Pub Date : 2025-12-23DOI: 10.1016/j.biosystemseng.2025.104374
Mengjie Li , Juan Wang , Na Li , Yaju Liu , Xue Cheng , Xinpei Fu , Sirui Li
The production mode in which a milking device is manually set on the teats of dairy cows is inefficient and labour-intensive. Automatic teat-cup-attachment technology can reduce the labour-intensive and increase milking efficient. In order to automatically attach the teat cup more accurately and quickly, an enhanced cow-teat-detection model was proposed, which was utilized in an automatic teat-cup-attachment device. Based on the YOLOv7, the Wise-IoU loss function was introduced, which enhanced the fitting ability and convergence speed of the bounding box regression. To optimize the captures pertaining to the features of cow teats in a complex background and to reduce the loss of the features from a small target, a fourth feature scale was constructed in the Neck network. To make the model focus more on the detailed information related to the target and enhance the target-recognition accuracy, a Coordinate Attention (CA) mechanism was added to the Backbone network and to the Neck network. The comparison experiment and ablation experiment were performed on the self-made dataset. The results revealed that the mAP0.5, Precision, and Recall of the improved YOLOv7 were 98.18 %, 97.50 %, and 96.15 %, respectively, which were 1.96, 2.07, and 2.67 percentage points higher than those of the baseline YOLOv7 model, respectively. The detection performance was significantly enhanced. This study provides the technical support for the milking device to achieve accurate positioning and rapid automatic teat-cup-attachment.
{"title":"An enhanced cow-teat-detection model for automatic teat-cup-attachment devices","authors":"Mengjie Li , Juan Wang , Na Li , Yaju Liu , Xue Cheng , Xinpei Fu , Sirui Li","doi":"10.1016/j.biosystemseng.2025.104374","DOIUrl":"10.1016/j.biosystemseng.2025.104374","url":null,"abstract":"<div><div>The production mode in which a milking device is manually set on the teats of dairy cows is inefficient and labour-intensive. Automatic teat-cup-attachment technology can reduce the labour-intensive and increase milking efficient. In order to automatically attach the teat cup more accurately and quickly, an enhanced cow-teat-detection model was proposed, which was utilized in an automatic teat-cup-attachment device. Based on the YOLOv7, the Wise-IoU loss function was introduced, which enhanced the fitting ability and convergence speed of the bounding box regression. To optimize the captures pertaining to the features of cow teats in a complex background and to reduce the loss of the features from a small target, a fourth feature scale was constructed in the Neck network. To make the model focus more on the detailed information related to the target and enhance the target-recognition accuracy, a Coordinate Attention (CA) mechanism was added to the Backbone network and to the Neck network. The comparison experiment and ablation experiment were performed on the self-made dataset. The results revealed that the mAP<sub>0.5</sub>, Precision, and Recall of the improved YOLOv7 were 98.18 %, 97.50 %, and 96.15 %, respectively, which were 1.96, 2.07, and 2.67 percentage points higher than those of the baseline YOLOv7 model, respectively. The detection performance was significantly enhanced. This study provides the technical support for the milking device to achieve accurate positioning and rapid automatic teat-cup-attachment.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104374"},"PeriodicalIF":5.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837519","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}
Pub Date : 2025-12-23DOI: 10.1016/j.biosystemseng.2025.104364
Zhengpu Chen , Carl Wassgren , R.P.Kingsly Ambrose , Yuefeng Du , Zhenghe Song , Xiaoyu Li
The Discrete Element Method (DEM) has gained increasing popularity for modelling agricultural production machinery and processes. As a key DEM input parameter, the coefficient of restitution (COR) quantifies energy dissipation during particle contacts, and its accurate determination is critical for predicting realistic particle dynamics, flow patterns, and consequently the performance of agricultural machinery. Despite the importance of the COR, a comprehensive review on its determination and usage in agricultural DEM applications is currently lacking. To address this gap, this study reviewed recent literature, summarizing and evaluating COR definitions, determination approaches, influencing factors, and effects on simulation outcomes. Among different COR definitions, the velocity-based kinematic COR remains the most widely implemented in DEM software due to its computational efficiency and ease of measurement. Current measurement approaches, such as drop tests and pendulum impact tests, often require high-speed cameras, highlighting a need for simpler, more robust methods for rapid COR determination. As the COR is influenced by various factors including impact speed, impact angle, and material properties, further investigation into the value of implementing a parameter-dependent COR and its efficient incorporation into DEM simulations is needed. Research findings from previous DEM simulation studies indicate that the COR significantly influences measurements in dilute flow systems, while exerting less influence on the macroscopic flow behaviour of dense flow systems. Comprehensive sensitivity analyses of the COR in DEM simulations of agricultural production systems are lacking, limiting our understanding of its effects on simulation predictions. In summary, this study summarizes current knowledge, identifies best practices, provides guidelines for COR usage in DEM simulations, and outlines future research directions for the COR in DEM within agricultural contexts.
{"title":"Coefficient of restitution considerations in the discrete element method for agricultural materials: A review","authors":"Zhengpu Chen , Carl Wassgren , R.P.Kingsly Ambrose , Yuefeng Du , Zhenghe Song , Xiaoyu Li","doi":"10.1016/j.biosystemseng.2025.104364","DOIUrl":"10.1016/j.biosystemseng.2025.104364","url":null,"abstract":"<div><div>The Discrete Element Method (DEM) has gained increasing popularity for modelling agricultural production machinery and processes. As a key DEM input parameter, the coefficient of restitution (COR) quantifies energy dissipation during particle contacts, and its accurate determination is critical for predicting realistic particle dynamics, flow patterns, and consequently the performance of agricultural machinery. Despite the importance of the COR, a comprehensive review on its determination and usage in agricultural DEM applications is currently lacking. To address this gap, this study reviewed recent literature, summarizing and evaluating COR definitions, determination approaches, influencing factors, and effects on simulation outcomes. Among different COR definitions, the velocity-based kinematic COR remains the most widely implemented in DEM software due to its computational efficiency and ease of measurement. Current measurement approaches, such as drop tests and pendulum impact tests, often require high-speed cameras, highlighting a need for simpler, more robust methods for rapid COR determination. As the COR is influenced by various factors including impact speed, impact angle, and material properties, further investigation into the value of implementing a parameter-dependent COR and its efficient incorporation into DEM simulations is needed. Research findings from previous DEM simulation studies indicate that the COR significantly influences measurements in dilute flow systems, while exerting less influence on the macroscopic flow behaviour of dense flow systems. Comprehensive sensitivity analyses of the COR in DEM simulations of agricultural production systems are lacking, limiting our understanding of its effects on simulation predictions. In summary, this study summarizes current knowledge, identifies best practices, provides guidelines for COR usage in DEM simulations, and outlines future research directions for the COR in DEM within agricultural contexts.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104364"},"PeriodicalIF":5.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837518","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}
Pub Date : 2025-12-23DOI: 10.1016/j.biosystemseng.2025.104366
S. Parrini , C. Dadousis , F. Sirtori , M.C. Fabbri , M. Čandek-Potokar , J.M. Garcia-Casco , B. Lebret , R. Nieto , C. Aquilani , R. Bozzi
The combination of Fourier transform near-infrared spectroscopy (FT-NIRS) of meat and fat samples and principal component discriminant analysis (DAPC) has been proposed as a tool for discriminating the local production of autochthonous pig breeds. Spectral samples (n = 272) belonging to 11 local European pig breeds, Longissimus muscle, and subcutaneous fat (both intact and minced) are collected. Classification accuracy based on DAPC was applied on FT-NIRS to predict breed of origin in i) semi-external cross-validation, splitting the data into training (80 %) and testing (20 %) sets; ii) external validation, in which one breed at a time was excluded from model training and classified in one of the remaining breeds. The effect of varying sample sizes from 50 % to 100 % of the data was assessed. Almost all breeds' spectra variability was summarised into two principal components for tissue and sample preparation. In cross-validation, intact fat yielded higher classification accuracies than intact meat, with less pronounced differences in minced samples. Success assignment rates of ∼81–83 % were obtained for two breeds in intact meat samples and were higher than 83 % for five breeds in fat samples. For minced samples, correct assignments between 80 % and 100 % were possible for five breeds, both in meat and fat samples. Sample size marginally affected the results. External validation confirmed similarity among some breeds, with greater accuracy for fat samples. The assignments success provides encouraging results for discriminating local pig production, mainly based on fat, using a rapid, eco-friendly FT-NIRS method, which could serve as tool for quality assurance.
{"title":"Discrimination of autochthonous pig breeds from meat and fat samples by FT-NIR spectra","authors":"S. Parrini , C. Dadousis , F. Sirtori , M.C. Fabbri , M. Čandek-Potokar , J.M. Garcia-Casco , B. Lebret , R. Nieto , C. Aquilani , R. Bozzi","doi":"10.1016/j.biosystemseng.2025.104366","DOIUrl":"10.1016/j.biosystemseng.2025.104366","url":null,"abstract":"<div><div>The combination of Fourier transform near-infrared spectroscopy (FT-NIRS) of meat and fat samples and principal component discriminant analysis (DAPC) has been proposed as a tool for discriminating the local production of autochthonous pig breeds. Spectral samples (n = 272) belonging to 11 local European pig breeds, Longissimus muscle, and subcutaneous fat (both intact and minced) are collected. Classification accuracy based on DAPC was applied on FT-NIRS to predict breed of origin in i) semi-external cross-validation, splitting the data into training (80 %) and testing (20 %) sets; ii) external validation, in which one breed at a time was excluded from model training and classified in one of the remaining breeds. The effect of varying sample sizes from 50 % to 100 % of the data was assessed. Almost all breeds' spectra variability was summarised into two principal components for tissue and sample preparation. In cross-validation, intact fat yielded higher classification accuracies than intact meat, with less pronounced differences in minced samples. Success assignment rates of ∼81–83 % were obtained for two breeds in intact meat samples and were higher than 83 % for five breeds in fat samples. For minced samples, correct assignments between 80 % and 100 % were possible for five breeds, both in meat and fat samples. Sample size marginally affected the results. External validation confirmed similarity among some breeds, with greater accuracy for fat samples. The assignments success provides encouraging results for discriminating local pig production, mainly based on fat, using a rapid, eco-friendly FT-NIRS method, which could serve as tool for quality assurance.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104366"},"PeriodicalIF":5.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837487","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}
Pub Date : 2025-12-22DOI: 10.1016/j.biosystemseng.2025.104363
Duc Nguyen , Si Thu Paing , Sarah Wakes , Ross Vennell , Scott Rhone , Louise Kregting , Suzy Black
This study examines the influence of various angles of attack of current flow (0° to 90° with 10° intervals) on the hydrodynamic performance, surface shear stress and drag force of various designs of semi-mobile aquaculture structures. The structures were cylinder- and cone-shaped, with the porosity on the body varying from 0 % to 15 %. Computational Fluid Dynamics (CFD) was employed, and the modelled flow speed and drag force were validated with flume-based experiments on a scaled model, 2.16 m in length and 0.45 m3 in volume. It was found that when the angle of attack was 30° and 60°, flow acceleration, from 1 to 1.3 , and low-speed zones (<0.1 ) occurred in the cylinder-shaped structure with an impermeable body (design 1A). However, flow speed was relatively uniform in the cone-shaped structure with porosity of 15 % (design 2A). When the angle of attack was 90°, flow speed in the structure increased from 0 in design 1A to 0.4 in design 2A. This indicated that hydrodynamics in design 2A could be more beneficial for fish welfare (increased water flow maintains dissolved oxygen) than design 1A, particularly during oblique flow conditions. However, the drag force exerted on design 2A is greater than those on design 1A. These differences in drag force increase when the flow speed increases and the volume of the structure increases, which could increase the operational costs. Overall, the findings of this work imply that designing aquaculture structures that benefit both fish and farmers is challenging, and balancing fish requirements with operational costs is crucial to select appropriate designs.
{"title":"Influence of angle of attack on hydrodynamic performance and its implications for designing semi-mobile aquaculture structures: A CFD study","authors":"Duc Nguyen , Si Thu Paing , Sarah Wakes , Ross Vennell , Scott Rhone , Louise Kregting , Suzy Black","doi":"10.1016/j.biosystemseng.2025.104363","DOIUrl":"10.1016/j.biosystemseng.2025.104363","url":null,"abstract":"<div><div>This study examines the influence of various angles of attack of current flow (0° to 90° with 10° intervals) on the hydrodynamic performance, surface shear stress and drag force of various designs of semi-mobile aquaculture structures. The structures were cylinder- and cone-shaped, with the porosity on the body varying from 0 % to 15 %. Computational Fluid Dynamics (CFD) was employed, and the modelled flow speed and drag force were validated with flume-based experiments on a scaled model, 2.16 m in length and 0.45 m<sup>3</sup> in volume. It was found that when the angle of attack was 30° and 60°, flow acceleration, from 1 to 1.3 <span><math><mrow><mi>m</mi><mspace></mspace><msup><mi>s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>, and low-speed zones (<0.1 <span><math><mrow><mi>m</mi><msup><mrow><mspace></mspace><mi>s</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>) occurred in the cylinder-shaped structure with an impermeable body (design 1A). However, flow speed was relatively uniform in the cone-shaped structure with porosity of 15 % (design 2A). When the angle of attack was 90°, flow speed in the structure increased from 0 <span><math><mrow><mi>m</mi><msup><mrow><mspace></mspace><mi>s</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span> in design 1A to 0.4 <span><math><mrow><mi>m</mi><mspace></mspace><msup><mi>s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span> in design 2A. This indicated that hydrodynamics in design 2A could be more beneficial for fish welfare (increased water flow maintains dissolved oxygen) than design 1A, particularly during oblique flow conditions. However, the drag force exerted on design 2A is greater than those on design 1A. These differences in drag force increase when the flow speed increases and the volume of the structure increases, which could increase the operational costs. Overall, the findings of this work imply that designing aquaculture structures that benefit both fish and farmers is challenging, and balancing fish requirements with operational costs is crucial to select appropriate designs.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104363"},"PeriodicalIF":5.3,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837490","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}
Pub Date : 2025-12-22DOI: 10.1016/j.biosystemseng.2025.104372
Yaping Li , Hequn Tan , Yiren Zhang , Xuefei Liu
Accurately predicting the feed intake of fish schools during intensive aquaculture is a crucial foundation for feeding decision systems. In the pond-based captive farming process, feeding devices cannot automatically and precisely adjust feeding strategies based on the farming environment, growth information, and parameters during the feeding process. To address this, a method based on multi-source information fusion is proposed to quantify the feeding demand of M. salmoides. Firstly, a two-stage feeding experiment was conducted to collect multi-source data from the first-stage feeding, along with supplementary feed intake (feed intake in the second stage). Secondly, a feeding endpoint detection algorithm was developed for the collected audio to identify feeding audio, and correlation analysis was applied to select features extracted from the feeding audio, which were processed utilising PCA to obtain the overall feeding feature. Thirdly, the SHAP method was used to identify the sensitive features. Finally, sensitive features were selected as inputs to establish a supplementary feed intake prediction model. Experimental results showed that the GBDT achieved the best performance among six ML models (CCC = 0.96, RMSE = 226.82 g, MAE = 173.93 g); The GBDT constructed in this study achieved an CCC of 0.93, an RMSE of 226.87 g, and an MAE of 170.55 g in real aquaculture scenarios; The GBDT-based feeding strategy achieved superior performance. This study enables the conversion of multi-source data into executable decision variables for feeding devices, thereby providing a data-driven decision-making framework for intelligent feeding systems.
{"title":"A quantitative method of feeding demand for M. salmoides based on multi-source information fusion","authors":"Yaping Li , Hequn Tan , Yiren Zhang , Xuefei Liu","doi":"10.1016/j.biosystemseng.2025.104372","DOIUrl":"10.1016/j.biosystemseng.2025.104372","url":null,"abstract":"<div><div>Accurately predicting the feed intake of fish schools during intensive aquaculture is a crucial foundation for feeding decision systems. In the pond-based captive farming process, feeding devices cannot automatically and precisely adjust feeding strategies based on the farming environment, growth information, and parameters during the feeding process. To address this, a method based on multi-source information fusion is proposed to quantify the feeding demand of <em>M. salmoides</em>. Firstly, a two-stage feeding experiment was conducted to collect multi-source data from the first-stage feeding, along with supplementary feed intake (feed intake in the second stage). Secondly, a feeding endpoint detection algorithm was developed for the collected audio to identify feeding audio, and correlation analysis was applied to select features extracted from the feeding audio, which were processed utilising PCA to obtain the overall feeding feature. Thirdly, the SHAP method was used to identify the sensitive features. Finally, sensitive features were selected as inputs to establish a supplementary feed intake prediction model. Experimental results showed that the GBDT achieved the best performance among six ML models (CCC = 0.96, RMSE = 226.82 g, MAE = 173.93 g); The GBDT constructed in this study achieved an CCC of 0.93, an RMSE of 226.87 g, and an MAE of 170.55 g in real aquaculture scenarios; The GBDT-based feeding strategy achieved superior performance. This study enables the conversion of multi-source data into executable decision variables for feeding devices, thereby providing a data-driven decision-making framework for intelligent feeding systems.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104372"},"PeriodicalIF":5.3,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837488","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}
Pub Date : 2025-12-19DOI: 10.1016/j.biosystemseng.2025.104360
Vasileios Anestis , Wajid Umar , Federico Dragoni , Tony J. van der Weerden , Mélynda Hassouna , Alasdair Noble , Thomas Bartzanas , Barbara Amon
{"title":"Erratum to “Mitigation of greenhouse gas and ammonia emissions due to livestock housing management practices: Analysis of the DATAMAN database” [Biosystems engineering (258), September 2025, 104260]","authors":"Vasileios Anestis , Wajid Umar , Federico Dragoni , Tony J. van der Weerden , Mélynda Hassouna , Alasdair Noble , Thomas Bartzanas , Barbara Amon","doi":"10.1016/j.biosystemseng.2025.104360","DOIUrl":"10.1016/j.biosystemseng.2025.104360","url":null,"abstract":"","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104360"},"PeriodicalIF":5.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788839","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}
Pub Date : 2025-12-19DOI: 10.1016/j.biosystemseng.2025.104362
Tiancheng Yu , Huanyu Jiang
Vertical farming integrated with hydroponics offers sustainable urban food solutions, yet reliance on manual harvesting, which requires labour-intensive tray transport and cutting, hinders scalability. This study focuses on the design and performance testing of an end effector for automated in-situ robotic harvesting of vertically stacked hydroponic lettuce, addressing two critical advancements: mechanised harvesting and post-harvest lightweight tray logistics. Manual harvesting trials revealed that push-cutting requires only 3.154 N of force (approximately 66 % lower than pull-cutting's 9.313 N), forming the basis for an energy-efficient end effector design. A novel robotic harvesting mode based on push-cutting was proposed, incorporating five phases: inserting, gripping, cutting, transporting, and unloading. An end effector integrating gripping and cutting functions was designed and optimised. Using response surface methodology, the optimal gripper parameters were determined: rotation radius of 73 mm, rotation angle of 80°, and movable finger diameter of 25 mm. The cutting performance test revealed the optimal cutting position as 5 mm above the root-stem junction and the optimal bevel cutting angle as 15°. Through structural improvements, the end effector was enhanced with a two-finger rotation mechanism to achieve more efficient and convenient unloading. Experimental results from performance testing demonstrated a harvesting success rate of 94 % and a leaf loss rate of 3.50 %, confirming the effectiveness and feasibility of the designed end effector. This innovation establishes a logistics-minimised automation framework for vertical farms, enhancing scalability and sustainability through energy-efficient, high-precision robotics and optimised material flow.
{"title":"Toward sustainable urban agriculture: Development of a robotic end effector for hydroponic lettuce in-situ harvesting in vertical farming","authors":"Tiancheng Yu , Huanyu Jiang","doi":"10.1016/j.biosystemseng.2025.104362","DOIUrl":"10.1016/j.biosystemseng.2025.104362","url":null,"abstract":"<div><div>Vertical farming integrated with hydroponics offers sustainable urban food solutions, yet reliance on manual harvesting, which requires labour-intensive tray transport and cutting, hinders scalability. This study focuses on the design and performance testing of an end effector for automated in-situ robotic harvesting of vertically stacked hydroponic lettuce, addressing two critical advancements: mechanised harvesting and post-harvest lightweight tray logistics. Manual harvesting trials revealed that push-cutting requires only 3.154 N of force (approximately 66 % lower than pull-cutting's 9.313 N), forming the basis for an energy-efficient end effector design. A novel robotic harvesting mode based on push-cutting was proposed, incorporating five phases: inserting, gripping, cutting, transporting, and unloading. An end effector integrating gripping and cutting functions was designed and optimised. Using response surface methodology, the optimal gripper parameters were determined: rotation radius of 73 mm, rotation angle of 80°, and movable finger diameter of 25 mm. The cutting performance test revealed the optimal cutting position as 5 mm above the root-stem junction and the optimal bevel cutting angle as 15°. Through structural improvements, the end effector was enhanced with a two-finger rotation mechanism to achieve more efficient and convenient unloading. Experimental results from performance testing demonstrated a harvesting success rate of 94 % and a leaf loss rate of 3.50 %, confirming the effectiveness and feasibility of the designed end effector. This innovation establishes a logistics-minimised automation framework for vertical farms, enhancing scalability and sustainability through energy-efficient, high-precision robotics and optimised material flow.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104362"},"PeriodicalIF":5.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788841","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}
Pub Date : 2025-12-18DOI: 10.1016/j.biosystemseng.2025.104365
Y. Gómez , N. Blasco-Andreo , A. Llabrés-Brustenga , K. Chow , J. Serra-Sagrista , G.V. Berteselli , E. Canali , X. Manteca , P. Llonch
Animal welfare on farms is currently assessed using human-evaluation protocols, which provide a single record of herd condition at a specific moment. Integrating sensor-based data and farm records, continuous information on each animal's welfare can be obtained. This study aims to create an algorithm to assess individual dairy cow welfare, contributing to the goal of building a platform to inform producers and consumers about dairy cattle welfare. It was built based on the Five Domains model of animal welfare. 221 cows from four commercial free-stall barn farms in Spain and Italy were fitted with accelerometry collars and rumen boluses and monitored for 92 days. Individual data were collected daily. Accelerometers recorded time spent ruminating, eating, lying, walking, and standing within a 24-h interval. Boluses recorded rumen pH and temperature every 10 min, averaged over 24 h. Farm records included parity, veterinary treatments, and milk conductivity. The model provides a daily global welfare index per cow, categorised into health, nutrition, and environment scores. Behaviour and mental state were not included due to a lack of relevant sensor data. Scores range from 0 to 10, indicating the likelihood of the cow experiencing welfare-compromising conditions. Normal thresholds, based on scientific literature, were set for each trait. The algorithm detected daily deviations in traits, assuming that cows with welfare issues deviate from normal behavioural and physiological patterns. When a cow's welfare index decreased, affected domains could be identified, enabling farmers to address potential welfare issues and implement corrective measures.
{"title":"Continuous welfare assessment of dairy cows at individual level: A farmer-oriented tool based on normal daily ranges of sensor-recorded traits","authors":"Y. Gómez , N. Blasco-Andreo , A. Llabrés-Brustenga , K. Chow , J. Serra-Sagrista , G.V. Berteselli , E. Canali , X. Manteca , P. Llonch","doi":"10.1016/j.biosystemseng.2025.104365","DOIUrl":"10.1016/j.biosystemseng.2025.104365","url":null,"abstract":"<div><div>Animal welfare on farms is currently assessed using human-evaluation protocols, which provide a single record of herd condition at a specific moment. Integrating sensor-based data and farm records, continuous information on each animal's welfare can be obtained. This study aims to create an algorithm to assess individual dairy cow welfare, contributing to the goal of building a platform to inform producers and consumers about dairy cattle welfare. It was built based on the Five Domains model of animal welfare. 221 cows from four commercial free-stall barn farms in Spain and Italy were fitted with accelerometry collars and rumen boluses and monitored for 92 days. Individual data were collected daily. Accelerometers recorded time spent ruminating, eating, lying, walking, and standing within a 24-h interval. Boluses recorded rumen pH and temperature every 10 min, averaged over 24 h. Farm records included parity, veterinary treatments, and milk conductivity. The model provides a daily global welfare index per cow, categorised into health, nutrition, and environment scores. Behaviour and mental state were not included due to a lack of relevant sensor data. Scores range from 0 to 10, indicating the likelihood of the cow experiencing welfare-compromising conditions. Normal thresholds, based on scientific literature, were set for each trait. The algorithm detected daily deviations in traits, assuming that cows with welfare issues deviate from normal behavioural and physiological patterns. When a cow's welfare index decreased, affected domains could be identified, enabling farmers to address potential welfare issues and implement corrective measures.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104365"},"PeriodicalIF":5.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788840","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}
Pub Date : 2025-12-18DOI: 10.1016/j.biosystemseng.2025.104368
Pengfei Zhao , Qingbin Song , Yubin Bi , Jianxin Dong , Zuoli Fu , Yuxiang Huang , Yi Zheng
To study the interaction mechanism between the seed suction and cleaning negative pressure at the suction hole of the air-suction seed metering device in maize breeding plot, CFD was used to simulate the flow field at the suction hole during the seed cleaning process. The decay change law of pressure at the suction hole during seed cleaning was studied through single-factor tests. The results showed that the adsorption pressure decay rate of the suction holes in the seed filling area was the largest. By analysing the pressure field and velocity field at the suction hole, it was found that the minimum negative pressure centre of the suction hole was affected by the seed cleaning negative pressure and shifted to the seed cleaning airflow side. Through the central composite design test, it was found that the seed suction and cleaning negative pressure had a highly significant interactive effect on the adsorption pressure of the suction holes in the seed filling area. And the influence of seed suction negative pressure was greater than that of seed cleaning negative pressure. The mathematical models for predicting adsorption pressure and decay rate were established on this basis. Through bench tests, the optimal parameter combination was determined to be 7 kPa for seed suction and 5 kPa for seed cleaning. No dropping of adsorbed seeds in the seed filling area was basically realized. This study can provide a theoretical basis for the design of air-suction seed metering devices in the plots.
{"title":"Interaction mechanisms of seed suction and cleaning negative pressure of an air-suction seed metering device for maize breeding plots","authors":"Pengfei Zhao , Qingbin Song , Yubin Bi , Jianxin Dong , Zuoli Fu , Yuxiang Huang , Yi Zheng","doi":"10.1016/j.biosystemseng.2025.104368","DOIUrl":"10.1016/j.biosystemseng.2025.104368","url":null,"abstract":"<div><div>To study the interaction mechanism between the seed suction and cleaning negative pressure at the suction hole of the air-suction seed metering device in maize breeding plot, CFD was used to simulate the flow field at the suction hole during the seed cleaning process. The decay change law of pressure at the suction hole during seed cleaning was studied through single-factor tests. The results showed that the adsorption pressure decay rate of the suction holes in the seed filling area was the largest. By analysing the pressure field and velocity field at the suction hole, it was found that the minimum negative pressure centre of the suction hole was affected by the seed cleaning negative pressure and shifted to the seed cleaning airflow side. Through the central composite design test, it was found that the seed suction and cleaning negative pressure had a highly significant interactive effect on the adsorption pressure of the suction holes in the seed filling area. And the influence of seed suction negative pressure was greater than that of seed cleaning negative pressure. The mathematical models for predicting adsorption pressure and decay rate were established on this basis. Through bench tests, the optimal parameter combination was determined to be 7 kPa for seed suction and 5 kPa for seed cleaning. No dropping of adsorbed seeds in the seed filling area was basically realized. This study can provide a theoretical basis for the design of air-suction seed metering devices in the plots.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104368"},"PeriodicalIF":5.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788842","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}
Pub Date : 2025-12-18DOI: 10.1016/j.biosystemseng.2025.104356
Long Zhou , Kuo Sun , Xu Zhao , Jingxiang Wang , Yulong Chen , Yongchang Sun , Wenjun Wang
Seeds are easy to collide with the guiding tube during air-seed contact in the air-assisted seed guiding process, which seriously affects the quality of sowing and has become a bottleneck problem hindering the development of precision sowing technology. Responding to the above, an innovative design of helical seed-guiding device with pressurised airflow assistance is presented. The structural parameters of the device are then optimised using Discrete Element Method - Computational Fluid Dynamics (DEM- CFD) simulation. To solve the problem of low accuracy of the ‘bonded-sphere model + unresolved DEM-CFD coupling model’, the calculation of porosity is improved by using virtual dual-grid porosity model with Gaussian kernel function smoothing method, and then the ‘multi-sphere model + semi-resolved DEM-CFD coupling model’ is constructed. Comparison of tests using blowing seeds with positive-pressure airflow reveals that the latter improves the simulation accuracy by 42.79 % relative to the former. Based on the new coupling calculation method, significance analysis and optimisation of the structural parameters of the helical seed-guiding device with pressurised airflow assistance by combining the Plackett-Burman and Box-Behnken test. The optimum combination of parameters obtained from the optimisation is a width of 4 mm for the helical guided airflow chamber, an angle of 39.36° for the inlet pipe and a number of helixes of 3. Finally, the working performance of the optimised seed guide tube is validated by adaptive and bench tests. The results showed that the coefficients of variation of plant spacing at each operating speed (8 km⋅h−1, 10 km⋅h−1, 12 km⋅h−1, and 14 km⋅h−1) are 5.51 %, 6.09 %, 9.01 %, 9.30 %, respectively. This study not only proposes a new airflow-assisted seed guiding device but also provides a coupled DEM-CFD calculation method applicable to large-size non-spherical particles.
{"title":"Design and optimisation of an air-assisted helical seed-guiding device for high-speed maize planters using DEM-CFD coupling","authors":"Long Zhou , Kuo Sun , Xu Zhao , Jingxiang Wang , Yulong Chen , Yongchang Sun , Wenjun Wang","doi":"10.1016/j.biosystemseng.2025.104356","DOIUrl":"10.1016/j.biosystemseng.2025.104356","url":null,"abstract":"<div><div>Seeds are easy to collide with the guiding tube during air-seed contact in the air-assisted seed guiding process, which seriously affects the quality of sowing and has become a bottleneck problem hindering the development of precision sowing technology. Responding to the above, an innovative design of helical seed-guiding device with pressurised airflow assistance is presented. The structural parameters of the device are then optimised using Discrete Element Method - Computational Fluid Dynamics (DEM- CFD) simulation. To solve the problem of low accuracy of the ‘bonded-sphere model + unresolved DEM-CFD coupling model’, the calculation of porosity is improved by using virtual dual-grid porosity model with Gaussian kernel function smoothing method, and then the ‘multi-sphere model + semi-resolved DEM-CFD coupling model’ is constructed. Comparison of tests using blowing seeds with positive-pressure airflow reveals that the latter improves the simulation accuracy by 42.79 % relative to the former. Based on the new coupling calculation method, significance analysis and optimisation of the structural parameters of the helical seed-guiding device with pressurised airflow assistance by combining the Plackett-Burman and Box-Behnken test. The optimum combination of parameters obtained from the optimisation is a width of 4 mm for the helical guided airflow chamber, an angle of 39.36° for the inlet pipe and a number of helixes of 3. Finally, the working performance of the optimised seed guide tube is validated by adaptive and bench tests. The results showed that the coefficients of variation of plant spacing at each operating speed (8 km⋅h<sup>−1</sup>, 10 km⋅h<sup>−1</sup>, 12 km⋅h<sup>−1</sup>, and 14 km⋅h<sup>−1</sup>) are 5.51 %, 6.09 %, 9.01 %, 9.30 %, respectively. This study not only proposes a new airflow-assisted seed guiding device but also provides a coupled DEM-CFD calculation method applicable to large-size non-spherical particles.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"262 ","pages":"Article 104356"},"PeriodicalIF":5.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788844","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}