Agriculture, Volume 14, Issue 2 (February 2024) – 167 articles

Due to factors such as a small amount of fertilizer application during rice topdressing and slow machine speed, the ordinary fertilizer discharge device fails to distribute the fertilizer uniformly and accurately as required, making it difficult to meet the needs of precise rice topdressing. This research focuses on the development of an offset spiral tooth fertilizer discharge device suitable for rice topdressing. The study analyzes the amount of fertilizer discharged in one cycle, the fertilizer force, and the motion of the fertilizer particles. In order to enhance the uniformity of the fertilizer discharge device at a low speed and small volume, the discrete element method is employed to conduct experimental research on the key structural parameters that affect the one-cycle amount of discharged fertilizer and the dynamics of the fertilizer discharge device. Through single-factor tests, it was found that the angle, height, number of spiral teeth, and diameter of the fertilizer discharge wheel are closely associated with the fertilizer discharge performance. To further investigate the impact of these four parameters on the fertilizer discharge performance, a regression combination test of the four factors is conducted based on the range optimized by the single-factor tests. A multi-objective mathematical model, considering the key parameters of fertilizer uniformity coefficient, one-cycle amount of fertilizer, and fertilizer discharge torque, is established at three speeds: 20, 55, and 90 rpm. The response surface method is utilized to analyze the influence of the interaction factors on the fertilizer discharge performance. The optimal combination of the key structural parameters was determined as follows: spiral tooth angle of 35.42°, tooth height of 9.02 mm, discharge wheel diameter of 57.43 mm, and tooth amount of 9.37. The bench test results of the device, using the optimal parameter combination and a fertilizer discharge speed of 0–90 rpm, were obtained for four commonly used rice fertilizers. The maximum variation coefficient of fertilizer discharge was found to be 10.42%. The one-cycle amount of fertilizer discharge was measured to be 19.82 ± 0.72 (A Kang), 17.20 ± 0.69 (Ba Tian), 20.34 ± 0.54 (Yaran), and 14.51 ± 0.44 (granular urea). The fertilizer discharge torque remained stable. These results indicate that the achieved optimization meets the precise fertilizer application requirements and can provide technical support for precise topdressing operations. Full article

In this study, the influence of genotype (G), environment (E), and their interaction (G × E) on the content of total free phenolic compounds (TPC) and the antioxidant capacity (AC) was investigated, using sixteen durum wheat genotypes cultivated under seven crop management systems in Mediterranean environments. Possible correlations between TPC and AC with protein content (PC) and vitreous kernel percentage (VKP) were examined. Gs that exhibited stability across diverse conditions were studied through a comprehensive exploration of G × E interaction using a GGE biplot, Pi, and 𝘒R. The results indicated significant impacts of E, G, and G × E on both TPC and AC. Across E, the mean values of G for TPC, ABTS (2’-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid), DPPH (2,2-diphenyl-1-picrylhydrazyl), and FRAP (ferric reducing antioxidant power) values were 48.8 mg Trolox equivalents (TE)/100 g, 121.3 mg TE/100 g, 23.0 mg TE/100 g, and 88.4 mg TE/100 g, respectively. E, subjected to splitting top-dressing N fertilization, consistently showed low values, while the late-sowing ones possessed high values. Organic crop management maintained a stable position in the middle across all measurements. The predominant influence was attributed to G × E, as indicated by the order G × E > E > G for ABTS, DPPH, and FRAP, while for TPC, it was E > G × E > G. For TPC, the superior Gs included G5, G7 and G10, for ABTS included G3, G5 and G7, and for protein included G1, G9, and G16. G7 and G5 had a high presence of frequency, with G7 being the closest genotype to the ideal for both TPC and ABTS. These results suggest that the sowing time, nitrogen fertilization, and application method significantly impact the various antioxidant properties of durum wheat. This study holds significant importance as it represents one of the few comprehensive explorations of the impact of various Es, Gs, and their interactions on the TPC and AC in durum wheat, with a special emphasis on crop management and superior Gs possessing stable and high TPC and AC among them, explored by GGE biplot, Pi and 𝘒R. Further experimentation, considering the effect of the cultivation year, is necessary, to establish more robust and stable conclusions. Full article

Wheat breeding heavily relies on the observation of various traits during the wheat growth process. Among all traits, wheat head density stands out as a particularly crucial characteristic. Despite the realization of high-throughput phenotypic data collection for wheat, the development of efficient and robust models for extracting traits from raw data remains a significant challenge. Numerous fully supervised target detection algorithms have been employed to address the wheat head detection problem. However, constrained by the exorbitant cost of dataset creation, especially the manual annotation cost, fully supervised target detection algorithms struggle to unleash their full potential. Semi-supervised training methods can leverage unlabeled data to enhance model performance, addressing the issue of insufficient labeled data. This paper introduces a one-stage anchor-based semi-supervised wheat head detector, named “Wheat Teacher”, which combines two semi-supervised methods, pseudo-labeling, and consistency regularization. Furthermore, two novel dynamic threshold components, Pseudo-label Dynamic Allocator and Loss Dynamic Threshold, are designed specifically for wheat head detection scenarios to allocate pseudo-labels and filter losses. We conducted detailed experiments on the largest wheat head public dataset, GWHD2021. Compared with various types of detectors, Wheat Teacher achieved a mAP0.5 of 92.8% with only 20% labeled data. This result surpassed the test outcomes of two fully supervised object detection models trained with 100% labeled data, and the difference with the other two fully supervised models trained with 100% labeled data was within 1%. Moreover, Wheat Teacher exhibits improvements of 2.1%, 3.6%, 5.1%, 37.7%, and 25.8% in mAP0.5 under different labeled data usage ratios of 20%, 10%, 5%, 2%, and 1%, respectively, validating the effectiveness of our semi-supervised approach. These experiments demonstrate the significant potential of Wheat Teacher in wheat head detection. Full article

Radix pseudostellariae is one of the well-known genuine medicinal herbs in Fujian province, China. However, the continuous cropping obstacles with respect to R. pseudostellariae have seriously affected the sustainable utilization of medicinal resources and the development of related industrial systems. The occurrence of continuous cropping obstacles is a comprehensive effect of multiple deteriorating biological and abiotic factors in the rhizosphere soil. Therefore, intensive ecological methods have been the key to abating such obstacles. In this study, four treatments were set up, i.e., fallow (RP-F), fallow + bacterial fertilizer (RP-F-BF), rice-paddy-upland rotation (RP-R), and rice-paddy-upland rotation + bacterial fertilizer (RP-R-BF), during the interval between two plantings of R. pseudostellariae, with a newly planted (NP) treatment as the control. The results show that the yield of R. pseudostellariae under the RP-F treatment decreased by 46.25% compared to the NP treatment. Compared with the RP-F treatment, the yields of the RP-F-BF, RP-R, and RP-R-BF treatments significantly increased by 14.11%, 27.79%, and 62.51%, respectively. The medicinal quality of R. pseudostellariae treated with RP-R-BF was superior to that achieved with the other treatments, with the total saponin and polysaccharide contents increasing by 8.54% and 27.23%, respectively, compared to the RP-F treatment. The ecological intensive treatment of RP-R-BF significantly increased the soil pH, content of organic matter, abundance of beneficial microbial populations, and soil enzyme activity, thus remediating the deteriorating environment of continuous cropping soil. On this basis, the ecological intensive treatment RP-R-BF significantly increased the activity of protective enzymes and the expression levels of genes related to disease and stress resistance in leaves and root tubers. Redundancy and Pearson correlation analyses indicated that rice-paddy-upland rotation improved the soil structure, promoted the growth of eutrophic r-strategy bacterial communities, enhanced compound oxidation and reduction, broke the relationship between the deteriorating environment and harmful biological factors, and eventually weakened the intensity of harmful factors. The subsequent application of bacterial fertilizer improved the beneficial biological and abiotic factors, activated various ecological functions of the soil, enhanced the ecological relationship between various biological and abiotic factors, and reduced the stress intensity of R. pseudostellariae, thereby improving its disease and stress resistance, and ultimately reflecting the recovery of yield and quality. The results indirectly prove that the intensive ecological amelioration of the soil environment was the main factor for the yield recovery of R. pseudostellariae under continuous cropping. Full article

To improve the operational efficiency of a hammer mill and delve into a high-efficiency, energy-saving grinding mechanism, the crucial parameters influencing the grinding of corn straw were identified as the spindle speed, hammer–sieve gap, and sieve pore diameter. According to the force analysis and kinematics analysis, the key factors affecting corn straw grinding were the spindle speed, the hammer–sieve gap, and the sieve pore diameter. The grinding process of corn straw was studied using computational fluid dynamics (CFDs) and the discrete element method (DEM) gas–solid coupling numerical simulation and experiment. The numerical simulation results showed that with the growth of time, the higher the spindle speed, the faster the bonds broke in each part, and the higher the grinding efficiency. When the energy loss of the hammer component was in the range of 985.6~1312.2 J, and the total collision force of the corn straw was greater than 47,032.5 N, the straw grinding effect was better, and the per kW·h yield was higher. The experimental results showed that the optimum combination of operating parameters was a spindle speed of 2625 r/min, a hammer-screen gap of 14 mm, and a sieve pore diameter of 8 mm. Finally, the CFD–DEM gas–solid coupling numerical simulation validation tests were performed based on the optimal combination of the operating parameters. The results showed that the energy loss of the hammer component was 1189.5 J, and the total collision force of the corn straw was 49,523.5 N, both of which were within the range of better results in terms of numerical simulation. Thus, the CFD–DEM gas–solid coupling numerical simulation could accurately predict the corn straw grinding process. This study provides a theoretical basis for improving a hammer mill’s key components and grinding performance. Meanwhile, the proposed gas–solid two-phase flow method provided theoretical references for other research in agricultural machinery. Full article

This investigation considered the effects of both internal and external excitation vibrations on the efficacy of the seed dispenser in a rice precision hole seeder. Through comprehensive field tests, we analyzed vibrational characteristics during direct seeder operations and established a vibration seeding test bed for systematic examination of these effects. Time-domain analysis of the vibration data revealed a predominantly vertical vibration direction, with notably higher levels in sandy loam soil compared to clay loam. A correlation was observed between increased engine size and rotary ploughing speeds, as well as forward speed and elevated vibration amplitudes. Frequency domain analysis pinpointed the primary vibration frequency of the machinery within the 0–170 Hz range, remaining consistent across different operating conditions. Crucially, bench test results indicated that seeding accuracy and dispersion were significantly influenced by vibration frequencies, particularly within the 70–130 Hz range, where a decrease in accuracy and increase in dispersion were noted. A regression model suggested a complex, non-linear relationship between seeding performance and vibration frequency. These insights highlight the necessity for a robust mechanism to effectively address these vibrational impacts. This study paves the way for enhancing the operational efficiency of the rice precision hole seeder, aiming to achieve the design goals of minimized vibrations in the paddy power chassis. Full article

Ethyl formate (EF), a naturally occurring fumigant, has attracted widespread attention owing to its low toxicity in mammals. Here, Direct Immersion Solid-Phase Microextraction (DI-SPME) was employed for sample preparation in mass spectrometry-based untargeted metabolomics to evaluate the effects on Tribolium castaneum (Herbst) strains with different levels of PH₃ resistance (sensitive, TC-S; moderately resistant, TC-M; strongly resistant, TC-SR) when exposed to a sub-lethal concentration (LC₃₀) of EF. The bioassay indicated that T. castaneum strains with varying PH₃ resistance levels did not confer cross-resistance to EF. A metabolomic analysis revealed that exposure to sublethal doses of EF significantly altered 23 metabolites in T. castaneum, including 2 that are unique to the species which remained unaffected by external conditions, while 11 compounds showed a strong response. A pathway topology analysis indicated that EF caused changes to several metabolic pathways, mainly involving fatty acids and their related metabolic pathways. This study showed that EF can induce highly similar metabolic responses in insects across varying levels of PH₃ resistance, suggesting that the mechanisms driving the toxicity of EF and PH₃ are distinct. These insights significantly extend our knowledge of the toxic mechanisms of EF and provide direct evidence for the efficacy of EF treatment for managing PH₃ resistance in insects. Full article

Remote sensing stands out as one of the most widely used operations in the field. In this research area, UAVs offer full coverage of large cultivation areas in a few minutes and provide orthomosaic images with valuable information based on multispectral cameras. Especially for orchards, it is helpful to isolate each tree and then calculate the preferred vegetation indices separately. Thus, tree detection and crown extraction is another important research area in the domain of Smart Farming. In this paper, we propose an innovative tree detection method based on machine learning, designed to isolate each individual tree in an orchard. First, we evaluate the effectiveness of Detectron2 and YOLOv8 object detection algorithms in identifying individual trees and generating corresponding masks. Both algorithms yield satisfactory results in cherry tree detection, with the best F1-Score up to 94.85%. In the second stage, we apply a method based on OTSU thresholding to improve the provided masks and precisely cover the crowns of the detected trees. The proposed method achieves 85.30% on IoU while Detectron2 gives 79.83% and YOLOv8 has 75.36%. Our work uses cherry trees, but it is easy to apply to any other tree species. We believe that our approach will be a key factor in enabling health monitoring for each individual tree. Full article

In response to the unclear impact of header vibration on cutting performance (stalk cutting quality and cutting energy consumption) during field operations of industrial hemp harvesters, this study utilized a vibration recorder to collect information on header vibration during the operation of industrial hemp harvesters. Through data processing, the dominant range for the resonant frequency and amplitude of the cutting platform is primarily concentrated between 5–45 Hz and 0–35 mm, respectively. Using numerical simulation techniques, a quadratic orthogonal rotation combination experiment was conducted with vibration frequency and amplitude as experimental factors and stalk cutting quality and cutting energy consumption as indicators. Regression equations were established to reveal the relationships between indicators and factors, elucidating the influence of each factor and its interactions on the indicators. Specifically, for the crack length indicator, the amplitude has a highly significant influence on the model, and there is a significant interaction effect between vibration frequency and amplitude on the model. As for the cutting energy consumption indicator, frequency and the interaction between frequency and amplitude significantly affect the model, while amplitude has an extremely significant impact on the model. Through comprehensive fuzzy evaluation, the optimal vibration parameter combination satisfying comprehensive cutting performance indicators was determined as a vibration frequency of 37.86 Hz and an amplitude of 5.34 mm. Furthermore, the reliability of the model has been further validated. This research can provide a reference for improving the field performance of industrial hemp harvesters. Full article

The digitalization of the agricultural industry is manifested through the active use of innovative technologies in all its areas. Agribusiness owners have to constantly improve their security to meet new challenges. In this context, the existing cyber risks of the agrarian industry were assessed and their classification by possible consequences, such as data theft or alteration, cyber terrorism, cyber warfare, software hacking or modification, the blocking of markets and transactions on them, was proposed. Cyber insurance is an effective tool for minimizing the likelihood of cyber incidents and for comprehensive post-incident support, with the involvement of cybersecurity specialists. An algorithm for cooperation between an agricultural company and an insurance company when concluding a cyber risk insurance contract is proposed, which takes into account the needs and wishes of insurers at each stage of the interaction. To assess the need to use cyber insurance in agriculture 4.0, a methodology has been developed to evaluate the regional characteristics of cybersecurity and the digitalization of agribusiness. The results of the study show a heterogeneous need for this tool in different regions of the world. Full article

A fast spraying speed, wide working area, and easy operation are the operational advantages of high-clearance boom sprayers. To address the issue of spray boom mechanical vibration affecting the spraying effect, a double-link trapezoidal boom suspension is designed for the 3WPYZ sprayer. This suspension can achieve passive vibration reduction, active balance, and ground profiling. The kinematic model of the boom suspension is established based on D’Alembert’s principle and the principle of multi-body dynamics, and the design factors affecting the stability of the boom are determined. Through orthogonal experimental design and virtual kinematics simulation, the influence of the boom length and orifice diameter of each part on the swing angle and the natural frequency of the boom suspension is investigated. Design-Expert 8.0.6 software is used to analyze and optimize the test results. The optimization results show that, when the connecting boom length L_AB is 265 mm, the inner boom suspension boom length L_AD is 840 mm, the outer boom suspension boom length L_BC is 1250 mm, and the throttle hole diameter d is 4 mm; the maximum swing angle of the boom suspension is reduced by 53.02%. In addition, the natural frequency of the boom is reduced from 1.3143 rad/s to 1.1826 rad/s, and the dynamic characteristic optimization effect is remarkable. The modal analysis results show that the first sixth-order vibration test frequency of the boom sprayer suspension designed in this paper meets the requirements and avoids the influence of external factors. Field tests show that, when the sprayer is excited by the environment at 3.5° to 4°, the boom suspension can reduce the vibration transmitted by the body to a reasonable range. The static analysis shows that the structural design of this study reduces the stress at the connection of the end boom suspension, the maximum displacement, and the maximum stress of the inner boom suspension. The test results of the dynamic characteristics of the implement are basically consistent with the virtual model simulation test results, thus achieving the optimization objectives. Full article

A novel deep learning model, DiffuCNN, is introduced in this paper, specifically designed for counting tobacco lesions in complex agricultural settings. By integrating advanced image processing techniques with deep learning methodologies, the model significantly enhances the accuracy of detecting tobacco lesions under low-resolution conditions. After detecting lesions, the grading of the disease severity is achieved through counting. The key features of DiffuCNN include a resolution enhancement module based on diffusion, an object detection network optimized through filter pruning, and the employment of the CentralSGD optimization algorithm. Experimental results demonstrate that DiffuCNN surpasses other models in precision, with respective values of 0.98 on precision, 0.96 on recall, 0.97 on accuracy, and 62 FPS. Particularly in counting tobacco lesions, DiffuCNN exhibits an exceptional performance, attributable to its efficient network architecture and advanced image processing techniques. The resolution enhancement module based on diffusion amplifies minute details and features in images, enabling the model to more effectively recognize and count tobacco lesions. Concurrently, filter pruning technology reduces the model’s parameter count and computational burden, enhancing the processing speed while retaining the capability to recognize key features. The application of the CentralSGD optimization algorithm further improves the model’s training efficiency and final performance. Moreover, an ablation study meticulously analyzes the contribution of each component within DiffuCNN. The results reveal that each component plays a crucial role in enhancing the model performance. The inclusion of the diffusion module significantly boosts the model’s precision and recall, highlighting the importance of optimizing at the model’s input end. The use of filter pruning and the CentralSGD optimization algorithm effectively elevates the model’s computational efficiency and detection accuracy. Full article

Treated livestock wastewater reuse for irrigation and straw return in arid regions have become common practices worldwide. However, many uncertainties still exist regarding the effects of the returning straw sizes on heavy metal accumulation in soil and plants under treated livestock wastewater irrigation. In a pot experiment growing maize and soybean, large (5–10 cm), medium (1–5 cm), and small (<1 cm) sizes of wheat straw were amended to assess the changes in Cu and Zn distribution in the rhizosphere, bulk soils, and plants. Groundwater and swine wastewater were used as irrigation water resources. The results showed that irrigation with swine wastewater significantly reduced soil pH and increased the concentration of soil-available potassium. Concentrations of Cu in soil were more sensitive to swine wastewater and straw application than those of Zn in soil. Swine wastewater irrigation increased the accumulation of Cu and Zn in plants with higher concentrations of Zn, while straw return tended to inhibit this increase, especially when a small size of straw was employed. In addition to providing a reference for revealing the interaction mechanism between swine wastewater irrigation and straw return, this study proposes feasible solutions to improve the efficiency of agricultural waste recycling and realize sustainable agricultural development. Full article

The escalating global population and climate change necessitate sustainable livestock production methods to meet rising food demand. Precision Livestock Farming (PLF) integrates information and communication technologies (ICT) to improve farming efficiency and animal health. Unlike traditional methods, PLF uses machine learning (ML) algorithms to analyze data in real time, providing valuable insights to decision makers. Dairy farming in diverse climates is challenging and requires well-designed structures to regulate internal environmental parameters. This study explores the application of the Facebook-developed Prophet algorithm to predict indoor temperatures in a dairy farm over a 72 h horizon. Exogenous variables sourced from the Open-Meteo platform improve the accuracy of the model. The paper details case study construction, data acquisition, preprocessing, and model training, highlighting the importance of seasonality in environmental variables. Model validation using key metrics shows consistent accuracy across different dates, as the mean absolute percentage error on daily base ranges from 1.71% to 2.62%. The results indicate excellent model performance, especially considering the operational context. The study concludes that black box models, such as the Prophet algorithm, are effective for predicting indoor temperatures in livestock buildings and provide valuable insights for environmental control and optimization in livestock production. Future research should explore gray box models that integrate physical building characteristics to improve predictive performance and HVAC system control. Full article

Hydrogen tractors are being developed, necessitating consideration of the variation in the center of gravity depending on the arrangement of components such as power packs and cooling modules that replace traditional engines. This study analyzes the effects of component arrangement on stability and rollover angle in hydrogen tractors through simulations and proposes an optimal configuration. Stability is evaluated by analyzing rollover angles in various directions with rotations around the tractor’s midpoint. Based on the analysis of rollover angles for Type 1, Type 2, and Type 3 hydrogen tractors, Type 2 demonstrates superior stability compared to the other types. Specifically, when comparing lateral rollover angles at 0° rotation, Type 2 exhibits a 2% increase over Type 3. Upon rotations at 90° and 180°, Type 2 consistently displays the highest rollover angles, with differences ranging from approximately 6% to 12% compared to the other types. These results indicate that Type 2, with its specific component arrangement, offers the most stable configuration among the three types of tractors. It is confirmed that the rollover angle changes based on component arrangement, with a lower center of gravity resulting in greater stability. These findings serve as a crucial foundation for enhancing stability in the future design and manufacturing phases of hydrogen tractors. Full article

In order to reduce ground drop loss during mechanical pepper picking and improve the net recovery rate, a drum snap finger picking device was designed. The picking device is mainly composed of a picking drum and auxiliary picking components; the picking finger arrangement was designed biomimetically and its structure and operating parameters were optimized by the DEM (discrete element method). According to the physical and mechanical characteristics of the pepper and the simplified three-dimensional model of the picking device, a virtual simulation model of the pepper-picking device was established using the EDEM software. Through simulation analysis and using the orthogonal test method, the main factors which affect the ground drop loss rate of pepper and their optimal parameter combination values were determined. The simulation results were verified by a pepper-picking field experiment. Orthogonal tests show that, when the picking drum speed ($V^{\prime }$) is 210 rpm, the pepper-feeding speed ($V^{″}$) is 1100 $\mathrm{m}\mathrm{m}·{\mathrm{s}}^{-1}$, the bending angle of each picking spring tooth (C) is 162°, and each group of circumferential fingers has rows, the picking device has a good picking effect. At this time, the ground drop loss rates in both the simulation and field test were 7.50% and 7.85%, respectively, and the drop error was only 4.46%, which was within the allowable range. The design form and parameter optimization simulation method in this paper provide an important reference for the design and optimization of pepper-harvesting machinery. Full article

A reasonable fertilization rate and appropriate irrigation technology can lead to the green development of greenhouse tomatoes. The purpose of this study was to explore suitable irrigation technology for greenhouse tomatoes and the appropriate application rate of the soluble organic fertilizer and inorganic fertilizer combination. In 2021 and 2022, the effects of different irrigation techniques and fertilization treatments on tomato plant growth, fruit quality, yield, and efficiency were studied. The irrigation techniques in this study were drip and Moistube irrigation, and there were seven types of fertilization treatment, namely, no fertilization treatment (CK); low-volume (T1, 330 kg/hm²), medium-volume (T2, 660 kg/hm²), and high-volume inorganic fertilizer treatments (T3, 990 kg/hm²); and three inorganic fertilizer treatments of low-volume inorganic fertilizer (T1, 330 kg/hm²) combined with low-volume (F1, T1 + 75 kg/hm²), medium-volume (F2, T1 + 225 kg/hm²), and high-volume (F3, T1 + 375 kg/hm²) organic fertilizer. A total of 14 experimental treatments were implemented for irrigation and fertilization. The results of the two-year experiment show that the growth effect on the height, stem diameter, and leaf area index of tomato plants was the best using the treatment of low-concentration inorganic fertilizer combined with medium-concentration organic fertilizer with Moistube irrigation and drip irrigation. Using the two irrigation methods, the application of soluble organic fertilizer increased the yield and improved the fruit quality of the tomato. The maximum yield increased by 28.52%, the soluble sugar content increased by 14.49%, the vitamin C content increased by 45.04%, and the lycopene increased by 18.79%. The entropy-weight TOPSIS model was used to comprehensively evaluate 14 evaluation objects with different irrigation methods and fertilization treatments. The results of the two-year experiment show that the best fertilization treatment under Moistube irrigation and drip irrigation conditions was low-concentration inorganic fertilizer combined with medium-concentration soluble organic fertilizer, which was combined with the best fertilization treatment, and the most suitable irrigation method for greenhouse tomato cultivation in the Loess Plateau was Moistube irrigation. The results of this study also provide practical experience and theoretical support for adaptive irrigation and the integrated management of water and fertilizer. Full article

Improving the performance of the threshing process is of utmost importance in enhancing the quality of sunflower seeds and minimizing power consumption in sunflower production. In this study, we developed a modified sunflower threshing machine by incorporating two types of threshing rotors, namely the angled rasp bar rotor and the tine bar rotor, as compared to the round bar rotor. The performance of these rotors was evaluated under various rotational speeds (150, 200, 250, and 300 rpm) and concave clearances (10, 15, and 20 mm). The evaluation parameters included machine throughput, the specific energy of threshing, the percentage of damaged seeds, the percentage of unthreshed seeds, and threshing efficiency. The results indicate that the specific energy decreased with an increase in rotor speed and a decrease in concave clearance, with the tine bar rotor exhibiting the lowest values. Threshing efficiency showed an increasing trend with higher rotor speeds and reduced concave clearance. The modifications made to the rotor design resulted in an enhanced threshing efficiency, with an improvement from 96.30% to 97.93% achieved at a rotor revolving speed of 300 rpm and a concave clearance of 10 mm. Moreover, the specific energy consumption reduced from 9.65 kW·h/ton to 5.09 kW·h/ton under the same operational conditions. These findings highlight the efficacy of the novel rotor design modifications in optimizing the performance of the stationary sunflower threshing machine, leading to improved efficiency and reduced energy consumption in sunflower seed threshing operations. Given its performance characteristics, this machine exhibits potential suitability for sunflower farms of small to medium scale. Full article

For cost-sensitive Chinese solar greenhouses (CSGs) with an uneven spatial distribution in temperature and humidity, there is a lack of effective strategies for sensor configuration that can reduce sensor usage while monitoring the microclimate precisely. A configuration strategy for integrated temperature–humidity sensors (THSs) based on the improved weighted Hilbert–Schmidt independence criterion (HSIC) is proposed in this paper. The data independence of the THSs in different sites was analyzed based on the improved HSIC, and the selection priority of the THSs was ranked based on the weighted independence of temperature and humidity. Then, according to different cost constraints and monitoring requirements, suitable THSs could be selected sequentially and constitute the monitoring solution. Compared with the original monitoring solution containing twenty-two THSs, the optimized solution used only four THSs (S6, S9 and H6, H5) under strict cost constraints, with a maximum RMSE of the temperature and relative humidity of 0.6 °C and 2.30%, as well as a maximum information gain rate (IGR) of 9.47% and 10.0%. If higher monitoring precision is required, we can increase the THS usage with a greater budget. The optimized solution with six THSs (S6, S9, S8 and H6, H5, H2) could further reduce the maximum RMSE of the temperature and relative humidity to 0.33 °C and 1.10% and the IGR to 6.9% and 8.7%. This indicated that the proposed strategy could use much fewer THSs to achieve accurate and comprehensive monitoring, which would provide efficient and low-cost solutions for CSG microclimate monitoring. Full article

To address the lack of available information on the soil physical conditions suitable for rapeseed blanket-shaped seedling transplanting, as well as the lack of protocols for the optimisation of soil tillage components in the utilisation of an integrated rapeseed blanket seedling combined transplanter, the physical parameters of different soil conditions and their impact on the growth of rapeseed after transplanting were investigated in this study. The aim was to determine the suitable soil physical parameters for rapeseed blanket-shaped seedling transplanting. First, the changes in soil firmness, soil bulk density, and soil moisture content during the installation of the rapeseed blanket seedling combined transplanter were tested and analysed, providing preliminary data for subsequent research. Using the variables of soil firmness and soil moisture content in the micro-environment around the roots and stems (30–50 mm) after rapeseed seedling transplantation and indicators such as the survival rate, root diameter, seedling height, and dry weight, an experiment on the growth of rapeseed blanket-shaped seedlings was conducted based on the furrow cutting transplanting principle. The results indicated that during the initial stage of rapeseed transplanting, the soil moisture content significantly influenced the vitality of the rapeseed plants. Under a high soil moisture content, the typically lengthy seedling period was shortened, and the effect on vitality was good, with minimal influence from the soil firmness. After seedling establishment, the rapeseed growth was significantly affected by the soil firmness. When the soil moisture content was less than 20%, increasing the soil firmness to 500 kPa was beneficial for moisture retention and rapeseed seedling growth. At a soil moisture content ranging from 20 to 25%, a soil firmness of 400 kPa was most suitable for both rapeseed vitality and late-stage growth. When the soil moisture content exceeded 25%, reducing the soil firmness to 300 kPa was beneficial for rapeseed growth, as an excessively high moisture content may lead to soil compaction, affecting seedling development. This study provides a theoretical basis for optimizing the design of soil tillage components in the application of an integrated rapeseed blanket seedling combined transplanter and for the high-yield management of rapeseed after transplanting. Full article

Yangchun City, a typical polymetallic ore distribution area in Guangdong Province (China), was selected as the research region to study the content, distribution, source, and possible impacts of heavy metals (HMs) (Arsenic: As; Cadmium: Cd; Chromium: Cr; Copper: Cu; Mercury: Hg; Nickel: Ni; Lead: Pb; and Zinc: Zn) on the farmland soil of this City. According to our findings, the spatial distribution of HMs in Yangchun City shows higher concentrations in the north and southeast and lower in the west and other regions. Metal content in some sampled sites of the agricultural land exceeded the soil pollution risk screening values, particularly As (7.5%), Cd (12%), Cu (4%), Hg (14.5%), and Pb (3%). Additionally, the average content of As, Cu, Cd, Pb, Hg, and Zn from the studied areas surpassed the soil background value of Guangdong Province for all metals. The absolute principal component score-multiple linear regression (APCS-MLR) was used to identify potential sources of HMs in the soil samples. There are three potential sources identified by the model: traffic emissions, natural sources, and agricultural activities, accounting for 28.16%, 16.68%, and 14.42%, respectively. Based on the ecological risk assessment, the potential ecological risk ($E_r^i$ = 310.77), Nemero pollution index (PN = 2.27), and multiple possible effect concentration quality (mPECQs = 0.23) indicated that the extent of heavy metal pollution in the soil samples was moderate. Three sources were identified: traffic emissions, natural sources, and agricultural activities. We suggest that by combining the above results, a monitoring and early warning system focused on Cd and Hg can be established. The system could utilize geographic information systems and remote sensing technologies to achieve dynamic monitoring and prediction of pollution. Regular testing of soils and sustainable management practices are also recommended to control and remediate contamination. Full article

To enhance the utilization of seed-used watermelon peel and mitigate environmental pollution, a hammer-blade seed-used watermelon peel crusher was designed and manufactured, and its structure and working parameters were optimized. Initially, the seed-used watermelon peel crusher and seed-used watermelon peel model were constructed, and the model’s parameters were calibrated. Subsequently, the discrete element method (EDEM2022) was employed to investigate the effects of spindle speed (MSS), the number of hammers (NCB), and feeding volume (FQ) on the pulverizing process. Multivariate nonlinear regression prediction models were developed for the percentage of pulverized particle size less than 8 mm (P_sv), pulverizing efficiency (G_e), and power density (P_pd), followed by the analysis of influencing factors and prediction models using ANOVA. The multiobjective optimization of the prediction model utilizing the improved hybrid metacellular genetic algorithm CellDE resulted in solutions of 90.02%, 89.57%, and 8.35 × 10⁻³ t/(h-kw) for P_sv-opt, G_e-opt, and P_pd-opt, respectively. The corresponding optimal interaction values of MSS, NCB, and FQ were determined to be 1500 r/min, 108, and 150 kg/min. Finally, a prototype test was conducted by combining the optimal factor interaction values, yielding statistically calculated values of 96.63%, 92.37%, and 7.76 × 10⁻³ t/(h-kw) for P_sv-pr, G_e-pr, and P_pd-pr, respectively. The results indicate that the optimized values of P_sv-opt, G_e-opt, and P_pd-opt models have an error of less than 8% compared to the statistically calculated values of the prototype test and outperform the values of P_sv-ori, G_e-ori, and P_pd-ori obtained under the original parameters. Full article

Fusarium oxysporum f. sp. lactucae is one of the most aggressive baby-lettuce soilborne pathogens. The application of Trichoderma spp. as biocontrol agents can minimize fungicide treatments and their effective targeted use can be enhanced by support of digital technologies. In this work, two Trichoderma harzianum strains achieved 40–50% inhibition of pathogen radial growth in vitro. Their effectiveness in vivo was surveyed by assessing disease incidence and severity and acquiring hyperspectral and thermal features of the canopies being treated. Infected plants showed a reduced light absorption in the green and near-red regions over time, reflecting the disease progression. In contrast, Trichoderma-treated plant reflectance signatures, even in the presence of the pathogen, converged towards the healthy control values. Seventeen vegetation indices were selected to follow disease progression. The thermographic data were informative in the middle–late stages of disease (15 days post-infection) when symptoms were already visible. A machine-learning model based on hyperspectral data enabled the early detection of the wilting starting from 6 days post-infection, and three different spectral regions sensitive to baby-lettuce wilting (470–490 nm, 740–750 nm, and 920–940 nm) were identified. The obtained results pioneer an effective AI-based decision support system (DSS) for crop monitoring and biocontrol-based management. Full article

Acquiring phenotypic data from livestock constitutes a crucial yet cumbersome phase in the breeding process. Traditionally, obtaining livestock phenotypic data primarily involves manual, on-body measurement methods. This approach not only requires extensive labor but also induces stress on animals, which leads to potential economic losses. Presently, the integration of next-generation Artificial Intelligence (AI), visual processing, intelligent sensing, multimodal fusion processing, and robotic technology is increasingly prevalent in livestock farming. The advantages of these technologies lie in their rapidity and efficiency, coupled with their capability to acquire livestock data in a non-contact manner. Based on this, we provide a comprehensive summary and analysis of the primary advanced technologies employed in the non-contact acquisition of livestock phenotypic data. This review focuses on visual and AI-related techniques, including 3D reconstruction technology, body dimension acquisition techniques, and live animal weight estimation. We introduce the development of livestock 3D reconstruction technology and compare the methods of obtaining 3D point cloud data of livestock through RGB cameras, laser scanning, and 3D cameras. Subsequently, we explore body size calculation methods and compare the advantages and disadvantages of RGB image calculation methods and 3D point cloud body size calculation methods. Furthermore, we also compare and analyze weight estimation methods of linear regression and neural networks. Finally, we discuss the challenges and future trends of non-contact livestock phenotypic data acquisition. Through emerging technologies like next-generation AI and computer vision, the acquisition, analysis, and management of livestock phenotypic data are poised for rapid advancement. Full article

Sulfur dioxide (SO₂) fumigation was evaluated for efficacy against western flower thrips (Frankliniella occidentalis) and phytotoxicity to four select fresh fruits and vegetables. Western flower thrips were found to be very susceptible to SO₂ fumigation. Fumigations with 0.3 and 0.5% SO₂ for 60 and 30 min, respectively, at a low temperature of 5 °C achieved 100% thrips mortality. Broccoli, bell peppers, apples, and navel oranges with thrips were subjected to 30 min fumigation with 0.3–0.5% SO₂ to verify efficacy and determine potential phytotoxicity. The fumigation resulted in complete control of thrips. Its effects on visual quality of fresh produce varied. The fumigation caused severe discoloration of broccoli. However, the treatment did not have significant effects on the color of other products. No negative impact on visual appearance of bell peppers and navel oranges was observed. However, it caused darkened lenticels on green apples and, therefore, may potentially degrade apple postharvest quality. The lack of phytotoxicity of SO₂ fumigation is likely due to well-developed wax layers on those fresh products. The results of the study suggest that SO₂ fumigation has good potential to be used safely and effectively against sensitive pests on select fresh fruit and vegetables including peppers and citrus fruits. Full article

Salinity is an obstacle to global agriculture, as it affects plant growth and development. Chitosan (CTS) has been suggested as a plant growth regulator to alleviate environmental stresses. In this study, the morphological and biochemical responses of chitosan application (75 mg L⁻¹) on maize seedling growth under salt stress (150 mM) were conducted with a hydroponic experiment. The results exhibited that CTS application effectively recovered salt-inhibited biomass accumulation and root architecture by increasing chlorophyll content and photosynthetic assimilation and reducing sodium content in shoots and roots by 25.42% and 5.12% compared with NaCl treatment. Moreover, salt-induced oxidative stress was alleviated by CTS application by increasing the activities of antioxidant enzymes of superoxide dismutase, catalase, ascorbate peroxidase, peroxidase and content of ascorbate. Correlation analysis and partial least squares (PLS) analysis revealed that root morphology and ascorbate play key roles for maize seedlings in response to salt stress. Based on these results, CTS application is recommended as an effective approach to enhance the tolerance of maize seedlings under salt stress. Full article

The accurate identification of citrus fruits is important for fruit yield estimation in complex citrus orchards. In this study, the YOLOv7-tiny-BVP network is constructed based on the YOLOv7-tiny network, with citrus fruits as the research object. This network introduces a BiFormer bilevel routing attention mechanism, which replaces regular convolution with GSConv, adds the VoVGSCSP module to the neck network, and replaces the simplified efficient layer aggregation network (ELAN) with partial convolution (PConv) in the backbone network. The improved model significantly reduces the number of model parameters and the model inference time, while maintaining the network’s high recognition rate for citrus fruits. The results showed that the fruit recognition accuracy of the modified model was 97.9% on the test dataset. Compared with the YOLOv7-tiny, the number of parameters and the size of the improved network were reduced by 38.47% and 4.6 MB, respectively. Moreover, the recognition accuracy, frames per second (FPS), and F1 score improved by 0.9, 2.02, and 1%, respectively. The network model proposed in this paper has an accuracy of 97.9% even after the parameters are reduced by 38.47%, and the model size is only 7.7 MB, which provides a new idea for the development of a lightweight target detection model. Full article

Soil salinization has become one of the major abiotic stresses limiting agricultural production globally. The full utilization of coastal saline-alkali land is of great significance for agricultural development. Among them, fertilizer management and planting density are crucial for promoting crop growth and productivity in saline soils. Field experiments were conducted to study the effects of different nitrogen application rates and planting densities on the growth, yield, and quality of alfalfa. Using alfalfa variety WL919 as the experimental material, three seeding rates of 15.0 kg·ha⁻¹ (D1), 30.0 kg·ha⁻¹ (D2), and 45.0 kg·ha⁻¹ (D3) as well as three nitrogen application rates of 150.0 kg·ha⁻¹ (N1), 225.0 kg·ha⁻¹ (N2), and 300.0 kg·ha⁻¹ (N3) were set. The results showed that under the same density, different nitrogen application rates had a positive impact on the agronomic traits and yield of alfalfa on saline-alkali land. Physiological and biochemical properties (chlorophyll and sucrose) increased with increasing nitrogen application, and (starch) increased initially and then decreased with increasing nitrogen application. Forage quality attributes (crude protein and crude ash) had a significant impact, while crude fat had no significant effect. Under the same nitrogen application, the yield of alfalfa increased with increasing density but then decreased after reaching a peak, while other traits initially increased and then decreased. In conclusion, the nitrogen fertilizer was superior in promoting alfalfa growth, biomass yield, and forage yield, while planting density was more suitable at D2. Although both D2N2 and D2N3 treatments were superior to others, considering economic benefits and environmental factors, it is recommended to use D2N2 as the appropriate treatment. Full article

The absorption of microplastics (MPs; size < 5 mm) by plants has garnered increasing global attention owing to its potential implications for food safety. However, the extent to which leafy vegetables can absorb large amounts of MPs, particularly those > 1 μm, remains insufficiently demonstrated. To address this gap in knowledge, we conducted water culture experiments using water spinach (Ipomoea aquatica F.) as a model plant. The roots of water spinach were exposed to a mixed solution that contained fluorescently labeled polystyrene (PS) beads with particle sizes of 200 nm and 1 μm for 10 d. We utilized laser confocal scanning microscopy and scanning electron microscopy to record the absorption, migration, and patterns of accumulation of these large particle sizes of MPs within water spinach. Our findings revealed that micron-sized PS beads were absorbed by the roots in the presence of submicron PS beads and subsequently transported through the exosomes to accumulate to significant levels in the leaves. Short-term hydroponic experiments further indicated that high concentrations of PS bead solutions significantly inhibited the growth of water spinach owing to their large specific surface area that hindered the uptake of water and nutrients by the roots. In conclusion, both sizes of PS beads were found to be absorbed by water spinach, thereby increasing the risk associated with direct human consumption of microplastics in fruits and vegetables. This study provides valuable scientific insights to assess the pollution risks related to fruits and vegetables, as well as ensuring vegetable safety. Full article

In the context of global food security and the pursuit of sustainable agricultural development, fostering synergistic innovation in the seed industry is of strategic importance. However, the collaborative innovation process between seed companies, research institutions, and governments is fraught with challenges due to information asymmetry and bounded rationality within the research and development phase. This paper establishes a multi-agent evolutionary game framework, taking the breeding of salt-tolerant rice as a case study. This study, grounded in the theories of information asymmetry and bounded rationality, constructs a two-party evolutionary game model for the interaction between enterprises and research institutions under market mechanisms. It further extends this model to include government participation, forming a three-party evolutionary game model. The aim is to uncover the evolutionary trends in collaborative behavior under various policy interventions and to understand how governments can foster collaborative innovation in salt-tolerant rice breeding through policy measures. To integrate the impact of historical decisions on the evolution of collaborative innovation, this research employs a delay differential equation (DDE) algorithm that takes historical lags into account within the numerical simulation. The stability analysis and numerical simulation using the DDE algorithm reveal the risk of market failure within the collaborative innovation system for salt-tolerant rice breeding operating under market mechanisms. Government involvement can mitigate this risk by adjusting incentive and restraint mechanisms to promote the system’s stability and efficiency. Simulation results further identify that the initial willingness to participate, the coefficient for the distribution of benefits, the coefficient for cost sharing, and the government’s punitive and incentivizing intensities are crucial factors affecting the stability of collaborative innovation. Based on these findings, the study suggests a series of policy recommendations including enhancing the initial motivation for participation in collaborative innovation, refining mechanisms for benefit distribution and cost sharing, strengthening regulatory compliance systems, constructing incentive frameworks, and encouraging information sharing and technology exchange. These strategies aim to establish a healthy and effective ecosystem for collaborative innovation in salt-tolerant rice breeding. While this research uses salt-tolerant rice breeding as a case study, the proposed cooperative mechanisms and policy suggestions have universal applicability in various agricultural science and technology innovation scenarios, especially when research meets widespread social needs but lacks commercial profit drivers, underscoring the essential role of government incentives and support. Consequently, this research not only contributes a new perspective to the application of evolutionary game theory in agricultural science and technology innovation but also offers empirical backing for policymakers in advancing similar collaborative innovation endeavors. Full article