Biosystems Engineering最新文献

{"title":"Characterising equivalent droplet indicators of sprinkler irrigation from a kinetic energy perspective","authors":"Rui Zhang ,&nbsp;Yichuan Liu ,&nbsp;Delan Zhu ,&nbsp;Pute Wu ,&nbsp;Changjuan Zheng ,&nbsp;Xiaomin Zhang ,&nbsp;Nazarov Khudayberdi ,&nbsp;Changxin Liu","doi":"10.1016/j.biosystemseng.2024.09.019","DOIUrl":"10.1016/j.biosystemseng.2024.09.019","url":null,"abstract":"<div><div>Equivalent droplet velocity and diameter are important parameters for measuring the effectiveness of sprinkler spraying; however, non-optical test methods (paper stain, flour pellet, and oil immersion methods) can only obtain the droplet number and diameter. With the widespread use of optical instruments in sprinkler testing, droplet velocity can also be measured, therefore, it has become possible to calculate the average droplet characteristics from an energy perspective. This paper proposes an energy-weighted method for calculating droplet equivalence indicators. Statistical analyses were performed based on five types of sprinkler irrigation droplet distribution data to compare the characteristics and differences between the energy-weighted method and the calculation results of the other methods. The results showed that 1) the velocity outcomes of the energy-weighted droplet equivalent method, empirical formula I, and empirical formula II consistently increase and decrease; 2) the equivalent droplet diameter based on the energy-weighted method is the largest, followed by the equivalent method related to droplet volume, and the smallest is the equivalent method related to droplet quantity; and 3) the equivalent droplet velocity and diameter calculated by the energy-weighted equivalent method can characterise droplets with a high energy contribution. The energy-weighted equivalent droplet velocity and diameter indicators derived in this study provide new ideas for characterising droplet averaging.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 241-248"},"PeriodicalIF":4.4,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314112","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":"Disturbance analysis and seeding performance evaluation of a pneumatic-seed spoon interactive precision maize seed-metering device for plot planting","authors":"Shidong Deng,&nbsp;Yamei Feng,&nbsp;Xiupei Cheng,&nbsp;Xianliang Wang,&nbsp;Xiangcai Zhang,&nbsp;Zhongcai Wei","doi":"10.1016/j.biosystemseng.2024.09.007","DOIUrl":"10.1016/j.biosystemseng.2024.09.007","url":null,"abstract":"<div><div>In response to the serious issue of missed seeding of the seed-metering device caused by the small and gradually decreasing number of maize seeds in plot planting conditions, a precision seed-metering device for maize plots with pneumatic-seed spoon interactive was designed. The seed-metering device utilises the coupling interaction between the seed spoons and airflow to adjust the maize posture in the filling zone, achieving stable filling of the seed-metering device with a low population of seeds in the seed chamber. EDEM software is used to simulate and analyse the disturbance caused by three types of seed-metering discs and the average kinetic energy in the filling zone as the evaluation criterion. A test platform for seed-metering device of maize plot was constructed, with the qualified index, multiple index, and missing index as evaluation criteria. A full-factorial experiment was conducted with rotation speed of the seed-metering disc, air pressure, and types of seed-metering discs as factors, determining the optimal seed-metering disc for seeding performance. The results indicated that under conditions of low seed population in the seeding chamber, with air pressures ranging from −1.5 to −2.5 kPa and seed-metering disc speeds between 1.16 and 3.49 rad s⁻¹, the seed-metering device with linear disturbance exhibited a multiple index of &lt;6.25% and a missing index of &lt;3.46%. Additionally, the qualified index consistently reached 90.29%. These evaluation criteria meet the standards, demonstrating effective seeding capabilities.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 221-240"},"PeriodicalIF":4.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311072","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":"Positioning of mango picking point using an improved YOLOv8 architecture with object detection and instance segmentation","authors":"Hongwei Li ,&nbsp;Jianzhi Huang ,&nbsp;Zenan Gu ,&nbsp;Deqiang He ,&nbsp;Junduan Huang ,&nbsp;Chenglin Wang","doi":"10.1016/j.biosystemseng.2024.09.015","DOIUrl":"10.1016/j.biosystemseng.2024.09.015","url":null,"abstract":"<div><div>Positioning of mango picking points is a crucial technology for the realisation of automated robotic mango harvesting. Herein, this study reported a visualised end-to-end system for mango picking point positioning using improved YOLOv8 architecture with object detection and instance segmentation, as well as an algorithm of picking point positioning. At first, the improved YOLOv8n model, incorporating the BiFPN structure and the SPD-Conv module, was utilised to enhance the detection performance of mango fruits and stems. This model achieved a detection precision of 98.9% in fruits and 97.1% in stems, with recall of 99.5% and 94.6% respectively. Then, the YOLOv8n-seg model was used for segment the stem ROI (Region of interest), leading to 81.85% in MIoU and 88.69% in mPA. Finally, a skeleton line of the stem region was obtained on the basis of the segmentation image, and a picking point positioning algorithm was developed to determine the coordinates of the optimal picking point. Subsequently, the positioning success rate of coordinates, absolute errors, and relative errors were calculated by comparing the automatic positioned coordinates with the manually positioned stem region. Experimental results indicated that this study achieved an average positioning success rate of 92.01%, with an average absolute error of 4.93 pixels and an average relative error of 13.11%. Additionally, the average processing time for processing 640 images using the picking point positioning system is 72.75 ms. This study demonstrates the reliability and effectiveness of positioning mango picking points, laying the technological basis for the automated harvesting of mango fruits.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 202-220"},"PeriodicalIF":4.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311071","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":"Laser Doppler vibrometer enables in-situ monitoring of peach firmness","authors":"Dachen Wang ,&nbsp;Yilei Hu ,&nbsp;Jiaqi Xiong ,&nbsp;Yibin Ying ,&nbsp;Ce Yang ,&nbsp;Di Cui","doi":"10.1016/j.biosystemseng.2024.09.013","DOIUrl":"10.1016/j.biosystemseng.2024.09.013","url":null,"abstract":"<div><div>Fruit firmness is a measure of the edible quality and maturity of peaches. In-situ monitoring of peach firmness can aid in fruit quality control and determining the optimal harvest time according to market demand. In this study, a non-contact acoustic vibration-based method was proposed for in-situ monitoring of fruit firmness of on-tree peaches. A new design of a compressed air excitation unit was constructed to impact the peach on the tree and a laser Doppler vibrometer was adopted to measure the acoustic vibration response (AVR) of the peach. To isolate the vibration information characterising fruit firmness, the AVR was firstly pre-processed by the wavelet threshold denoising method and then analysed by the autoregressive method to acquire the power spectral density (PSD) of the peach. For effectively extracting vibration features from the PSD to predict peach firmness, a novel one-dimensional convolutional neural network (CNN_m) with multiscale perceptual fields was constructed. The performance of CNN_m was compared with those of partial least squares regression, support vector regression models, and a single-branch 1D-CNN model with the mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (<em>R</em>^<em>2</em>), and residual prediction deviation (<em>RPD</em>). The results indicated that the proposed method enabled in-situ monitoring of peach firmness and the established CNN_m model performed better than other models in predicting peach firmness (<span><math><mrow><msubsup><mi>R</mi><mi>P</mi><mn>2</mn></msubsup></mrow></math></span> = 0.813, MAEP = 1.636 N mm⁻¹, RMSEP = 2.501 N mm⁻¹, and <span><math><mrow><msub><mrow><mi>R</mi><mi>P</mi><mi>D</mi></mrow><mi>P</mi></msub></mrow></math></span> = 2.334).</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 191-201"},"PeriodicalIF":4.4,"publicationDate":"2024-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311070","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":"A new removal method of yellow-rotten leaf for hydroponic lettuce with the flipping-tearing-twisting trajectory and its parameters optimisation","authors":"Yidong Ma ,&nbsp;Chong Qi ,&nbsp;Liming Zhou ,&nbsp;Xin Jin ,&nbsp;Bo Zhao ,&nbsp;Xinping Li","doi":"10.1016/j.biosystemseng.2024.09.010","DOIUrl":"10.1016/j.biosystemseng.2024.09.010","url":null,"abstract":"<div><p>To intelligently remove the yellow-rotten leaf of hydroponic lettuce, a new leaf removal method was proposed. The lettuce position was adjusted for yellow-rotten leaf removal according to the visual recognition and localisation, and then the adsorbed yellow-rotten leaf was lifted by air pipes. Finally, the leaf was clamped and removed along the flipping-tearing-twisting trajectory. The adsorbing pressure, adsorbing position, and clamping position for yellow-rotten leaf removal were confirmed by the adsorbing and stretching tests. To improve the leaf removal success rate, the tearing angle, flipping angle, and torsional time radio were optimised by Box-Behnken tests. A quadratic model for the three factors and leaf removal success rate was established to analyse the orders of significance, and the order of significance for single factor was (i) the tearing angle, (ii) the flipping angle, and (iii) the torsional time radio. The order of significance for interaction terms was (i) the flipping angle and tearing angle, and (ii) the flipping angle and torsional time ratio. The solved optimal combination of factors was a flipping angle of 100.5°, a tearing angle of 131.0°, and a torsional time ratio of 0.68, which gave the maximum leaf removal success rate. The optimal combination of factors was verified, and the leaf removal process was shot by high speed camera. The verification tests showed that the maximum leaf removal success rate was 82.8%, and the leaf removal process took 6.58 s, meeting the requirements of yellow-rotten leaf removal for hydroponic lettuce.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 175-190"},"PeriodicalIF":4.4,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272118","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":"Impact damage evolution rules of maize kernel based on FEM","authors":"Han Tang ,&nbsp;Guixuan Zhu ,&nbsp;Zhiyuan Sun ,&nbsp;Changsu Xu ,&nbsp;Jinwu Wang","doi":"10.1016/j.biosystemseng.2024.09.012","DOIUrl":"10.1016/j.biosystemseng.2024.09.012","url":null,"abstract":"<div><p>The main cause of damage to maize during harvesting and processing is impact damage. This study aimed to investigate the evolution of impact damage to maize kernels under different impact velocities and orientations. Based on the damage characteristics observed in impact tests, an elastoplastic model has been established to accurately simulate the damage behaviour of maize kernels. The microscopic impact behaviour of maize kernels was presented by the finite element method. The results indicated that there were differences in the evolution of damage for different damage morphology in maize kernels. The nature of surface damage was the diffusion and reflection of stress waves, while the nature of local breakage was the concentration of tiny cracks and the release of elastic potential energy. The nature of fracture was the combined effect of compressive and tensile stresses. Meanwhile, under the surface damage, the maximum stresses in the contact area of maize kernels subjected to front orientation were 20.08 MPa, 10.71 MPa for side orientation, and 13.56 MPa for bottom orientation. Under the local breakage, the front orientation with the highest number of cracks occurred at a velocity of 27.3 m s⁻¹, while for the side orientation, it occurred at 24.6 m s⁻¹, and for the bottom orientation, it occurred at 26.2 m s⁻¹. The results can be extended to the study of impact damage in irregularly shaped grains, which was beneficial for controlling product quality and optimising the design of relevant mechanical parameters in agricultural engineering and food engineering fields.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 162-174"},"PeriodicalIF":4.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272117","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":"Evaluation of a hyperspectral image pipeline toward building a generalisation capable crop dry matter content prediction model","authors":"Ioannis Malounas,&nbsp;Borja Espejo-Garcia,&nbsp;Konstantinos Arvanitis,&nbsp;Spyros Fountas","doi":"10.1016/j.biosystemseng.2024.09.009","DOIUrl":"10.1016/j.biosystemseng.2024.09.009","url":null,"abstract":"<div><p>Hyperspectral imaging has proven to be a reliable technique for estimating dry matter, a common variable when considering the quality of the fresh produce. However, developing models capable of generalising across different crops is challenging. In this study, several pipelines were explored towards achieving a robust and accurate generic regression model were evaluated and the development of Automatic Relevance Determination (ARD) and Partial Least Squares (PLS) algorithms for fruit and vegetable dry matter estimation. The models were built using a VIS-NIR dataset that includes both fruit and vegetables, namely, apples, broccoli and leek (n = 779). The PLS regression model obtained Root Mean Square on Prediction (RMSEP) = 0.0137, outperforming ARD regression (RMSEP = 0.0140) on a 10x5-fold cross-validation protocol. The evaluated preprocessing techniques affect the two regression algorithms differently, with the best results achieved when the pipeline was used without feature extraction. Overall, the pipeline using either ARD or PLS regression shows strong performance and generalisation for Visible-Near Infrared (VIS-NIR)-based dry matter estimation across diverse fruits and vegetables.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 153-161"},"PeriodicalIF":4.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142241690","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":"In situ determination of soybean leaves nutritional status by portable X-ray fluorescence: An initial approach for data collection and predictive modelling","authors":"Thainara Rebelo da Silva ,&nbsp;Eduardo de Almeida ,&nbsp;Tiago Rodrigues Tavares ,&nbsp;Fábio Luiz Melquiades ,&nbsp;Murilo Mesquita Baesso ,&nbsp;Rachel Ferraz de Camargo ,&nbsp;Marcos Henrique Feresin Gomes ,&nbsp;Hudson Wallace Pereira de Carvalho","doi":"10.1016/j.biosystemseng.2024.09.011","DOIUrl":"10.1016/j.biosystemseng.2024.09.011","url":null,"abstract":"<div><p>X-ray fluorescence <strong>(</strong>XRF) analyses are fast, clean, non-destructive, and compatible with on-field operations, which are some advantages over traditional determinations using coupled plasma optical emission spectroscopy (ICP-OES). The aim of this study was to advance <em>in situ</em> XRF approaches for assessing the nutritional status of soybean leaves (<em>i.e.</em>, P, S, K, Ca, Mn, Fe, Cu and Zn). More specifically, we propose a protocol to ensure accuracy of in-field analysis and then evaluate the predictive performance of XRF via different data modelling strategies for macro- and micronutrient determination. Therefore, the XRF sensor dwell time of 60 s and the maximum time of 5 min were determined for the analysis of the leaves after leaf abscission, taking into account the influence of moisture loss on the signal intensity of the lighter elements. Regarding the predictive performance of XRF data for nutrients determination, multiple linear regression (MLR) models resulted in lower root mean square errors (RMSE) for P (433 mg kg⁻¹), S (204 mg kg⁻¹) and K (1957 mg kg⁻¹); Partial least squares regression (PLS) for Ca (519 mg kg⁻¹); and simple linear regression (SLR) for Mn (9 mg kg⁻¹), Fe (18 mg kg⁻¹), Zn (5 mg kg⁻¹). The different modelling strategies exhibited equivalent RMSE for Cu (2 mg kg⁻¹). These prediction errors are within a ±20% range, demonstrating that the <em>in situ</em> protocols developed in this research are useful for predicting the nutrients concentration in soybean leaves. Our study shows the possibility of using the <em>in situ</em> XRF sensor for the rapid and practical nutrients determination in soybean leaves, presenting good potential as a crop diagnosis tool.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 143-152"},"PeriodicalIF":4.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142241689","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":"In ovo sexing of chickens: Evaluating volatile organic compounds analysis techniques and daily prediction performance from the onset of incubation","authors":"Matthias Corion ,&nbsp;Miguel Portillo-Estrada ,&nbsp;Simão Monteiro Belo dos Santos ,&nbsp;Nadia Everaert ,&nbsp;Jeroen Lammertyn ,&nbsp;Maarten Hertog ,&nbsp;Bart De Ketelaere","doi":"10.1016/j.biosystemseng.2024.08.013","DOIUrl":"10.1016/j.biosystemseng.2024.08.013","url":null,"abstract":"<div><p>In ovo sexing identifies chicken embryo sex before or during incubation to avoid euthanising male chicks after hatching, enhancing animal welfare in the laying hen industry. Recently, researchers demonstrated the potential for non-invasive and early in ovo sexing through the analysis of volatile organic compounds (VOCs) emitted by eggs. However, a knowledge gap remains in understanding prediction model robustness, the efficacy of faster acquisition techniques, and day-to-day performance. In this study, two experiments were performed to fill these gaps. In Experiment 1, passive VOC extractions were performed on 110 eggs on incubation day 10 using sampling bags employing headspace sorptive extraction-gas chromatography-mass spectrometry (HSSE-GC-MS), proton transfer reaction-time-of-flight-mass spectrometry (PTR-TOF-MS), and selected ion flow tube-mass spectrometry (SIFT-MS). Prediction models were built using partial least squares-discriminant analysis (PLS-DA) and variable selection methods. As a result, prediction accuracies ranged from 57.6 % to 61.4 %, indicating no significant difference between the devices and highlighting the need for further optimisations. In Experiment 2, passive VOC samplings were performed on 42 eggs in glass jars during the initial 12 days of incubation using HSSE-GC-MS. Consequently, the optimised setup yielded higher accuracies ranging from 63.1 % (on day 0) to 71.4 % (on days 4, 6, and 12), revealing VOCs consistently elevated in relative abundance for a specific sex, and overall VOC abundance was higher in male embryos. Suggestions for future experiments to increase the accuracy of VOC in ovo sexing include active sampling with inert materials, expanding sample sets, and targeting consistent compounds.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 109-118"},"PeriodicalIF":4.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142172928","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":"Experimental study on temperature difference between the interior and exterior of the vehicle transporting weaner pigs","authors":"Guoxing Chen ,&nbsp;Cecilie Kobek-Kjeldager ,&nbsp;Line D. Jensen ,&nbsp;Jens K. Kristensen ,&nbsp;Marianne Kaiser ,&nbsp;Karen Thodberg ,&nbsp;Guoqiang Zhang ,&nbsp;Li Rong ,&nbsp;Mette S. Herskin ,&nbsp;Leslie Foldager","doi":"10.1016/j.biosystemseng.2024.09.001","DOIUrl":"10.1016/j.biosystemseng.2024.09.001","url":null,"abstract":"<div><p>Transporting pigs poses a significant challenge in maintaining proper interior thermal conditions. This study conducted 36 field trials run in Denmark and collected data from a certified livestock vehicle, during journeys of 8 h and 23 h respectively. This study aims to investigate the air temperature inside a livestock vehicle during the transportation and the influence of five factors on DT (difference in air temperature between interior of the vehicle and exterior): compartment location, deck height, height of openings for natural ventilation, wind speed and vehicle speed. The compartment location was the most important influencing factor of interior air temperature. The maximum percentage of time when air temperature exceeded 30 °C was 13.6% observed in the front compartment of trailer. The maximum difference in mean DT between the front and rear compartments at the same deck was 11.0 ± 0.67 °C occurred in the lorry. The maximum differences in mean DT between the two investigated deck heights were 1.2 ± 0.39 °C in the lorry (70 vs. 90 cm) and 0.9 ± 0.26 °C in the trailer (60 vs. 80 cm), respectively. The DT decreased with increasing height of opening for natural ventilation and wind speed, while the DT was insensitive to vehicle speed. Extra sensors installed on the front partition wall during the last 4 journeys showed significant temperature variability (up to 12 °C) within compartment. Further studies identifying the efficient monitoring of thermal condition and prompt interior environmental control are needed in vehicles for pig transport.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 119-131"},"PeriodicalIF":4.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1537511024002034/pdfft?md5=c308b5ba444f59fde584485779e961ac&pid=1-s2.0-S1537511024002034-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142228853","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}