{"title":"Design and testing of planting unit for rice dry-direct-seeding planter in cold region","authors":"Jiale Zhao, Chengliang Zhang, Yanpeng Wei, Mingzhuo Guo, Chao Chen, Chongqin Zhang, Yungan Zhang","doi":"10.25165/j.ijabe.20231604.7843","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.7843","url":null,"abstract":"Rice dry-direct-seeding technology is a time-saving, cost-saving and efficient rice cultivation technique that increases the efficiency of seeding. In order to implement the specialization, light simplicity and scale of rice production, improve the level of mechanization of the whole rice production process, and solve the problems of uneven seed furrows, uneven number of seeds sown, shallow mulching and uncompact repression that occur during the promotion and application of dry-direct-seeding for rice in the cold region of northeast China. In this paper, a planting unit for rice dry-direct-seeding planter is designed. The working principles and structural parameters of the furrow opening components, the seeding apparatus and the soil covering-pressing device are described. The mechanical model of the key components of the seeding unit was established, and the forward speed, roller diameter and compacting strength were selected as the test factors. A three-factor, five-level quadratic rotation orthogonal combination test was conducted with the seed breakage rate, seeding depth qualification rate, seeding uniformity coefficient of variation and hole grain count qualification rate as the evaluation indexes. Field performance test and test results show that: at a forward speed of 4 km/h, a roller diameter of 427 mm and a compacting strength of 48.45 kPa, the seed breakage rate was 1.31%, the sowing depth qualification rate was 9.95%, the coefficient of variation of sowing uniformity was 3.75% and the number of holes was 86.75%. This accords with the agronomic requirements of dry-direct-seeding for rice and implements a combination of superior agronomy and modern farm machinery. Keywords: rice, dry-direct-seeding, planting unit, structural design, testing research DOI: 10.25165/j.ijabe.20231604.7843 Citation: Zhao J L, Zhang C L, Wei Y P, Guo M Z, Chen C, Zhang C Q, et al. Design and testing of planting unit for rice dry-direct-seeding planter in cold region. Int J Agric & Biol Eng, 2023; 16(4): 76-84","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135659788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin Zhao, Wanli Wang, Long Wen, Zhibo Chen, Sixian Wu, Kun Zhou, Mengyao Sun, Lanjun Xu, Bingbing Hu, Caicong Wu
{"title":"Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles","authors":"Xin Zhao, Wanli Wang, Long Wen, Zhibo Chen, Sixian Wu, Kun Zhou, Mengyao Sun, Lanjun Xu, Bingbing Hu, Caicong Wu","doi":"10.25165/j.ijabe.20231604.8039","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.8039","url":null,"abstract":"Digital twins can improve the level of control over physical entities and help manage complex systems by integrating a range of technologies. The autonomous agricultural machine has shown revolutionary effects on labor reduction and utilization rate in field works. Autonomous vehicles in precision agriculture have the potential to improve competitiveness compared to current crop production methods and have become a research hotspot. However, the development time and resources required in experiments have limited the research in this area. Simulation tools in unmanned farming that are required to enable more efficient, reliable, and safe autonomy are increasingly demanding. Inspired by the recent development of an open-source virtual simulation platform, this study proposed an autoware-based simulator to evaluate the performance of agricultural machine guidance based on digital twins. Oblique photogrammetry using drones is used to construct three-dimensional maps of fields at the same scale as reality. A communication format suitable for agricultural machines was developed for data input and output, along with an inter-node communication methodology. The conversion, publishing, and maintenance of multiple coordinate systems were completed based on ROS (Robot Operating System). Coverage path planning was performed using hybrid curves based on Bézier curves, and it was tested in both a simulation environment and actual fields with the aid of Pure Pursuit algorithms and PID controllers. Keywords: autoware, simulation platform, autonomous agricultural vehicle, digital twin; autonomous robots DOI: 10.25165/j.ijabe.20231604.8039 Citation: Zhao X, Wang W L, Wen L, Chen Z B, Wu S X, Zhou K, et al. Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles. Int J Agric & Biol Eng, 2023; 16(4): 185-190.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135660287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maohua Xiao, Ye Ma, Chen Wang, Junyun Chen, Yejun Zhu, Petr Bartos, Guosheng Geng
{"title":"Design and experiment of fuzzy-PID based tillage depth control system for a self-propelled electric tiller","authors":"Maohua Xiao, Ye Ma, Chen Wang, Junyun Chen, Yejun Zhu, Petr Bartos, Guosheng Geng","doi":"10.25165/j.ijabe.20231604.8116","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.8116","url":null,"abstract":"The research on the self-propelled electric tiller is vital for further improving the quality and efficiency of greenhouse rotary tillage operation, reducing the work intensity and operation risk of operators, and achieving environmentally friendly characteristics. Most of the existing self-propelled tillers rely on manual adjustment of the tillage depth. Moreover, the consistency and stability of the tillage depth are difficult to guarantee. In this study, the automatic control method of tillage depth of a self-propelled electric tiller is investigated. A method of applying the fuzzy PID (Proportional Integral Derivative) control method to the tillage depth adjustment system of a tiller is also proposed to realize automatic control. The system uses the real-time detection of the resistance sensor and angle sensor. The controller runs the electronically controlled hydraulic system to adjust the force and position comprehensively. The fuzzy control algorithm is used in the operation error control to realize the double-parameter control of the tillage depth. The simulation and experimental verification of the system are conducted. Results show that the control system applying fuzzy PID can improve the soil breaking rate by 3% in the operation process based on reducing the stability variation of tillage depth by 24%. The control strategy can reach the set value of tillage depth quickly and accurately. It can also meet the requirement of tillage depth consistency during the operation. Keywords: fuzzy PID, self-propelled electric tiller, tillage depth, electro-controlled hydraulic system, comprehensive adjustment of force and position DOI: 10.25165/j.ijabe.20231604.8116 Citation: Xiao M H, Ma Y, Wang C, Chen J Y, Zhu Y J, Bartos P, et al. Design and experiment of fuzzy-PID based tillage depth control system for a self-propelled electric tiller. Int J Agric & Biol Eng, 2023; 16(4): 116-125.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135660292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of black soil compaction with driver-agricultural machinery-soil system under corn sowing with high-power tractor in Northeast China","authors":"Xiao Yang, Zhiqiang Zhai, Weijie Guo, Wenjie Li, Minli Yang, Zhenghe Song","doi":"10.25165/j.ijabe.20231604.7284","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.7284","url":null,"abstract":"Soil compaction leads to crop yield reduction in Northeast of China. The interaction mechanism of driver-agricultural machinery-black soil is not clear. A comprehensive field experiment of 4 hm2 of maize seeding was carried out in Baiquan County Cooperative. The results showed that the average increase rates of soil compaction before and after sowing were 118.82% and 71.02%. The SEM showed that waist fatigue had the greatest impact on soil compaction, and the unit fatigue of waist caused 1.51 and 1.27 unit compactions to the soil at the depths of 10 cm and 20 cm. The neck, waist, arm and leg fatigue of drivers increased the surface soil compaction by 1.83, 1.76, 1.78 and 1.55 units, and the deep soil compaction by 1.65, 1.58, 1.60 and 1.40 units. The results can provide a reference for the integration of human factor efficiency and conservation tillage. Keywords: agriculture ergonomics, structural equation model, black soil compaction, sowing, high-power tractor DOI: 10.25165/j.ijabe.20231604.7284 Citation: Yang X, Zhai Z Q, Guo W J, Li W J, Yang M L, Song Z H. Analysis of black soil compaction with driver-agricultural machinery-soil system under corn sowing with high-power tractor in Northeast China. Int J Agric & Bio Eng, 2023; 16(4): 168-173","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135660484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mazhar H. Tunio, Jianmin Gao, Tarek M. K. Mohamed, Fiaz Ahmad, Irfan Abbas, Sher Ali Shaikh
{"title":"Comparison of nutrient use efficiency, antioxidant assay, and nutritional quality of butter-head lettuce (Lactuca sativa L.) in five cultivation systems","authors":"Mazhar H. Tunio, Jianmin Gao, Tarek M. K. Mohamed, Fiaz Ahmad, Irfan Abbas, Sher Ali Shaikh","doi":"10.25165/j.ijabe.20231601.6794","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.6794","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"2 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80425572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chengqi Liu, Haijian Ye, Shuhan Lu, Zhan Tang, Zhao Bai, Lei Diao, Longhe Wang, Lin Li
{"title":"Skeleton extraction and pose estimation of piglets using ZS-DLC-PAF","authors":"Chengqi Liu, Haijian Ye, Shuhan Lu, Zhan Tang, Zhao Bai, Lei Diao, Longhe Wang, Lin Li","doi":"10.25165/j.ijabe.20231603.6930","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.6930","url":null,"abstract":"The accurate identification of various postures in the daily life of piglets that are directly reflected by their skeleton morphology is necessary to study the behavioral characteristics of pigs. Accordingly, this study proposed a novel approach for the skeleton extraction and pose estimation of piglets. First, an improved Zhang-Suen (ZS) thinning algorithm based on morphology was used to establish the chain code mechanism of the burr and the redundant information deletion templates to achieve a single-pixel width extraction of pig skeletons. Then, body nodes were extracted on the basis of the improved DeepLabCut (DLC) algorithm, and a part affinity field (PAF) was added to realize the connection of body nodes, and consequently, construct a database of pig behavior and postures. Finally, a support vector machine was used for pose matching to recognize the main behavior of piglets. In this study, 14 000 images of piglets with different types of behavior were used in posture recognition experiments. Results showed that the improved algorithm based on ZS-DLC-PAF achieved the best thinning rate compared with those of distance transformation, medial axis transformation, morphology refinement, and the traditional ZS algorithm. The node tracking accuracy reached 85.08%, and the pressure test could accurately detect up to 35 nodes of 5 pigs. The average accuracy of posture matching was 89.60%. This study not only realized the single-pixel extraction of piglets’ skeletons but also the connection among the different behavior body nodes of individual sows and multiple piglets. Furthermore, this study established a database of pig posture behavior, which provides a reference for studying animal behavior identification and classification and anomaly detection. Keywords: piglets, skeleton extraction, pose estimation, Zhang-Suen, DeepLabCut, Part affinity field DOI: 10.25165/j.ijabe.20231603.6930 Citation: Liu C Q, Ye H J, Lu S H, Tang Z, Bai Z, Diao L, et al. Skeleton extraction and pose estimation of piglets using ZS-DLC-PAF. Int J Agric & Biol Eng, 2023; 16(3): 180–193.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135357309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Vision-based measuring method for individual cow feed intake using depth images and a Siamese network","authors":"Xinjie Wang, Baisheng Dai, Xiaoli Wei, Weizheng Shen, Yonggen Zhang, Benhai Xiong","doi":"10.25165/j.ijabe.20231603.7985","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.7985","url":null,"abstract":"Feed intake is an important indicator to reflect the production performance and disease risk of dairy cows, which can also evaluate the utilization rate of pasture feed. To achieve an automatic and non-contact measurement of feed intake, this paper proposes a method for measuring the feed intake of cows based on computer vision technology with a Siamese network and depth images. An automated data acquisition system was first designed to collect depth images of feed piles and constructed a dataset with 24 150 samples. A deep learning model based on the Siamese network was then constructed to implement non-contact measurement of feed intake for dairy cows by training with collected data. The experimental results show that the mean absolute error (MAE) and the root mean square error (RMSE) of this method are 0.100 kg and 0.128 kg in the range of 0-8.2 kg respectively, which outperformed existing works. This work provides a new idea and technology for the intelligent measuring of dairy cow feed intake. Keywords: computer vision, Siamese network, cow feed intake, depth image, precision livestock farming DOI: 10.25165/j.ijabe.20231603.7985 Citation: Wang X J, Dai B S, Wei X L, Shen W Z, Zhang Y G, Xiong B H. Vision-based measuring method for individual cow feed intake using depth images and a Siamese network. Int J Agric & Biol Eng, 2023; 16(3): 233–239.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135358864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuanyuan Shao, Hongdong Zhang, Guantao Xuan, Tao Zhang, Xianlu Guan, Fuhui Wang
{"title":"Simulation and experiment of a transplanting mechanism for sweet potato seedlings with ‘boat-bottom’ transplanting trajectory","authors":"Yuanyuan Shao, Hongdong Zhang, Guantao Xuan, Tao Zhang, Xianlu Guan, Fuhui Wang","doi":"10.25165/j.ijabe.20231603.7613","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.7613","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135361579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qizhi Yang, Lei Shi, Aiping Shi, Mingsheng He, Xiaoqi Zhao, Li Zhang, Min Addy
{"title":"Determination of key soil characteristic parameters using angle of repose and direct shear stress test","authors":"Qizhi Yang, Lei Shi, Aiping Shi, Mingsheng He, Xiaoqi Zhao, Li Zhang, Min Addy","doi":"10.25165/j.ijabe.20231603.6293","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.6293","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135361599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}