International Journal of Agricultural and Biological Engineering最新文献

{"title":"Design of a high-voltage electrostatic ultrasonic atomization nozzle and its droplet adhesion effects on aeroponically cultivated plant roots","authors":"Jianmin Gao, Yinan Guo, Mazhar Hussain Tunio, Xiangchao Chen, Zhijian Chen","doi":"10.25165/j.ijabe.20231602.7222","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231602.7222","url":null,"abstract":": In the process of aeroponics cultivation, the atomizer is one of the most important influencing factors on the cultivation process. This study presented the design of an ultrasonic atomization nozzle using contact charging and a root droplet adhesion test rig. The purpose of this study was to reveal the relationship between the main operating parameters of the high-voltage electrostatic ultrasonic atomization nozzle and the atomization effect using droplet adhesion measurements. In this study, the ultrasonic effect of nozzle was achieved by using Laval tube, and the design of the key parameters for the high-voltage electrostatic ultrasonic atomization nozzle were inlet pressure, electrostatic voltage root core electrode material and spray distance; the droplet size variation and root adhesion patterns were obtained through experiments. The best operating parameters were analyzed by using the orthogonal test method, and the droplet deposition distribution of the root system at different scales was investigated in the atomization chamber. The test results revealed that when the root core electrode material was coppe and the nozzle working parameters were at 0.4 MPa of inlet pressure, at 1.75 m the spray distance, at 12 kV of the electrostatic voltage, the root system has the highest droplet adhesion.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"3 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79001040","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":"Determination of energy use efficiency and greenhouse gas emissions in peach production","authors":"Cihan Demir, Osman Gökdoğan","doi":"10.25165/j.ijabe.20231602.7917","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231602.7917","url":null,"abstract":": The purpose of this study was to determine the energy use efficiency and greenhouse gas (GHG) emissions in peach production that took place in Kırklareli province of Turkey during the 2020-2021 production season. This study included calculations of energy input, energy output, energy use efficiency, specific energy, energy productivity, net energy, energy input types, GHG emissions and GHG ratio. Survey, observation and data calculations are related to the 2020-2021 production season. The data obtained from the study were collected from 16 different farms (reachable) through face-to-face surveys with full count method. Energy input and energy output were calculated as 19 570.58 MJ/hm 2 and 19 471.94 MJ/hm 2 , respectively. With regards to production inputs, 55.70% of the energy inputs consisted of chemical fertilizers energy (10 900.03 MJ/hm 2 ), 9.46% consisted of chemicals energy (1852.10 MJ/hm 2 ), 9.32% consisted of human labour energy (1823.13 MJ/hm 2 ), 7.65% consisted of electricity energy (1497.28 MJ/hm 2 ), 6.91% consisted of diesel fuel energy (1351.52 MJ/hm 2 ), 4.73% consisted of irrigation water energy (926.10 MJ/hm 2 ), 3.43% consisted of machinery energy (671.98 MJ/hm 2 ), 1.88% consisted of transportation energy (367.72 MJ/hm 2 ), 0.88% consisted of farmyard manure energy (171.80 MJ/hm 2 ) and 0.05% consisted of lime energy (8.94 MJ/hm 2 ). Energy use efficiency, specific energy, energy productivity and net energy were calculated as 0.99, 1.91 MJ/kg, 0.52 kg/MJ and –98.64 MJ/hm 2 , respectively. The consumed total energy input in production was classified as 28.60% direct energy, 71.40% indirect energy, 14.93% renewable energy and 85.07% non-renewable. Total GHG emissions and GHG ratio were calculated as 1683.24 kgCO 2-eq /hm 2 and 0.16 kg CO 2-eq /kg, respectively.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"18 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":"84945867","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":"Design and performance analysis of indoor calibration device for the force-measuring system of the tractor three-point hitch","authors":"Dong Dai, Du Chen, Xu Mao, Yawei Zhang, Yutong Li, Shumao Wang, Bin Zhang","doi":"10.25165/j.ijabe.20231603.7455","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.7455","url":null,"abstract":"The real-time monitoring of the load in farming by the sensor installed on the tractor's three-point hitch can effectively improve the farming efficiency and force-position combined control, reduce the compaction risk of the wheel on the soil and reduce the fuel consumption in farming process. However, the measurement and quantification of the loads on the three-point hitch have some problems remaining unresolved: testing the accuracy and reliability of a load measuring system is hard when the tractor works in a field, the mathematical model of spatial forces usually lacks a practical and effective validation, and the calibration process of the measurement system is inconvenient and incomplete while easily causing a low accuracy. Specifically, this paper builds a new spatial-force mathematical model based on the geometry of a three-point hitch. To eliminate the discrepancy of the geometric model with the actual structure and to refine the mathematical model, a calibration process is conducted by developing a calibration bench, which is equipped with a data acquisition system and a multi-parameter monitoring interface. The three-point hitch installed on this calibration bench is subject to steady-state loading. The loading force, angle of the lower drawbar, and three-component forces (three shaft pin sensors’ forces) of the three-point hitch are well measured. With applying for the measured data to calibrate the theoretical mathematic model eventually derives the resultant force from all the three-component forces, a dynamical loading bench was developed to test the calculated resultant force for the three-point hitch during the sinusoidal and randomly variant dynamical loadings tests. A hitch force measurement system is also developed to collect real-time data and calculate the resultant force of measured three-component forces through the calibrated mathematical model. The results of the dynamical loading tests show that the average relative error MRE=1.09% with an average force measurement time delay being Δt=0.5 s, the root mean square error RMSE=59.3 N, and the coefficient of determination R2=0.9903. As observed, the shape and the trend of the generated resultant force curve are basically the dynamical loading force. The dynamical loading test proves the high efficacy and reliability of the proposed indoor calibration method for calculating the load based on the three-component forces as measured on the three-point hitch. Besides, the preliminary study of the proposed method on the hitch load provides great potential to improve the indoor six-component measurement and quantification of both the force and momentum acting on the three-point hitch. Keywords: tractor, three-point hitch, hitch force calibration bench, hitch force measurement system, dynamic loading verification method DOI: 10.25165/j.ijabe.20231603.7455 Citation: Dai D, Chen D, Mao X, Zhang Y W, Li Y T, Wang S M, et al. Design and performance analysis of indoor calibration device ","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"18 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":"135357312","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":"NxO emissions in response to the irrigation lower limits under different irrigation modes in a lettuce field","authors":"Maomao Hou, Ying Xiao, Qinyuan Zhu, Jingnan Chen, Huan Huang, Qiu Jin, Lin Zhu, Fenglin Zhong","doi":"10.25165/j.ijabe.20231604.7961","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.7961","url":null,"abstract":"Irrigation has a significant impact on NxO (N2O and NO) emissions from cultivated land, yet the N2O or NO emission among the irrigation lower limits under different irrigation modes has not been well compared. In an irrigated lettuce field, three DR (drip irrigation) lower limits were designed, including 75% (DR1), 65% (DR2) and 55% (DR3) field capacity, and one FI (furrow irrigation) lower limit (65% field capacity). The N2O and NO emission fluxes and soil nitrogen (N) forms were determined, and the linear correlation between these indicators was analyzed. Results showed that under the same irrigation regime, the N2O and NO emissions from furrow irrigation treatment increased by 36.8% and 45.2% respectively compared to that from drip irrigation treatment. The cumulative N2O and NO emissions under DR3 were 30.2% and 28.6% higher than under DR1, respectively. Moreover, DR1 was also the lowest among the four treatments in soil NO3--N concentration. The N2O and NO emission fluxes were more correlated to soil NH4+-N (r=0.88 and 0.76) or NO2--N (r=0.90 and 0.80) concentration than soil NO3--N and soluble organic N, indicating that N2O and NO were mainly produced by the soil nitrification process. When the irrigation regime was the same, N2O and NO emissions were lower with drip irrigation than with furrow irrigation. Besides, drip irrigation with small quota but high frequency reduced N2O and NO emission compared to that with large quota but low frequency. Keywords: nitrous oxide, nitric oxide, drip irrigation, furrow irrigation, soil nitrogen DOI: 10.25165/j.ijabe.20231604.7961 Citation: Hou M M, Xiao Y, Zhu Q Y, Chen J N, Huang H, Jin Q, et al. NxO emissions in response to the irrigation lower limits under different irrigation modes in a lettuce field. Int J Agric & Biol Eng, 2023; 16(4): 159–167.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"27 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":"135660289","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":"Drying curve simulation and LF-NMR online monitor of water state in ursolic acid loaded chitosan nanoparticles during microwave freeze drying","authors":"Xing Ren, Xu Duan, Weiwei Cao, Lujie Zhao, Guangyue Ren, Panpan Liu","doi":"10.25165/j.ijabe.20231604.7519","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.7519","url":null,"abstract":"Changes in various states of water in ursolic acid (UA) loaded chitosan nanoparticles were assessed using low-field nuclear magnetic resonance (LF-NMR) during microwave freeze drying (MFD) process, and six thin-layer models were applied to simulate the drying kinetics. UA nanoparticles were dried at different microwave power densities (1 W/g, 2 W/g and 4 W/g). The results showed that three water fractions with different transverse relaxation times (T2) were detected in fresh UA nanoparticles. The T2 relaxation time of water decreased significantly with the increase of drying time at different microwave power densities. And the mutual migration and transformation of water in different states during the drying process of chitosan nanoparticles occurred. Furthermore, mathematical model analysis showed that the Page model provided the best description during the process of UA nanoparticle dried by MFD. The Page model can better simulate the drying kinetics of chitosan nanoparticles dried by MFD, and LF-NMR technology can monitor the changes in water status of UA nanoparticles. The results revealed that LF-NMR can monitor the changes of water in UA nanoparticles during the drying process. Keywords: microwave, drying, chitosan nanoparticles, water distribution DOI: 10.25165/j.ijabe.20231604.7519 Citation: Ren X, Duan X, Cao W W, Zhao L J, Ren G Y, Liu P P. Drying curve simulation and LF-NMR online monitor of water state in ursolic acid loaded chitosan nanoparticles during microwave freeze drying. Int J Agric & Biol Eng, 2023; 16(4): 263－268.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"10 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":"135660296","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":"Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach","authors":"Lifeng Xu, Zhongzhuo Yang, Zusheng Huang, Weilong Ding, G. Buck-Sorlin","doi":"10.25165/j.ijabe.20231601.6581","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.6581","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"46 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80581357","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":"Review of deep learning-based weed identification in crop fields","authors":"Wenze Hu, Samuel Oliver Wane, Junke Zhu, Dongsheng Li, Qing Zhang, Xiaoting Bie, Yubin Lan","doi":"10.25165/j.ijabe.20231604.8364","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231604.8364","url":null,"abstract":"Automatic weed identification and detection are crucial for precision weeding operations. In recent years, deep learning (DL) has gained widespread attention for its potential in crop weed identification. This paper provides a review of the current research status and development trends of weed identification in crop fields based on DL. Through an analysis of relevant literature from both within and outside of China, the author summarizes the development history, research progress, and identification and detection methods of DL-based weed identification technology. Emphasis is placed on data sources and DL models applied to different technical tasks. Additionally, the paper discusses the challenges of time-consuming and laborious dataset preparation, poor generality, unbalanced data categories, and low accuracy of field identification in DL for weed identification. Corresponding solutions are proposed to provide a reference for future research directions in weed identification. Keywords: deep learning, weed detection, weed classification, image segmentation, Convolutional Neural Network, image processing DOI: 10.25165/j.ijabe.20231604.8364 Citation: Hu W Z, Wane S O, Zhu J K, Li D S, Zhang Q, Bie X T, et al. Review of deep learning-based weed identification in crop fields. Int J Agric & Biol Eng, 2023; 16(4): 1-10.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"46 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":"135660077","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":"sugarcane, single-bud sugarcane seed, disc-type seeding device, seeding uniformity","authors":"Yulong Feng, Xuchao Yin, Hairong Jin, Wenyu Tong, Xiaofeng Ning","doi":"10.25165/j.ijabe.20231602.7067","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231602.7067","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"14 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74306512","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":"In-situ soil texture classification and physical clay content measurement based on multi-source information fusion","authors":"Chao Meng, Wei Yang, Xinjian Ren, D. Wang, Minzan Li","doi":"10.25165/j.ijabe.20231601.6918","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.6918","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"125 1 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74853254","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":"DR-XGBoost: An XGBoost model for field-road segmentation based on dual feature extraction and recursive feature elimination","authors":"Yuzhen Xiao, Guozhao Mo, Xiya Xiong, Jiawen Pan, Bingbing Hu, Caicong Wu, Weixin Zhai","doi":"10.25165/j.ijabe.20231603.8187","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231603.8187","url":null,"abstract":"Field-road segmentation is one of the key tasks in the processing of the trajectory of agricultural machinery. To improve the accuracy of the field-road segmentation, this study proposed an XGBoost model based on dual feature extraction and recursive feature elimination called DR-XGBoost. DR-XGBoost takes only a small amount of agricultural machine trajectory features as input. Firstly, the model adopted the dual feature extraction method we designed to rapidly expand the number of features and then adequately extract local trajectory features by the time window and feature extraction operator. Secondly, the model applies the recursive feature elimination algorithm to eliminate redundant features from the perspective of the model segmentation effect and thus reduce the computational consumption of model training. Thirdly, it trains XGBoost to complete the trajectory segmentation. To evaluate the effectiveness of DR-XGBoost, we conducted a series of experiments on a real trajectory dataset of agricultural machines. The model achieves a 98.2% Macro-F1 score on the dataset, which is 10.9% higher than the previous state-of-art. The proposal of DR-XGBoost fills the knowledge gap of trajectory feature extraction for agricultural machinery and provides a reasonable and effective feature selection scheme for the field-road segmentation problem. Keywords: trajectory segmentation, feature extraction, recursive feature elimination, time window, XGBoost DOI: 10.25165/j.ijabe.20231603.8187 Citation: Xiao Y Z, Mo G Z, Xiong X Y, Pan J W, Hu B B, Wu C C, et al. DR-XGBoost: An XGBoost model for field-road segmentation based on dual feature extraction and recursive feature elimination. Int J Agric & Biol Eng, 2023; 2023; 16(3): 169–179.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"132 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":"135357560","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}