Biosystems Engineering最新文献

{"title":"An effective unsupervised domain adaptation for in-field potato disease recognition","authors":"Xueze Gao ,&nbsp;Quan Feng ,&nbsp;Shuzhi Wang ,&nbsp;Jianhua Zhang ,&nbsp;Sen Yang","doi":"10.1016/j.biosystemseng.2024.10.005","DOIUrl":"10.1016/j.biosystemseng.2024.10.005","url":null,"abstract":"<div><div>Accurate disease recognition through computer vision is crucial for the intelligent management of potato production. Popular data-driven classification methods face challenges including limited labelled data and poor model portability. Unsupervised Domain Adaptation (UDA) addresses these challenges with a novel learning strategy. However, the complex field environment introduces a significant domain shift problem due to varying conditions. Existing UDA methods usually concentrate on aligning global data distribution and employ a single structure for disease feature extraction, thereby limiting their efficacy in true field environment. To tackle this challenge of potato disease recognition, the Multi-Representation Adaptive Network (MRSAN) based on subdomain alignment is presented. MRSAN effectively aligns feature distributions across diverse data by minimising distribution differences among relevant subdomains. Simultaneously, the multi-representation extraction method captures finer details from various perspectives in the disease images. The combination of these two approaches efficiently mitigates the adverse effects caused by various interference factors in field environment. Based on the acquisition conditions of light variation and disease progression, two field potato disease image datasets are created, containing five and six kinds of potato leaf disease, respectively. Extensive transfer experiments are conducted on the two datasets. MRSAN achieves average classification accuracies of 87.03% and 80.06% on the datasets for the corresponding transfer tasks, outperforming the other compared methods. This not only validates the effectiveness of MRSAN but also demonstrates its robust ability to generalise across changes in regard to light variation and disease progression.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 267-282"},"PeriodicalIF":4.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Injury mechanisms in high-speed transplanting of over aged rice seedlings","authors":"Tingjue Wang,&nbsp;Menghao Shi,&nbsp;Dongdong Xi,&nbsp;Dongdong Sun,&nbsp;Fuming Kuang,&nbsp;Wei Xiong,&nbsp;Shun Zhang,&nbsp;Dequan Zhu","doi":"10.1016/j.biosystemseng.2024.10.006","DOIUrl":"10.1016/j.biosystemseng.2024.10.006","url":null,"abstract":"<div><div>The mechanical transplanting of over aged seedlings (OAS) of rice poses several challenges, including seedling mortality and a significant delay in the greening period, which severely restrict yield. The causes of these issues remain unknown. Through theoretical analysis, mechanical tests, bench tests, and growth experiments were conducted to explore the reasons for seedling mortality and the significant delay in the greening period from the perspectives of seedlings, transplanting machines, and post-transplant growth. The results indicated that OAS transplanting causes combined root and stem injuries. For 40-day-old seedlings, the energy required for stem elasto-plastic deformation ranged from 1.37 to 7.19 N mm. Within this deformation range, the stem sustains internal injury but is not considered as injured seedling. The main factors influencing stem injury were the stem's major axis length and elastic modulus, whereas root injury was primarily affected by root diameter. Root and stem injuries significantly inhibited seedling growth, as demonstrated by significant structural changes in the stem 3 days post-transplantation, along with partial seedling mortality. New roots emerged only 9 days post-transplantation, and the heart leaf growth rate and SPAD value at 12 days were only 49% and 77% those of uninjured transplanted seedlings, respectively. Based on these findings, it was concluded that the seedling mortality and significant delay in the greening period observed in OAS transplantation are due to inhibited nutrient absorption and transport, caused by stem elasto-plastic deformation and weakened root vitality. These results may serve as a basis for improving transplanting machine design and optimising rice cultivation practices.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 142-155"},"PeriodicalIF":4.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of rice debranning mechanism based on tribological behaviour between rice grains","authors":"Jiaming Fei ,&nbsp;Ze Sun ,&nbsp;Dan Zhao ,&nbsp;Anqi Li ,&nbsp;Fuguo Jia ,&nbsp;Yanlong Han ,&nbsp;Hao Li ,&nbsp;Shouyu Ji ,&nbsp;Zhuozhuang Li ,&nbsp;Wenyu Feng","doi":"10.1016/j.biosystemseng.2024.10.007","DOIUrl":"10.1016/j.biosystemseng.2024.10.007","url":null,"abstract":"<div><div>Frictional debranning between rice grains is a fragile and energy-consuming process. Understanding the mechanism of this frictional debranning is the key to achieving moderate debranning, yet the mechanisms involved remain poorly understood. In this work, the mechanism of rice grain debranning was investigated through rice milling experiments, SEM analysis of the rice surface, and rice wear experiments. The results showed that the bran layer of rice grains exhibited different removal patterns at different milling pressures. During frictional debranning between rice grains, adhesive wear and bulk stripping of the bran layer occurred. The bran layer of the rice grain initially experiences primary damage due to adhesive wear, followed by bulk stripping at the edges of the existing damage. Pre-milling can effectively improve the debranning efficiency of rice grains. These findings should provide a theoretical reference for the design of grain milling equipment and the process improvement of grain moderate milling.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 130-141"},"PeriodicalIF":4.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of slurry separation and air-plasma treatment on NH3 and VOC emissions from field applied biogas digestate and pig slurry to grassland","authors":"Johanna Pedersen ,&nbsp;Rodrigo Labouriau ,&nbsp;Anders Feilberg","doi":"10.1016/j.biosystemseng.2024.09.014","DOIUrl":"10.1016/j.biosystemseng.2024.09.014","url":null,"abstract":"<div><div>Different technologies can be utilised to mitigate environmentally harmful ammonia (NH₃) emissions after field application of liquid animal manure (slurry). After a solid-liquid separation, air-plasma technology can acidify the liquid fraction and enrich its nutrient value by increasing the amount of inorganic nitrogen. The present work investigates the emissions of NH₃ and volatile organic compounds (VOC) after field application of the following fractions of pig slurry and slurry digestate: i) untreated slurry (UN), ii) liquid fraction of slurry (LF), iii) liquid fraction of slurry treated with air from the plasma treatment (LP). Emissions were measured with a system of wind tunnels and a cavity ring-down spectrometer for NH₃ concentration measurements and a proton-transfer-reaction mass-spectrometer for measurements of VOC. For both slurry types, the cumulative NH₃ emissions were in the following order UN &gt; LF &gt; LP. All the differences were significant (P &lt; 0.05), except between pig slurry LF and LP. The reduction in cumulative NH₃ emission obtained by the treatments compared to UN were 55–74% and 70–89% for LF and LP, respectively. The slurry separation decreased dry matter by 46–54% and resulted in a rapid decrease in slurry exposed surface area after application, presumably due to high infiltration. Several VOCs were measured after application of the slurry, but continuous emission was undetectable for all VOCs. The very low VOC emission was presumably due to high infiltration of the low dry matter slurry treatments and low concentration of VOC in the digestate.<span><div><span><div><strong>Science4Impact Statement</strong></div></span><div><div>This work demonstrates how treating slurry with plasma treated air can mitigate ammonia emissions after field application. The presented findings can be used for additional technology development and verification. Future research efforts should e.g. clarify what level of solid-liquid separation is needed before treating the liquid fraction with plasma treated air, to assess whether the additional ammonia reductions are profitable. Furthermore, the findings can be used by decision makers and advisory bodies to assess the compliancy of this slurry application technology with applicable environmental regulations. The work also highlights important remaining knowledge gaps that need to be investigated before the technology can be deemed fit for wider practical application.</div></div></div></span></div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 257-266"},"PeriodicalIF":4.4,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nutrient flows in biofloc-Nile tilapia culture: A semi-physical modelling approach","authors":"Nurhayati Br Tarigan ,&nbsp;Marc Verdegem ,&nbsp;Julie Ekasari ,&nbsp;Karel J. Keesman","doi":"10.1016/j.biosystemseng.2024.09.021","DOIUrl":"10.1016/j.biosystemseng.2024.09.021","url":null,"abstract":"<div><div>Biofloc culture systems potentially reduce the nutrient losses in aquaculture. However, knowledge of the nutrient flows in the system is not yet well-developed. This study deployed experimental data to develop a semi-physical model to understand the dynamics and flows of carbon (C), nitrogen (N), and phosphorus (P) in a biofloc-Nile tilapia-rearing system. The model involved eight process variables, which are pelleted feed A, C, N, P, fish, biofloc, periphyton, and water volume. Model calibration and validation were done under a Control-diet and High-NSP-diet, respectively. The diets differed by the type of starch in which the latter contains three times higher fibrous starch, called non-starch polysaccharides, than the former. Except for biofloc, the behaviour of the process variables fit the observations with a root mean square error (RMSE) of less than 30% of the corresponding average observations. The biofloc biomass was predicted using exponential growth model and results in a RMSE of 49% and 56% for the Control and High-NSP-diet, respectively. Scenario analyses, using the validated model, showed that the biofloc system generates less waste when the stocking density is doubled, which means double fish production and less nutrient losses. In terms of different diets, the high-NSP-diet resulted in more organic waste than the Control-diet. However, the amount of loss and unutilised C and P were similar which was mainly caused by the ability of biofloc and periphyton to assimilate more waste, especially C, in the High-NSP-diet.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 108-129"},"PeriodicalIF":4.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LSANNet: A lightweight convolutional neural network for maize leaf disease identification","authors":"Fu Zhang ,&nbsp;Ruofei Bao ,&nbsp;Baoping Yan ,&nbsp;Mengyao Wang ,&nbsp;Yakun Zhang ,&nbsp;Sanling Fu","doi":"10.1016/j.biosystemseng.2024.09.023","DOIUrl":"10.1016/j.biosystemseng.2024.09.023","url":null,"abstract":"<div><div>Maize (<em>Zea Mays</em>) is a major food crop and is of great importance to ensure national food security. However, maize leaf diseases occur from time to time, which poses a serious threat to grain yield and quality, so methods for the quick identification of maize leaf diseases are particularly important. In this paper, a long-short attention neural network (LSANNet) is proposed for maize leaf diseases identification. The main component of the LSANNet is the long-short attention block (LSAB). The long-short connection method enables the fusion of multi-scale features, which enhances the model generalisation capability. The attention mechanism is applied in the block, which aims to enhance the extraction of maize leaf features. The effectiveness of separable convolution and attention modules is demonstrated by ablation studies. Experimental results on 124 unseen images show that the accuracy of the proposed model on the test sets reaches 94.35%, which is better than the accuracy of existing models, such as VGG16, ResNet50, DenseNet201, MobileNetV3S, and Xception. The practical performance of the proposed network model is verified by deploying the model on a mobile device, demonstrating strong compatibility and high recognition. In this paper, a lightweight convolutional neural work is proposed for maize leaf disease identification, and the performance of the network on the test sets meets the required requirements. This research will provide an idea for the identification of maize leaf diseases and disease prevention schemes for agricultural production.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 97-107"},"PeriodicalIF":4.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Covering reduces emissions of ammonia, methane, and nitrous oxide from stockpiled broiler litter","authors":"Jesper N. Kamp,&nbsp;Anders Feilberg","doi":"10.1016/j.biosystemseng.2024.10.002","DOIUrl":"10.1016/j.biosystemseng.2024.10.002","url":null,"abstract":"<div><div>Poultry litter, a mix of excreta, bedding material, and discarded feed, is extracted from poultry houses, and used as fertiliser. The litter is often stored in stockpiles outside before field application thereby posing a risk for negative environmental and climatic impact from emissions of ammonia (NH₃) and greenhouse gases (GHG). This study investigated the emissions of methane (CH₄), NH₃, and nitrous oxide (N₂O) from a 22 tonnes broiler litter stockpile over 44 days. The emissions were measured on a farm-scale stockpile with and without coverage using the backward Lagrangian Stochastic method. The results showed distinct emission patterns for each gas during the measurement periods. For all compounds, the emissions during the covered period were significantly lower than during the two uncovered periods. The reduction due to coverage was 92–95% for NH₃, 25–40% for CH₄, and 82–89% for N₂O. NH₃ emissions were highest immediately after coverage removal and during stockpile removal. CH₄ emissions were highest during stockpile removal and lowest during coverage. N₂O emissions were lowest during coverage but a notable increase after coverage removal was observed. The temperature within the stockpile showed variations at different heights, with the highest temperatures recorded in the middle of the stockpile. GHG emissions, based on global warming potential, indicate substantial contributions from N₂O, accounting for 55–72% of emissions in CO₂-equivalents during uncovered periods and 27% during coverage. Furthermore, GHG emissions were reduced 63–72% during coverage compared to the uncovered periods highlighting the importance for immediate coverage of stockpiles to minimise NH₃ and GHG emissions.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 73-81"},"PeriodicalIF":4.4,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial LiDAR odometry and mapping for complex agricultural environments - Spatial FieldLOAM","authors":"Jurij Rakun ,&nbsp;František Duchoň ,&nbsp;Peter Lepej","doi":"10.1016/j.biosystemseng.2024.09.020","DOIUrl":"10.1016/j.biosystemseng.2024.09.020","url":null,"abstract":"<div><div>The challenge of autonomous driving in natural environments, without the use of GNSS devices is addressed. It utilises the readings from a multichannel LiDAR, supported by IMU, and enhances the capabilities of the FieldSLAM algorithm to establish an independent localisation and mapping system. This system is designed for performing specific tasks in predefined agricultural areas, employing incremental LOAM techniques. By comparing the outcomes of the novel Spatial FieldLOAM algorithm with the assistance of a precise Inertial Measurement Unit (IMU) and using the state-of-the-art RTK-GPS system as the ground truth, it is concluded that the Spatial FieldLOAM achieves an error rate of 5.5%, whereas the Xsens IMU yields an error rate of 5.7%. In terms of Euclidean distances to the final RTK GPS supported localisation on a 68.7 m test run, the error rates are 3.78 m and 3.92 m, respectively, or 0.0038 m per epoch for the Spatial FieldLOAM algorithm during non-vegetation season. The tests were also conducted during the vegetation season in a total length of 210 m, revealing a difference of 3.07 m distance between the final position calculated by the Spatial FieldLOAM and Xsens IMU.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 58-72"},"PeriodicalIF":4.4,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating a hybrid process of anaerobic digestion, aerobic degradation, and electrochemical separation for swine wastewater treatment with methane and nutrient recovery","authors":"Run-Feng Chen ,&nbsp;Chun-Hai Wei ,&nbsp;Hai-Tao Zhong ,&nbsp;Xiu-Feng Ye ,&nbsp;Jun-Jie Ye ,&nbsp;Kai Liu ,&nbsp;Quan-Bao Zhao ,&nbsp;Huu Hao Ngo","doi":"10.1016/j.biosystemseng.2024.09.022","DOIUrl":"10.1016/j.biosystemseng.2024.09.022","url":null,"abstract":"<div><div>A hybrid process of anaerobic digestion (AD), aerobic degradation, and electrochemical separation was evaluated for treating real swine wastewater that is rich in organic and nutrient to achieve methane and nutrient recovery and industry standard discharge quality. Fe anode electrocoagulation and Mg anode struvite electrochemical precipitation (SEP) were evaluated as AD pretreatments. Both removed partial chemical oxygen demand (COD) from raw swine wastewater, but only SEP slightly enhanced the methane yield of pretreated swine wastewater. The SEP efficiency of the AD effluent was significantly better than raw swine wastewater. A further coupled micro/ultra-filtration produced high-purity (96%) struvite. SEP and struvite chemical precipitation (SCP) were evaluated for AD effluent treatment. This showed that compared with SCP following first-order reaction kinetics (reaction rate constant of 0.791 and 0.854 h⁻¹ for NH₄⁺-N and PO₄^3--P), SEP not only achieved better removal of COD, NH₄⁺-N and PO₄^3--P, but was also shown to follow zero-order reaction kinetics (reaction rate constant of 5.72 and 5.78 mmol L⁻¹ h⁻¹ for NH₄⁺-N and PO₄^3--P). The SEP and SCP treated AD effluent was evaluated by conventional activated sludge (CAS), showing faster COD removal (first-order reaction rate constant of 0. 213 and 0.163 h⁻¹) and lower residual COD (150 and 248 mg L⁻¹) from SEP than SCP treated AD effluent, making the final effluent well below Chinese livestock wastewater discharge standards. Therefore, an emerging hybrid anaerobic membrane bioreactor (AnMBR)-SEP-CAS is proposed for swine wastewater treatment and proved to be more economically viable than the conventional hybrid AD-SCP-CAS process via cost-benefit analysis.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 47-57"},"PeriodicalIF":4.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PointStack based 3D automatic body measurement for goat phenotypic information acquisition","authors":"Bo Jin ,&nbsp;Guorui Wang ,&nbsp;Jingze Feng ,&nbsp;Yongliang Qiao ,&nbsp;Zhifeng Yao ,&nbsp;Mei Li ,&nbsp;Meili Wang","doi":"10.1016/j.biosystemseng.2024.09.008","DOIUrl":"10.1016/j.biosystemseng.2024.09.008","url":null,"abstract":"<div><div>The body size of livestock is an essential phenotypic trait in genetic breeding, gene improvement, health screening, and animal welfare. To develop a non-contact automatic system for measuring goat body traits, we propose a point-cloud segmentation model based on an improved PointStack, which segments the automatically acquired three-dimensional (3D) point-cloud data of goats into different parts, including the head, front legs, hind legs, chest, abdomen, hip, and tail. The segmented point cloud, along with the physiological features of the goat, is then used to locate the corresponding key points for body size measurement. A novel method for key point localisation is proposed that includes coordinate normalisation, retrieval of key clusters, key point adjustment, optimisation of the traveling salesman problem, and edge detection. These methods were designed to reduce discrepancies at crucial points of body features, thereby facilitating the precise computation of the body size parameter in goats. In this work, 326 point clouds representing the upright posture of 55 goats were used for segmentation and body size measurement testing. The proposed segmentation model achieved a mean intersection over union of 89.21% and accuracy of 94.54%, outperforming comparative models. In the body traits measurement experiment, mean absolute percentage errors for body length, body height, chest width, chest girth, hip height, and hip width were recorded as 3.24%, 2.54%, 5.43%, 3.08%, 2.16%, and 4.59%, respectively. In summary, the proposed automated measurement method demonstrates high accuracy, strong robustness, and holds significant potential for widespread application.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"248 ","pages":"Pages 32-46"},"PeriodicalIF":4.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142357508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}