Biosystems Engineering最新文献

{"title":"Effectiveness of cooling interventions on heat-stressed dairy cows based on a mechanistic thermoregulatory model","authors":"M. Zhou ,&nbsp;X. Tang ,&nbsp;B. Xiong ,&nbsp;P.W.G. Groot Koerkamp ,&nbsp;A.J.A. Aarnink","doi":"10.1016/j.biosystemseng.2024.06.003","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.06.003","url":null,"abstract":"<div><p>Addressing heat stress in dairy farming is a substantial challenge, and there is an increasing need for efficient cooling systems, even in regions with moderate climates. Accurately predicting the efficacy of diverse cooling options under different climatic conditions is crucial for reducing heat stress in modern high-producing dairy cows, aligning with sustainability goals. This study assessed the effectiveness and feasibility of different cooling measures, including fans, sprinklers with fans, and evaporative air cooling, using a dynamic thermoregulatory model. This 3-node dynamic model was developed based on recent animal data simulating the processes of dairy cows' physiological regulation and heat dissipation under various environmental conditions. The cooling methods were based on two principles: enhancing heat loss from cows using fans with/without sprinklers; lowering the ambient temperature by evaporative air cooling. The predicted results were discussed and partly validated using the experimental data from the literature. The predictions indicated that fan cooling alone was effective in ambient temperatures below 26 °C, while higher temperatures required a combination of fans and sprinklers for effective heat stress alleviation. Consideration of individual cow characteristics and environmental factors, including fan speed and wetting area, is crucial for optimal cooling. In regions with high relative humidity, evaporative air cooling could be counterproductive to some extent. The model's predictions largely aligned with experimental data, demonstrating its capability to forecast cooling effects under various climatic conditions. Future model improvements included refining calculations for water holding capacity, wetted skin area, and dry time, depending on the influence of spraying time and rate.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1537511024001375/pdfft?md5=e7291d2646f743319db1a4a5180643ae&pid=1-s2.0-S1537511024001375-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315069","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":"Blood vitamin A level prediction in Japanese black cattle based on chromatic and dynamic eye features using double imaging system","authors":"Nanding Li ,&nbsp;Dimas Firmanda Al Riza ,&nbsp;Otieno Samuel Ouma ,&nbsp;Mizuki Shibasaki ,&nbsp;Wulandari ,&nbsp;Moriyuki Fukushima ,&nbsp;Tateshi Fujiura ,&nbsp;Yuichi Ogawa ,&nbsp;Naoshi Kondo ,&nbsp;Tetsuhito Suzuki","doi":"10.1016/j.biosystemseng.2024.05.016","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.016","url":null,"abstract":"<div><p>Proactive dietary control of blood vitamin A levels is crucial for the intramuscular fat development in cattle worldwide. However, cattle become susceptible to either vitamin A deficiency or excessive state during fattening stage, influencing cattle performance, health, and beef quality. A good understanding and modelling of vitamin A levels throughout the whole cattle growth phase is needed. This study aims to assist in controlling the fattening process for production of high-marbling beef through a non-invasive monitoring of blood vitamin A levels. Using an automatic double imaging system, this study captured both surface and fundus images of cattle eyes, and based on this, predicted blood vitamin A levels through a novel dynamic analysis of 29 eye features. The best PLS model had a prediction of R² = 0.82 and RMSE = 6.50 IU·dL⁻¹ (equivalent to 0.02 μg · mL⁻¹), which is of a clinically meaningful accuracy. This system can greatly facilitate vitamin A levels management in cattle raising, contributing to the effective control of beef marbling for both the market and industry.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141303756","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":"Optimising maize threshing by integrating DEM simulation and interpretive enhanced predictive modelling","authors":"Xuwen Fang,&nbsp;Jinsong Zhang,&nbsp;Xuelin Zhao,&nbsp;Li Zhang,&nbsp;Deyi Zhou,&nbsp;Chunsheng Yu,&nbsp;Wei Hu,&nbsp;Qiang Zhang","doi":"10.1016/j.biosystemseng.2024.06.001","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.06.001","url":null,"abstract":"<div><p>Maize threshing is a complex and dynamic process, and optimisation of operating parameters is essential to improve threshing quality and efficiency. In this study, machine learning was combined with interpretability analysis to investigate the dynamic effects of operating parameters on maize threshing quality and to optimise the threshing process. The maize cob model used to simulate threshing was validated by stacking angle and tensile test. Real-time drum operating parameters and threshing quality data obtained through Discrete Element Method (DEM) threshing simulation were used to train a threshing quality prediction network. The prediction accuracy was improved by incorporating an attention mechanism into the Long Short-Term Memory (LSTM) model with an optimised Root Mean Square Error (RMSE) of 0.0041. The global feature importance and dynamic Shapley Additive Explanations (SHAP) value analyses demonstrated that rotational speed is a key determinant of unthreshed and damaged rates and that its effect varies significantly at different stages of the threshing process. Guided by these analyses, a staged speed adjustment experiment was conducted. Specifically, an increase in rotational speed during the initial threshing phase markedly lowered the initial unthreshed rate for medium and high-speed groups to 6.63% and 2.73%, respectively, a significant improvement over the 67.70% observed in the low-speed group. The final damage rate in the high-speed group decreased by 9.79% relative to the low-speed group. This dynamic analysis approach provides a novel paradigm for optimising complex agricultural processes under varying conditions, offering interpretable insights for precise process control and improvement.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141292068","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":"Machine/deep learning techniques for disease and nutrient deficiency disorder diagnosis in rice crops: A systematic review","authors":"Mayuri Sharma ,&nbsp;Chandan Jyoti Kumar ,&nbsp;Dhruba K. Bhattacharyya","doi":"10.1016/j.biosystemseng.2024.05.014","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.014","url":null,"abstract":"<div><p>Disease and nutrient deficiency disorders significantly impact the productivity of rice crops. Timely identification of these conditions is essential for effective mitigation of potential crop damage. To address this challenge, considerable research is happening in the field of rice crop monitoring and maintenance, using cutting-edge techniques like Machine learning (ML)/Deep learning (DL). This study aims to address critical aspects of the research landscape, including publication trends, data modalities, ML/DL models, pre-processing methods, segmentation techniques, and feature selection approaches in the context of rice crop's health. By presenting both research findings and existing gaps, this systematic literature review (SLR) offers valuable insights to direct future research endeavours in this domain. Our investigation involves a comprehensive review of articles sourced from Scopus, IEEE Xplore, Science Direct and Google Scholar resulting in a dataset of 91 unique articles spanning from the year 2013–2023. Following rigorous selection criteria, these 91 articles have been considered for in-depth analysis. Through an extensive examination of this corpus, our study seeks to provide answers to seven key questions pertaining to the past, present, and future directions of research of ML/DL application in rice crop health monitoring and disease/disorder diagnosis. The review adheres to the agricultural science-based PRISMA systematic review methodology and incorporates statistical analysis to explore relationships among variables such as dataset sample size, experimental accuracy, and classification models employed in various studies.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141286127","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":"Continuous monitoring the Queen loss of honey bee colonies","authors":"Yuntao Lu ,&nbsp;Wei Hong ,&nbsp;Yu Fang ,&nbsp;Ying Wang ,&nbsp;Zhenguo Liu ,&nbsp;Hongfang Wang ,&nbsp;Chuanqi Lu ,&nbsp;Baohua Xu ,&nbsp;Shengping Liu","doi":"10.1016/j.biosystemseng.2024.05.017","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.017","url":null,"abstract":"<div><p>The queen bee is the core member of a bee colony, and her loss will pose a great threat to the survival of the colony that may cause colony collapse. However, the process by which queen bee loss affects the internal social state of the bee colony remains unclear. In this paper, we used a multi-sensors system to continually monitor colonies with queen loss and regularly checked their biological status. Our results show that the queen loss initially caused a rapid decrease in brood rearing and changed the foraging strategy of the colony, leading to an increase in food storage. Also the population decline is difficult to reverse in a short time, even if the queen is naturally replaced. This study emphasises the impact of queen bee loss on the operation of the bee colony social system, and elucidates the interconnectedness of the bee colony social system.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141249600","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":"Non-contact leaf wetness measurement with laser-induced light reflection and RGB imaging","authors":"Zhangkai Wu ,&nbsp;Zhichong Wang ,&nbsp;Klaus Spohrer ,&nbsp;Steffen Schock ,&nbsp;Xiongkui He ,&nbsp;Joachim Müller","doi":"10.1016/j.biosystemseng.2024.05.019","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.019","url":null,"abstract":"<div><p>Leaf wetness duration is a crucial factor in plant disease management. Current optical methods use standard RGB images to classify leaf wetness as a binary problem, i.e., wet or dry. Green leaves absorb red light, whereas water reflects it. Based on this difference, an experimental platform was built to semi-automatically measure droplet deposition on grape leaves while capturing red laser images using an RGB camera. The setup measured changes in leaf mass and area of scanned leaves to determine the water mass per leaf area as a measure of leaf wetness. A sprayer was used to apply water droplets to the leaves. As the amount of deposited water increased, the mean red channel intensity decreased, with more bright spots in the images. These bright spots were more distinguishable as droplets in the green channel. Segmented leaf area, mean red channel intensity, and the number of identified droplets were used as image features. A generalised additive model was employed to predict the leaf wetness value with extracted features. The R-squared value for the prediction of the validation dataset was 0.71. Image resolution and leaf orientation were identified as factors that influenced the model accuracy. The measurement method introduced in this study shows potential for accurately quantifying leaf wetness, and implies that in practice detecting leaf wetness can be integrated into a multi-classification problem, thereby broadening the potential applications of optical methods.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1537511024001284/pdfft?md5=2cb190952bd9b0e118d77ffb4e583ebe&pid=1-s2.0-S1537511024001284-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141239637","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":"Efficient two-way fluid–structure interaction simulation for performance prediction of pressure-compensating emitter","authors":"Byung-hun Seo ,&nbsp;Sangik Lee ,&nbsp;Jong-hyuk Lee ,&nbsp;Dong-su Kim ,&nbsp;Ye-jin Seo ,&nbsp;Dong-woo Kim ,&nbsp;Won Choi","doi":"10.1016/j.biosystemseng.2024.05.015","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.015","url":null,"abstract":"<div><p>Drip irrigation using a high-performance pressure-compensating (PC) emitter is one of the essential components for precision agriculture, and it is necessary to accurately predict its performance prior to design. In this study, an efficient two-way fluid–structure interaction (FSI) simulation model was developed and verified through an enlarged model experiment. The computational fluid dynamics (CFD) and computational solid mechanics (CSM) models of the FSI simulation were systematically verified, and a calibration method for the overestimated flow rate in the re-rising range was applied. The CFD model was determined to be the shear stress transport turbulence model, and the CSM model was determined to be the Ogden hyperelastic model for the PC emitter. The minimum prediction error for the flow rate was 7.93%, which was within 10% for all cases. The simulation model demonstrated its efficiency by analysing the performance of a single PC emitter with an average total analysis time of 18.6 h. In addition, by comparing various cases according to the design parameters, it is considered that the hardness of the diaphragm has a significant impact on the design of low-pressure PC emitters. The simulation model of this study can accurately predict the performance of PC emitter under specific conditions, yet improvement of simulation model is required to be applied in design optimisation. Future studies may benefit from combining an improved FSI simulation with a surrogate model to further enhance optimisation efforts.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141242365","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":"Threshing cylinder unbalance detection using a signal extraction method based on parameter-adaptive variational mode decomposition","authors":"Zhiwu Yu ,&nbsp;Yaoming Li ,&nbsp;Xiaoxue Du ,&nbsp;Yanbin Liu","doi":"10.1016/j.biosystemseng.2024.05.010","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.010","url":null,"abstract":"<div><p>The threshing cylinder will wear and deform during the threshing process, causing dynamic balance problems. The combine harvester has multiple vibration excitation sources and a complex vibration environment, making it challenging to extract weak unbalanced signals from strong background noise. A novel three-step filtering framework is proposed in this paper. A zero phase filter was used as the pre-processing layer to filter out the high frequency components in the original signal and reduce the number of parameter-adaptive variational mode decompositions (PAVMD) needed. The PAVMD was used to decompose the non-stationary vibration signal before Adaptive Neuron Linear (Adaline) function was used to fit sinusoidal signal parameters. A measurement index, termed the correlation amplitude (CA) index, is constructed. The parameterisation of PAVMD was guided by the CA index, and the modal component of the unbalanced fault features were located. The simulation and real cylinder signals proved that the proposed method could effectively extract unbalanced signals under noise interference, and the unbalance was identified accurately by the influence coefficient method. Experiments on a threshing cylinder showed that the amplitude identification error was &lt;24 g in single-sided unbalance identification, and the amplitude identification error was &lt;27 g in double-sided unbalance identification. The proposed method had high robustness and small identification error, especially under short-time working conditions, compared with other similar approaches.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141239662","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":"Assessment of apple bruise resistance under transient collisions through X-ray computed tomography and image processing","authors":"Yin Huang,&nbsp;Zhenwei Liang","doi":"10.1016/j.biosystemseng.2024.05.009","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.009","url":null,"abstract":"<div><p>To evaluate the resistance of apples to bruising under transient impact loads, a pendulum device was initially employed to gather collision data. Subsequently, an image acquisition and processing system was utilised to compute the apple surface bruise area, and X-ray computed tomography technology was utilised to precisely calculate the bruise volume. Based on the CT image and bruise area image analysis, the difference between bruised area and normal tissue on the apple after collision, and effects of impact energy on apple bruising volume and bruise area has been elaborated in detail. Results analysis revealed a general increase in both bruise volume and bruise area with escalating impact energy, and there is a strong correspondence between bruise volume and bruise area across different storage days and impact energies. The relationship between bruise volume and bruise area under different storage duration were also established. On the base of bruise resistance index (BRI) model utilising impact energy and bruise volume as variables, those analysis led to the establishment of a new bruise resistance index (BRI*) model employing impact energy and bruise area as independent variables. The effectiveness of BRI* model in assessing apple bruise resistance was demonstrated by comparing the corresponding relative error for bruise thresholds of BRI and BRI* under the same condition. The relative error ≤3.3% underscores the accuracy of the new model and proves the proposed BRI* model to be an efficient and rapid tool for assessing the degree of apple bruising.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141239639","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":"Enhancing spray deposition in grape canopies through the development of new prototype air-disturbance sprayers","authors":"Chenggong Yan,&nbsp;Liming Xu,&nbsp;Shuai Ma,&nbsp;Haochao Tan,&nbsp;Congcong Shen,&nbsp;Junlong Ma,&nbsp;Huineng Zhou","doi":"10.1016/j.biosystemseng.2024.05.013","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.05.013","url":null,"abstract":"<div><p>To address the challenge of uneven and inadequate deposition within the canopy and on the lower side of the leaves in vineyards spraying operations, the performance of new prototype air-disturbance sprayers was evaluated. Firstly, the optimal parameter combination under the swing type disturbance mode (SW) was determined through orthogonal analysis. Then, a multivariate variance analysis was employed to compare the performance indicators of SW with those found under the rotating type disturbance modes (anticlockwise rotating AR, and clockwise rotating CR), as well as with the blank control group. It has been confirmed that SW could increase the penetration of droplets within the canopy and obtain the optimal deposition uniformity (58.72%). This mode did not affect the canopy deposition, but it decreased the coverage of droplets on the lower side of the leaves (11.82%). AR achieved a deposition uniformity of 62.06% and could consistently ensure that the coverage of both sides of the leaf was over the threshold of 30%. However, it decreased the canopy deposition. Generally speaking, CR not only significantly increased the canopy deposition, but also improved the deposition uniformity to 60.94% (second only to SW). Although the coverage on the lower side of the leaf for CR (25.41%) has not yet reached the threshold requirement of 30%, it could be anticipated that the implementation of two-sided spraying could effectively solve this deficiency. Therefore, the future positioning of a clockwise rotating turbulence system at the airflow outlet of the air-assisted sprayer will be a valuable choice.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141239638","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}