes, impair photosynthesis, and hinder optimal growth and yield by diminishing water uptake, causing osmotic stress, ion toxicity, and oxidative stress. In response, various mitigation strategies have been explored, including breeding for stress-tolerant cultivars, improved irrigation techniques, and the application of exogenous osmoprotectants and soil amendments. Among these strategies, the emergence of rhizospheric and endophytic growth-promoting microorganisms has attracted significant attention. Therefore, a systematic review was undertaken to illustrate the role of endophytic bacteria in enhancing wheat tolerance to drought and salinity stresses. This review analyzes physiological mechanisms and research trends, identifies gaps, and discusses implications for sustainable agriculture. An analysis of the literature related to endophytic bacteria in wheat was conducted using databases of major publishers from 2004 to 2023. The review explores their mechanisms, such as phytohormone production and stress-responsive gene induction, emphasizing their contribution to plant growth and stress resilience. The current research trends indicate a growing interest in utilizing endophytic bacteria to mitigate these stresses in wheat cultivation, with studies focusing on understanding their physiological responses and interactions with wheat plants. Future research should concentrate on elucidating the role of endophytic bacteria in enhancing host plant tolerance to multiple stressors, as well as aspects like endophytic mechanism of action , endophytic lifestyle, and transmission pathways. Overall, endophytic bacteria offer promising avenues for sustainable agricultural practices, aiding in crop resilience and food security amid environmental challenges. Full article

Sustainable plant production requires less use of synthetic chemicals in plant nutrition and protection. Microbial products are among the most promising substitutes for chemicals. With the increasing popularity and availability of such products, it has become obligatory to use different microbes together. The effect of this has been tested in several studies, but their results have sometimes been contradictory depending on the microbial strains tested and the mode of application. We tested the effect of two commercially available antagonists and Funneliformis mosseae alone and in combination on tomato. Mycorrhizal treatment increased plant growth and yield, both alone and combined with the antagonists; however, mycorrhizal root colonization was not influenced by the antagonist. This treatment also led to a slight decrease in the occurrence of Trichoderma spp. on tomato roots but did not impede the colonization of roots by the applied Trichoderma strain. Our result confirmed that Trichoderma asperellum (T34) and Streptomyces griseoviridis (K61) can be safely combined with arbuscular mycorrhizal fungi (AMF), namely with F. mosseae. Full article

AGIs (agricultural geographical indicators) are effective quality signals that can improve market welfare, but few studies have investigated the impact of AGIs on economic development. To fill this gap, this paper explores the impact of AGIs on per capita GDP and its mechanisms, according to country-level data in China from 2000 to 2018. For every additional AGI in the country, GDP per capita increased by 0.2–0.4%. Our conclusion remained reliable after various robustness tests. These effects were more salient in western areas, the main grain-producing areas, and settled areas. AGIs related to aquatic environments, animal husbandry, and planting products promoted economic development most significantly. For these effects, encouraging an increase in agricultural value (improving the quantity and quality of products) and promoting the agglomeration of populations, capital, and enterprises in the agricultural sector were the main mechanisms. Full article

Soil quality decline can adversely affect ecosystem health and land productivity, with soil-dwelling mesofauna considered to potentially fulfill vital functions in accurately predicting these outcomes. However, the current state of research reveals a gap concerning the relationships between soil quality decline and soil-dwelling mesofauna in the Mollisols Region. For a more profound understanding of this issue, we conducted a comprehensive investigation of soil-dwelling mesofaunal communities in the different agricultural lands of the Mollisols Region. In this study, soil-dwelling mesofauna were collected, and 11 soil properties were determined following standard procedures, with soil quality levels quantified by utilizing soil quality index (SQI). Our results revealed that there was a gradient of soil quality across the different agricultural lands, which were divided into five levels, including very strong, strong, medium, weak, and very weak. Subsequently, this investigation provided empirical evidence that the decline in soil quality had implications for soil-dwelling mesofaunal communities in agricultural lands of the Mollisols region. A consistent decrease in the density of soil-dwelling mesofauna was observed with the decline of soil quality. In contrast, a greater richness was observed in areas with relatively weaker soil quality, suggesting that the consequences of soil quality decline on soil-dwelling mesofauna were not exclusively negative. Various taxa of soil-dwelling mesofauna exhibited varying degrees of response to the decline in soil quality. Oribatida was overwhelmingly dominant in the sampling fields with medium soil quality, and most Entomobryidae were found in agricultural lands with very weak soil quality. During soil quality decline, soil nutrients were observed to correlate positively with the density of soil-dwelling mesofauna. Overall, the outcomes of this investigation carry significance for comprehending how soil quality decline relates to soil-dwelling mesofauna, and can provide valuable ecological insights for formulating biodiversity guidelines targeted at preserving soil resources in the Mollisols region. Full article

The accurate assessment of peanut seed plumpness is crucial for optimizing peanut production and quality. The current method is mainly manual and visual inspection, which is very time-consuming and causes seed deterioration. A novel imaging technique is used to enhance the detection of peanut seed fullness using a non-destructive soft X-ray, which is suitable for the analysis of the surface or a thin layer of a material. The overall grayscale of the peanut is similar to the background, and the edge of the peanut seed is blurred. The inaccuracy of peanut overall and peanut seed segmentation leads to low accuracy of seed plumpness detection. To improve accuracy in detecting the fullness of peanut seeds, a seed plumpness detection method based on level set and multi-threshold segmentation was proposed for peanut images. Firstly, the level set algorithm is used to extract the overall contour of peanuts. Secondly, the obtained binary image is processed by morphology to obtain the peanut pods (the peanut overall). Then, the multi-threshold OTSU algorithm is used for threshold segmentation. The threshold is selected to extract the peanut seed part. Finally, morphology is used to complete the cavity to achieve the segmentation of the peanut seed. Compared with optimization algorithms, in the segmentation of the peanut pods, average random index (RI), global consistency error (GCE) and variation of information (VI) were increased by 10.12% and decreased by 0.53% and 24.11%, respectively. Compared with existing algorithms, in the segmentation of the peanut seed, the average RI, VI and GCE were increased by 18.32% and decreased by 9.14% and 6.11%, respectively. The proposed method is stable, accurate and can meet the requirements of peanut image plumpness detection. It provides a feasible technical means and reference for scientific experimental breeding and testing grading service pricing. Full article

This paper takes the frame as the research object and explores the vibration characteristics of the frame to address the vibration problem of a 1-MSD straw-crushing and residual film recycling machine in the field operation process, and an accurate identification of the modal parameters of the frame is carried out to solve the resonance problem of the machine, which can achieve cost reduction and increase income to a certain extent. The first six natural frequencies of the frame are extracted by finite element modal identification and modal tests, respectively. The rationality of the modal test results is verified using the comprehensive modal and frequency response confidences. The maximum frequency error of modal frequency results of the two methods is only 6.61%, which provides a theoretical basis for the optimal design of the frame. In order to further analyze the resonance problem of the machine, the external excitation frequency of the machine during normal operation in the field is solved and compared with the first six natural frequencies of the frame. The results show that the first natural frequency of the frame (18.89 Hz) is close to the external excitation generated by the stripping roller (16.67 Hz). The first natural frequency and the volume of the frame are set as the optimization objectives, and the optimal optimization scheme is obtained by using the Optistruct solver, sensitivity method, and grey correlation method. The results indicate the first-order natural frequency of the optimized frame is 21.89 Hz, an increase of 15.882%, which is much higher than the excitation frequency of 16.67 Hz, and resonance can be avoided. The corresponding frame volume is 9.975 × 10⁷ mm³, and the volume reduction is 3.46%; the optimized frame has good dynamic performance, which avoids the resonance of the machine and conforms to the lightweight design criteria of agricultural machinery structures. The research results can provide some theoretical reference for this kind of machine in solving the resonance problem and carrying out related vibration characteristics research. Full article

Both arbuscular mycorrhizal (AM) fungi and root hairs are crucial in facilitating plant uptake of phosphorus (P), while it is unclear whether and how they respond to varying P supplies. In order to explore how AM fungal colonization and root hair development are affected by substrate P supply, trifoliate orange (Poncirus trifoliata) seedlings were inoculated with AM fungus Rhizophagus intraradices and grown under low, moderate, and high P conditions; then, root hair morphological features and AM fungal colonization were measured. Following 120 days of AM fungal inoculation, root hair density, root hair length, AM fungal colonization rate, arbuscule colonization rate, and AM fungal colonization frequency all increased significantly under P-deficient conditions but decreased under high P conditions. Moreover, the colonization of AM fungi had a major impact on root hair formation by altering the expression of related genes and the growth of epidermal cells. The effect of AM fungi was dependent on P supply levels, as evidenced by the fact that root hair density and length increased at high P levels but decreased at low P levels. As a result, root hairs may serve as a preferential site for AM fungal colonization, and their morphology could influence the early stage of AM symbiosis establishment. Full article

Whether the stems and leaves of leaf-vegetable sweet potatoes can be listed ahead of schedule is related to the improvement in economic benefits for farmers, and the key to all of this is to implement the safe overwintering of potato seedlings under the premise of saving production costs. Only in this way can we truly seize the “market opportunity” and achieve the goals of cost saving and increasing economic benefit. In this study, the main leaf-vegetable sweet potato variety Fucai 18 was used as the material, and the L9(3⁴) orthogonal experiment was carried out in a simple solar greenhouse environment for two consecutive years from 2021 to 2022 and from 2022 to 2023, respectively. The effects of nine different combinations of factors on the above-ground and underground agronomic traits of overwintering sweet potato seedlings were studied under the conditions of four factors and three levels: planting density (a); different cutting seedlings (b); rooting agent concentration (c); and transplanting time (d). The methods of principal component analysis, membership function method, cluster analysis, grey correlation degree and stepwise regression analysis were used to evaluate the growth of overwintering seedlings, and try to screen out the key indicators that can be used to identify and evaluate the growth of overwintering sweet potato seedlings. Through range analysis, identify the optimal combination of four factors and three levels, and explore the main factors that have a significant impact on the key indicators for evaluating the growth of overwintering potato seedlings. The results indicate the following: (1) The use of simple sunlight greenhouse in Changsha area can achieve the safe overwintering of vegetable sweet potato seedlings. (2) Stem thickness, root length, and root diameter can be used as three key indicators for identifying and evaluating the growth potential of vegetable sweet potato overwintering seedlings. (3) Under four factors and three levels, the best combination was A3B3C1D1 (planting density of 250,000 plants/ha, stem tip core-plucking seedlings, rooting agent concentration of 50 mg/L, the first batch of transplanting time). (4) The transplanting time (D) is the main factor for the two key evaluation indicators of stem diameter and root diameter, while there is no significant difference in the three other factors. (5) Different cutting seedlings (B) are the main influencing factors for the key evaluation index of root length, while the other three factors have the following impact on root length: transplanting time (D) > rooting agent concentration (C) > planting density (A). The results of this study not only contribute to the construction of a safe overwintering cultivation technology system for vegetable sweet potato seedlings, but also provide a certain theoretical basis for the breeding of new cold-leaf-vegetable sweet potato varieties in the future. Full article

Increasing fruit crop production sustainability under climate change, particularly increasing temperatures, is a major challenge in modern agriculture. High temperatures affect apple fruit quality and decrease its color. Herein, we constructed an experimental field under temperature simulation to evaluate climate change mitigation strategies for apples. ‘Hongro’ apples were subjected to three treatments: (1) cultivation inside a vinyl house for heat treatment (heat induction), (2) cultivation under water irrigation (heat reduction), and (3) cultivation under normal atmospheric temperature (control). At harvest, the fruits of the heat treatment group exhibited poor coloration, with a lower gene expression and pigment accumulation than those of the water irrigation and control groups. Furthermore, the fruit quality of the heat treatment group decreased, with a lower soluble solid content (SSC) and titratable acidity (TA), and smaller fruits. Additionally, a higher fruit disorder (cracking and spots) ratio was observed in the heat treatment group than in the water irrigation and control groups. However, the fruits of the water irrigation group exhibited higher quality indexes (flesh firmness, SSC, and TA) and less cracking than those of the heat treatment and control groups. Heat reduction, including water irrigation, may be used for orchard management to prevent climate change-induced increasing temperatures. Full article

The percent canopy cover and health of winter wheat are important crop performance indicators. Thus, understanding how tillage management practices affect these indicators is beneficial for improving crop performance and consequently yield. The availability of high-resolution drone data with spectral characteristics provides an opportunity to examine the percent canopy cover and health of winter wheat in different tillage systems. This is because the use of drones provides real-time high spatial resolution and temporal images to effectively monitor winter wheat conditions throughout the growing season. Nonetheless, very limited studies have utilized drone data for assessing the percent canopy cover and health conditions of winter wheat for different tillage practices. This study aimed to examine the percent canopy cover and health of winter wheat in no-till and conventional tillage plots using a drone. We used the mean Normalized Difference Vegetation Index (NDVI) ± Standard Deviation (SD) (0.89 ± 0.04) of winter wheat for the growth stages of tillering, jointing, and boot/heading to generate the percent wheat canopy cover. The Normalized Difference Red-Edge (NDRE) produced for winter wheat at the middle and late growth stages was used as a proxy for wheat health condition. We found that the mean percentage canopy cover of winter wheat was about 4% higher in no-till compared to conventional tillage plots in most of the growing season. The mean NDRE ± standard error (SE) of winter wheat was about 0.44 ± 0.01 and 0.43 ± 0.01 for no-till and conventional tillage plots, respectively, during the mid- and late growth stages. There was no significant difference in either the percent canopy cover or health of winter wheat between no-till and conventional tillage plots. The results generated in this study could be used to support farmers’ decision-making process regarding tillage practices and wheat crop performance. Full article

Nitro-substituted neonicotinoid insecticides have been widely used until recently to control a range of important agricultural pests. Growing concerns about thiamethoxam’s toxicity to pollinators have led to its use being restricted or to it even being banned in some countries. Nevertheless, in Asia, Africa, Southeast Europe, and South America thiamethoxam is still used. Although thiamethoxam has been intensively studied all over the world, its dissipation dynamics have not been studied in depth. The subject of the present study was to (1) develop and validate a QuEChERS/LC-MS/MS protocol for the determination of thiamethoxam and its main metabolite clothianidin in samples of young oilseed rape plants with high chlorophyll content, and (2) make a comparison of the degradation behaviors of thiamethoxam and clothianidin in two crops of winter oilseed rape, cultivated on soils with different pH. For determination of thiamethoxam and clothianidin in plant material with high chlorophyll content, a QuEChERS/LC–MS/MS protocol enabling the detection of low levels of compound concentrations was developed. The proposed clean-up protocol provided recoveries within the range of 92–98% for the compounds under analysis. Precision, calculated as relative standard deviation, was below 20%. Satisfactory linearity of the method was obtained in the concentration range under analysis (0.001–1.0 mg kg⁻¹). Differences in degradation of both insecticides, depending on the physico-chemical properties of the soil, were observed. Thiamethoxam and clothianidin residues disappeared in plants very quickly, and they were not detected below the limit of quantitation in oilseed rape at the flowering stage. Full article

Using beneficial microorganisms, such as purple non-sulfur bacteria (PNSB), has shown enormous potential for improving plant growth and agricultural production. However, the full extent of their benefits and interactions with agricultural practices is yet to be fully understood. The present study aimed to investigate the use of PNSB in crop rotation practice, focusing on its impact on rice growth and yield. The experiment was conducted over two rice cropping seasons, with djulis grown between the rice as a rotation crop. The study shows that PNSB treatment increased the concentration of 5-aminolevulinic acid (5-ALA) in plants, indicating enhanced photosynthesis. Moreover, when combined with crop rotation, PNSB remarkably improved soil fertility. These combined benefits resulted in substantial increases in tiller numbers (163%), leaf chlorophyll content (13%), and lodging resistance (66%), compared to the untreated plants. The combined treatment also resulted in higher productive tillers per hill (112%), average grain per hill (65%), and grain fertility (26%). This led to increased grain yield (65%), shoot dry weight (15%), and harvest index (37%). The findings clearly suggest that the incorporation of PNSB in crop rotation strategies can significantly augment the growth and yield of rice crops. These insights, pivotal for sustainable rice cultivation, hold the potential to simultaneously tackle the pressing issues of global food security and climate change. Full article

(1) Background: The effective selection of hyperspectral feature bands is pivotal in monitoring the nutritional status of intricate alpine grasslands on the Qinghai–Tibet Plateau. The traditional methods often employ hierarchical screening of multiple feature indicators, but their universal applicability suffers due to the use of a consistent methodology across diverse environmental contexts. To remedy this, a backward feature elimination (BFE) selection method has been proposed to assess indicator importance and stability. (2) Methods: As research indicators, the crude protein (CP) and chlorophyll (Chl) contents in degraded grasslands on the Qinghai–Tibet Plateau were selected. The BFE method was integrated with partial least squares regression (PLS), random forest (RF) regression, and tree-based regression (TBR) to develop CP and Chl inversion models. The study delved into the significance and consistency of the forage quality indicator bands. Subsequently, a path analysis framework (PLS-PM) was constructed to analyze the influence of grassland community indicators on Spec_Chl and Spec_CP. (3) Results: The implementation of the BFE method notably enhanced the prediction accuracy, with ΔR²_RF-Chl = 56% and ΔR²_RF-CP = 57%. Notably, spectral bands at 535 nm and 2091 nm emerged as pivotal for CP prediction, while vegetation indices like the PRI and mNDVI were critical for Chl estimation. The goodness of fit for the PLS-PM stood at 0.70, indicating the positive impact of environmental factors such as grassland cover on Spec_Chl and Spec_CP prediction (r_Chl = 0.73, r_CP = 0.39). Spec_Chl reflected information pertaining to photosynthetic nitrogen associated with photosynthesis (r = 0.80). (4) Disscusion: Among the applied model methods, the BFE+RF method is excellent in periodically discarding variables with the smallest absolute coefficient values. This variable screening method not only significantly reduces data dimensionality, but also gives the best balance between model accuracy and variables, making it possible to significantly improve model prediction accuracy. In the PLS-PM analysis, it was shown that different coverage and different community structures and functions affect the estimation of Spec_CP and Spec_Chl. In addition, Spec_Chl has a positive effect on the estimation of Spec_CP (r = 0.80), indicating that chlorophyll does reflect photosynthetic nitrogen information related to photosynthesis, but it is still difficult to obtain non-photosynthetic and compound nitrogen information. (5) Conclusions: The application of the BFE + RF method to monitoring the nutritional status of complex alpine grasslands demonstrates feasibility. The BFE filtration process, focusing on importance and stability, bolsters the system’s generalizability, resilience, and versatility. A key research avenue for enhancing the precision of CP monitoring lies in extracting non-photosynthetic nitrogen information. Full article