Haiyan Zhang, Yao Zhang, Xiu-hua Li, Minzan Li, Zezhong Tian
Highlights A dataset expansion method based on random sampling could improve the robustness of yield estimation models. CIRE was more suitable for banana yield estimation. XGBoost-based banana yield estimation method showed good prediction ability of banana yield. Abstract. Banana yield prediction at the field level offers significant benefits to growers, packinghouses, crop insurance companies, and researchers. This study explored a remote sensing-based approach for forecasting banana yield at the field scale by using Sentinel-2 (S2) image time series and regression models. First, S2 images of critical phenological periods for bananas were acquired from the Google Earth Engine platform, and these images were treated with cloud and cloud shadow removal. Second, the dataset was expanded by randomly selecting pixels for each field to improve the accuracy of yield prediction. Third, nine vegetation indices (VIs) with high correlation with crop yield were compared and analyzed. Chlorophyll Index Red Edge was selected with a particularly high predictive ability in banana yield prediction. Finally, six regression models, namely, least absolute shrinkage and selection operator (LASSO), support vector regression (SVR), k-nearest neighbors (k-NN), random forest (RF), gradient boosted regression trees (GBRT), and extreme gradient boost (XGBoost), were employed, and their performances were compared. Results showed that the best prediction of banana yield was when 70 pixels were selected for each banana field. Out of nine VIs, comparing different regression models, the XGBoost model emerged as the best learner (the average of R2 for 100 runs in 2019 and 2020 were 0.84 and 0.79, respectively). It was followed by the GBRT model with almost the same performance, which explained 82% and 79% of the banana yield variability for 2019 and 2020, respectively. The LASSO model exhibited the lowest performance of all, but it performed best in terms of stability. The proposed framework applied to satellite image time series can achieve reliable banana yield prediction across years at the field scale. Keywords: Banana yield prediction, Extreme gradient boost, Sentinel-2, Vegetation index.
{"title":"Predicting Banana Yield at the Field Scale by Combining Sentinel-2 Time Series Data and Regression Models","authors":"Haiyan Zhang, Yao Zhang, Xiu-hua Li, Minzan Li, Zezhong Tian","doi":"10.13031/aea.15220","DOIUrl":"https://doi.org/10.13031/aea.15220","url":null,"abstract":"Highlights A dataset expansion method based on random sampling could improve the robustness of yield estimation models. CIRE was more suitable for banana yield estimation. XGBoost-based banana yield estimation method showed good prediction ability of banana yield. Abstract. Banana yield prediction at the field level offers significant benefits to growers, packinghouses, crop insurance companies, and researchers. This study explored a remote sensing-based approach for forecasting banana yield at the field scale by using Sentinel-2 (S2) image time series and regression models. First, S2 images of critical phenological periods for bananas were acquired from the Google Earth Engine platform, and these images were treated with cloud and cloud shadow removal. Second, the dataset was expanded by randomly selecting pixels for each field to improve the accuracy of yield prediction. Third, nine vegetation indices (VIs) with high correlation with crop yield were compared and analyzed. Chlorophyll Index Red Edge was selected with a particularly high predictive ability in banana yield prediction. Finally, six regression models, namely, least absolute shrinkage and selection operator (LASSO), support vector regression (SVR), k-nearest neighbors (k-NN), random forest (RF), gradient boosted regression trees (GBRT), and extreme gradient boost (XGBoost), were employed, and their performances were compared. Results showed that the best prediction of banana yield was when 70 pixels were selected for each banana field. Out of nine VIs, comparing different regression models, the XGBoost model emerged as the best learner (the average of R2 for 100 runs in 2019 and 2020 were 0.84 and 0.79, respectively). It was followed by the GBRT model with almost the same performance, which explained 82% and 79% of the banana yield variability for 2019 and 2020, respectively. The LASSO model exhibited the lowest performance of all, but it performed best in terms of stability. The proposed framework applied to satellite image time series can achieve reliable banana yield prediction across years at the field scale. Keywords: Banana yield prediction, Extreme gradient boost, Sentinel-2, Vegetation index.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67051731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Yao, Zuzana Hruska, R. Kincaid, Feifei Tao, K. Rajasekaran
HighlightsKernels were artificially inoculated with toxigenic and non-toxigenic strains of Aspergillus flavus in the lab.Corn kernel mechanical strength was assessed as single kernel compression rupture force (CRF).Fungus-infected kernels had lower mechanical strength than the controls.Kernels with high aflatoxin contamination had lower mechanical strength than others.ABSTRACT. One persistent food safety issue associated with corn is aflatoxin contamination. Aflatoxins are secondary metabolites produced mainly by the fungi Aspergillus flavus (A. flavus) and A. parasiticus. Under environmental conditions suitable for fungal growth and aflatoxin production, these fungi are capable of infecting corn kernels in the field and in storage. When corn kernels are infected, the fungi use nutrients from the kernels to grow and propagate. In general, moldy and contaminated kernels are discolored and lighter in weight. These features could aid in the identification and removal of infected kernels. The objective of this research was to investigate the relationship between the mechanical strength of corn kernels and fungal infection, as well as aflatoxin contamination as a consequence of fungal infection. Corn kernels were infected with aflatoxin producing (AF13) and non-toxin-producing (AF36) A. flavus strains in lab inoculations. A total of 900 kernels were assigned to three groups, non-inoculated control, AF13-inoculated, and AF36-inoculated. One hundred kernels from each group were incubated for 3, 5, and 8 days. After incubation each kernel was cleaned and dried, then subjected to a destructive mechanical test. The compression rupture force (CRF) of each kernel was measured using a Mark-10 material test gauge to assess its kernel strength. The results show that kernel strength was significantly different between the control and treatment groups, with the control kernels being the strongest and the AF36-inoculated kernels the weakest. The results also indicated that kernels with aflatoxin contamination of 300 ppb and above were significantly weaker than control kernels and those less contaminated in the AF13-inoculated group. It is expected that the results of this research could benefit the corn industry by mitigating the aflatoxin contamination problem in post-harvest management. Keywords: Aflatoxin, Aspergillus flavus, Compression rupture force, Corn, Fungus-infected, Inoculation, Mechanical strength.
{"title":"Effect of Aspergillus Flavus Fungi Infection and Aflatoxin Contamination on Single Corn Kernel Mechanical Strength","authors":"H. Yao, Zuzana Hruska, R. Kincaid, Feifei Tao, K. Rajasekaran","doi":"10.13031/aea.15266","DOIUrl":"https://doi.org/10.13031/aea.15266","url":null,"abstract":"HighlightsKernels were artificially inoculated with toxigenic and non-toxigenic strains of Aspergillus flavus in the lab.Corn kernel mechanical strength was assessed as single kernel compression rupture force (CRF).Fungus-infected kernels had lower mechanical strength than the controls.Kernels with high aflatoxin contamination had lower mechanical strength than others.ABSTRACT. One persistent food safety issue associated with corn is aflatoxin contamination. Aflatoxins are secondary metabolites produced mainly by the fungi Aspergillus flavus (A. flavus) and A. parasiticus. Under environmental conditions suitable for fungal growth and aflatoxin production, these fungi are capable of infecting corn kernels in the field and in storage. When corn kernels are infected, the fungi use nutrients from the kernels to grow and propagate. In general, moldy and contaminated kernels are discolored and lighter in weight. These features could aid in the identification and removal of infected kernels. The objective of this research was to investigate the relationship between the mechanical strength of corn kernels and fungal infection, as well as aflatoxin contamination as a consequence of fungal infection. Corn kernels were infected with aflatoxin producing (AF13) and non-toxin-producing (AF36) A. flavus strains in lab inoculations. A total of 900 kernels were assigned to three groups, non-inoculated control, AF13-inoculated, and AF36-inoculated. One hundred kernels from each group were incubated for 3, 5, and 8 days. After incubation each kernel was cleaned and dried, then subjected to a destructive mechanical test. The compression rupture force (CRF) of each kernel was measured using a Mark-10 material test gauge to assess its kernel strength. The results show that kernel strength was significantly different between the control and treatment groups, with the control kernels being the strongest and the AF36-inoculated kernels the weakest. The results also indicated that kernels with aflatoxin contamination of 300 ppb and above were significantly weaker than control kernels and those less contaminated in the AF13-inoculated group. It is expected that the results of this research could benefit the corn industry by mitigating the aflatoxin contamination problem in post-harvest management. Keywords: Aflatoxin, Aspergillus flavus, Compression rupture force, Corn, Fungus-infected, Inoculation, Mechanical strength.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights Guidelines for measuring ASP® 602 concentrations with a spectrophotometer or turbidimeters were established. Concentration predictions had errors between 0.1% and 24.6% for the range from 0 to 100 ppm with the instruments. Stationary and portable instruments were able to detect ASP® 602 concentrations as low as 2 ppm. Test results from ISO 22368-1 validated that ASP® 602 could be used for inspecting cleanout and agitation systems. Abstract. ASP® 602 (kaolin clay) was evaluated as an alternate material for performing ISO 22368-1 sprayer clean out test standard. Recommendations for sample homogenization, measurement temperature and sample sizes to address potential concerns or technical challenges in assaying ASP® 602 samples were provided under relevant conditions. Linear regression models for predicting ASP® 602 concentrations from 0 to 100 ppm (mg·L-1) in sample mixtures were developed using outputs from a spectrophotometer and two different turbidimeters. Test results showed that the three instruments could measure ASP® 602 concentrations as low as 2 ppm. Validations of the developed models showed approximation errors were 0.9% to 24.6% and 0.1% to 18.4% for the spectrophotometer and the turbidimeters, respectively. However, their maximum absolute errors were less than 3.7 ppm for the spectrophotometer and 2.3 ppm for the turbidimeters within the validation range. Two agitation and cleaning systems of a sprayer were evaluated with ASP® 602 following the ISO 22368-1 clean out procedure. Residue reduction factors from the initial mixture concentration were 163 for one system which did not meet ISO 16119-2 environmental requirement (factor over 400) and 819 for the other system which exceeded the requirement. Analysis results of ASP® 602 samples from ISO 22368-1 clean out tests showed that ASP® 602 could be used as a potential testing substance to evaluate and differentiate the performance of agitation and cleaning systems of sprayers. Keywords: Absorbance, ASP® 602, ISO Standard, Pesticide, Spectrophotometer, Turbidity.
{"title":"Evaluating Kaolin Clay as a Potential Substance for ISO Sprayer Cleaning System Tests","authors":"Carla Román, H. Jeon, Heping Zhu, E. Ozkan","doi":"10.13031/aea.15466","DOIUrl":"https://doi.org/10.13031/aea.15466","url":null,"abstract":"Highlights Guidelines for measuring ASP® 602 concentrations with a spectrophotometer or turbidimeters were established. Concentration predictions had errors between 0.1% and 24.6% for the range from 0 to 100 ppm with the instruments. Stationary and portable instruments were able to detect ASP® 602 concentrations as low as 2 ppm. Test results from ISO 22368-1 validated that ASP® 602 could be used for inspecting cleanout and agitation systems. Abstract. ASP® 602 (kaolin clay) was evaluated as an alternate material for performing ISO 22368-1 sprayer clean out test standard. Recommendations for sample homogenization, measurement temperature and sample sizes to address potential concerns or technical challenges in assaying ASP® 602 samples were provided under relevant conditions. Linear regression models for predicting ASP® 602 concentrations from 0 to 100 ppm (mg·L-1) in sample mixtures were developed using outputs from a spectrophotometer and two different turbidimeters. Test results showed that the three instruments could measure ASP® 602 concentrations as low as 2 ppm. Validations of the developed models showed approximation errors were 0.9% to 24.6% and 0.1% to 18.4% for the spectrophotometer and the turbidimeters, respectively. However, their maximum absolute errors were less than 3.7 ppm for the spectrophotometer and 2.3 ppm for the turbidimeters within the validation range. Two agitation and cleaning systems of a sprayer were evaluated with ASP® 602 following the ISO 22368-1 clean out procedure. Residue reduction factors from the initial mixture concentration were 163 for one system which did not meet ISO 16119-2 environmental requirement (factor over 400) and 819 for the other system which exceeded the requirement. Analysis results of ASP® 602 samples from ISO 22368-1 clean out tests showed that ASP® 602 could be used as a potential testing substance to evaluate and differentiate the performance of agitation and cleaning systems of sprayers. Keywords: Absorbance, ASP® 602, ISO Standard, Pesticide, Spectrophotometer, Turbidity.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Javier Campos, Heping Zhu, H. Jeon, R. Salcedo, E. Ozkan, Emilio Gil
HighlightsTwelve industrial PWM valves were investigated to manipulate high-pressure agricultural hollow-cone nozzles.Modulation frequencies ranged between 5 and 50 Hz and duty cycles between 10% and 100%.Upstream and downstream pressure profiles were used to determine maximum duty cycle ranges.Two out of 12 PWM valves could be potentially used for future variable-rate orchard sprayer designs.Abstract. Integration of high-speed pulse-width-modulation (PWM) solenoid valves into variable-rate orchard sprayers is needed to accurately regulate spray outputs for matching changes in plant canopy structure characteristics. Capability of 12 PWM valves to modulate hollow-cone nozzles for variable-rate applications was investigated with PWM frequencies of 5 to 50 Hz and duty cycles of 10% to 100%. The PWM valves were assembled on a laboratory spray system with a hollow-cone disc-core nozzle of 2.84 L min-1 flow capacity operated at 1380 kPa pressure. The upstream and downstream pressures on the PWM valves were recorded and analyzed to determine the maximum functional duty cycle ranges and maximum PWM frequency at which the PWM valves could manipulate the nozzle functionally. Test results showed that there were noticeable differences in the modulation capability among the 12 PWM valves due to their design differences. Two out of 12 valves were able to manipulate the hollow-cone nozzles with duty cycles ranging from 30% or 40% to 70% at the modulation frequency of 40 Hz. These two PWM valves performed the highest capability among the 12 valves to manipulate the hollow-cone nozzle. As a result, these two valves would be selected for future investigations on their flow rate modulation accuracy and droplet size distributions before they could be recommended for adaptation in the variable-rate orchard sprayers. Keywords: Duty cycle, Flow control, Orchard sprayer, Pesticide, Precision farming, Pulse width modulation.
{"title":"Assessment of PWM Solenoid Valves to Manipulate Hollow-Cone Nozzles with Different Modulation Frequencies","authors":"Javier Campos, Heping Zhu, H. Jeon, R. Salcedo, E. Ozkan, Emilio Gil","doi":"10.13031/aea.15415","DOIUrl":"https://doi.org/10.13031/aea.15415","url":null,"abstract":"HighlightsTwelve industrial PWM valves were investigated to manipulate high-pressure agricultural hollow-cone nozzles.Modulation frequencies ranged between 5 and 50 Hz and duty cycles between 10% and 100%.Upstream and downstream pressure profiles were used to determine maximum duty cycle ranges.Two out of 12 PWM valves could be potentially used for future variable-rate orchard sprayer designs.Abstract. Integration of high-speed pulse-width-modulation (PWM) solenoid valves into variable-rate orchard sprayers is needed to accurately regulate spray outputs for matching changes in plant canopy structure characteristics. Capability of 12 PWM valves to modulate hollow-cone nozzles for variable-rate applications was investigated with PWM frequencies of 5 to 50 Hz and duty cycles of 10% to 100%. The PWM valves were assembled on a laboratory spray system with a hollow-cone disc-core nozzle of 2.84 L min-1 flow capacity operated at 1380 kPa pressure. The upstream and downstream pressures on the PWM valves were recorded and analyzed to determine the maximum functional duty cycle ranges and maximum PWM frequency at which the PWM valves could manipulate the nozzle functionally. Test results showed that there were noticeable differences in the modulation capability among the 12 PWM valves due to their design differences. Two out of 12 valves were able to manipulate the hollow-cone nozzles with duty cycles ranging from 30% or 40% to 70% at the modulation frequency of 40 Hz. These two PWM valves performed the highest capability among the 12 valves to manipulate the hollow-cone nozzle. As a result, these two valves would be selected for future investigations on their flow rate modulation accuracy and droplet size distributions before they could be recommended for adaptation in the variable-rate orchard sprayers. Keywords: Duty cycle, Flow control, Orchard sprayer, Pesticide, Precision farming, Pulse width modulation.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gary Daniel Chesser, Joseph L. Purswell, Jeremiah D. Davis, Jason K. Ward, Tom Tabler, Yang Zhao
Highlights Design air temperatures disregard ambient weather effects such as convective heating/cooling and solar radiation. Design air temperatures may not yield accurate estimates of heat transfer for broiler houses during warm conditions. The use of sol-air temperature as a design parameter could serve to optimize estimates of heat transfer. Sol-air temperatures can be predicted with historical meteorological data and used as a design parameter. This study supports the appropriateness of using sol-air temperature as a design parameter. Abstract. Thermal stress adversely affects poultry production efficiency, health, and welfare. Poultry house insulation requirements are typically specified based on engineering design air temperatures, which disregards ambient weather effects such as convective heating and cooling, and solar radiation. The objectives of this study were: (1) to monitor external temperatures of a commercial broiler house to verify the suitability of using sol-air temperature as a design parameter for broiler housing design; (2) to use the sol-air temperature to simulate the effects of solar radiation on conductive heat gain during warm weather for a modeled broiler house in varying climatic locations using historical meteorological data. For two 7-day warm season periods (September and May), ambient air, exterior surface temperatures, and solar radiation were recorded for an east facing sidewall of a broiler house in northern Alabama and used to calculate sol-air temperatures. For both periods, maximum daily surface (Tsurface) and sol-air (Tsol-air) temperatures were significantly elevated (P < 0.0001) as compared to maximum ambient air temperatures (Tair). Maximum Tsurface and Tsol-air were not significantly different for September (P = 0.2144) and May (P = 0.1544), respectively. Additionally, simulations of conductive heat transfer (gain/loss) using Tair and Tsol-air were performed for a model structure located in ten different broiler regions in the United States during daytime warm conditions using historical meteorological data. For each simulation, conductive heat transfer calculated using Tsol-air was considerably higher when compared to conductive heat transfer calculated using Tair. Methods currently used to specify design temperatures for broiler house design and construction can result in inadequate thermal insulation and Tsol-air provides improved estimates of conductive heat transfer during daytime conditions. Keywords: Broiler house, Design temperature, Heat transfer, Insulation, Poultry, Solar radiation, Sol-air temperature, Thermal envelope.
{"title":"Comparison of Outside Air and Sol-Air Design Temperatures for Estimating Insulation Needs","authors":"Gary Daniel Chesser, Joseph L. Purswell, Jeremiah D. Davis, Jason K. Ward, Tom Tabler, Yang Zhao","doi":"10.13031/aea.15424","DOIUrl":"https://doi.org/10.13031/aea.15424","url":null,"abstract":"Highlights Design air temperatures disregard ambient weather effects such as convective heating/cooling and solar radiation. Design air temperatures may not yield accurate estimates of heat transfer for broiler houses during warm conditions. The use of sol-air temperature as a design parameter could serve to optimize estimates of heat transfer. Sol-air temperatures can be predicted with historical meteorological data and used as a design parameter. This study supports the appropriateness of using sol-air temperature as a design parameter. Abstract. Thermal stress adversely affects poultry production efficiency, health, and welfare. Poultry house insulation requirements are typically specified based on engineering design air temperatures, which disregards ambient weather effects such as convective heating and cooling, and solar radiation. The objectives of this study were: (1) to monitor external temperatures of a commercial broiler house to verify the suitability of using sol-air temperature as a design parameter for broiler housing design; (2) to use the sol-air temperature to simulate the effects of solar radiation on conductive heat gain during warm weather for a modeled broiler house in varying climatic locations using historical meteorological data. For two 7-day warm season periods (September and May), ambient air, exterior surface temperatures, and solar radiation were recorded for an east facing sidewall of a broiler house in northern Alabama and used to calculate sol-air temperatures. For both periods, maximum daily surface (Tsurface) and sol-air (Tsol-air) temperatures were significantly elevated (P &lt; 0.0001) as compared to maximum ambient air temperatures (Tair). Maximum Tsurface and Tsol-air were not significantly different for September (P = 0.2144) and May (P = 0.1544), respectively. Additionally, simulations of conductive heat transfer (gain/loss) using Tair and Tsol-air were performed for a model structure located in ten different broiler regions in the United States during daytime warm conditions using historical meteorological data. For each simulation, conductive heat transfer calculated using Tsol-air was considerably higher when compared to conductive heat transfer calculated using Tair. Methods currently used to specify design temperatures for broiler house design and construction can result in inadequate thermal insulation and Tsol-air provides improved estimates of conductive heat transfer during daytime conditions. Keywords: Broiler house, Design temperature, Heat transfer, Insulation, Poultry, Solar radiation, Sol-air temperature, Thermal envelope.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"28 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":"135910886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ji Feng, Jiachong Pan, Haisheng Liu, Yanzheng Liu, Peng Hou, Youquan Jiao, Haosu Sun, Changjian Ma, Shanshan Ke
Highlights Keywords: Click here to enter keywords and key phrases, separated by commas, with a period at the end
重点显示关键字:单击此处输入关键字和关键短语，以逗号分隔，最后加句号
{"title":"Optimal Structural Parameters of Drip Laminar Emitters Using High Sediment Irrigation Water","authors":"Ji Feng, Jiachong Pan, Haisheng Liu, Yanzheng Liu, Peng Hou, Youquan Jiao, Haosu Sun, Changjian Ma, Shanshan Ke","doi":"10.13031/aea.15617","DOIUrl":"https://doi.org/10.13031/aea.15617","url":null,"abstract":"Highlights Keywords: Click here to enter keywords and key phrases, separated by commas, with a period at the end","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"30 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":"135911210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aaron P. Turner, Samuel G. McNeill, Michael Montross, Mark E. Casada, Sidney A. Thompson, Ronaldo G. Maghirang, Marvin Carpena Petingco
Highlights The pressure dependent bulk density relationship was evaluated for nine crops. Two compressibility models were proposed, with RMSE ranging from 1.7 to 7.1 kg m-3, depending on the crop. Differences between compressibility equations had minimal influence on packing predictions in full size bins. Combined test weight and packing correction factors are shown for each crop in bins of different sizes and construction. Abstract. Knowledge of the pressure-dependent bulk density increase observed in stored grains and oil seeds, commonly referred to as packing or compressibility, is important for maintaining accurate grain inventory, evaluating wall loads, and other applications that require estimating density at specific depths in a bin. This study presents compressibility equation parameters determined utilizing a compilation of the best data available, including previously published and new datasets. In all, confined uniaxial compression tests for nine crops (barley, canola, corn, oats, rice, sorghum, soybeans, hard red winter wheat, and soft red winter wheat) were included. The data was fit using two candidate compressibility equations, both of which generally fit well and resulted in root mean squared errors ranging from 1.7 to 7.1 kg m-3, depending on the model and crop. For crops with full scale bin data available from previous research, the resulting equations were applied to estimate inventory and were compared with the measured mass of grain in the bin. Results from both equations were similar, and apart from oats, median errors were less than 2.5%. Keywords: Bulk density, Compressibility, Pack factor, Grain storage, Test weight, Stored grain inventory.
对9种作物的容重关系进行了压力依赖性评价。提出了两种可压缩性模型，其RMSE范围为1.7至7.1 kg m-3，具体取决于作物。可压缩性方程之间的差异对全尺寸箱的包装预测影响最小。每种作物在不同尺寸和结构的仓内的综合试验重量和包装修正系数均显示。摘要在储存谷物和油籽中观察到的与压力相关的堆积密度增加的知识，通常被称为包装或压缩性，对于保持准确的谷物库存，评估壁负载以及其他需要估计特定深度密度的应用非常重要。本研究提出了利用现有最佳数据汇编确定的可压缩性方程参数，包括以前发表的和新的数据集。总共包括9种作物(大麦、油菜籽、玉米、燕麦、水稻、高粱、大豆、硬红冬小麦和软红冬小麦)的单轴压缩试验。数据使用两个候选压缩性方程进行拟合，这两个方程总体上拟合良好，根据模型和作物的不同，其均方根误差在1.7至7.1 kg - m-3之间。对于从以前的研究中获得的全尺寸仓数据的作物，将所得方程应用于估计库存，并与仓中谷物的测量质量进行比较。两个方程的结果相似，除燕麦外，中位误差小于2.5%。关键词:堆积密度，可压缩性，包装系数，储粮，试验重量，储粮库存。
{"title":"Bulk Compressibility Behavior for Select Crops","authors":"Aaron P. Turner, Samuel G. McNeill, Michael Montross, Mark E. Casada, Sidney A. Thompson, Ronaldo G. Maghirang, Marvin Carpena Petingco","doi":"10.13031/aea.15593","DOIUrl":"https://doi.org/10.13031/aea.15593","url":null,"abstract":"Highlights The pressure dependent bulk density relationship was evaluated for nine crops. Two compressibility models were proposed, with RMSE ranging from 1.7 to 7.1 kg m-3, depending on the crop. Differences between compressibility equations had minimal influence on packing predictions in full size bins. Combined test weight and packing correction factors are shown for each crop in bins of different sizes and construction. Abstract. Knowledge of the pressure-dependent bulk density increase observed in stored grains and oil seeds, commonly referred to as packing or compressibility, is important for maintaining accurate grain inventory, evaluating wall loads, and other applications that require estimating density at specific depths in a bin. This study presents compressibility equation parameters determined utilizing a compilation of the best data available, including previously published and new datasets. In all, confined uniaxial compression tests for nine crops (barley, canola, corn, oats, rice, sorghum, soybeans, hard red winter wheat, and soft red winter wheat) were included. The data was fit using two candidate compressibility equations, both of which generally fit well and resulted in root mean squared errors ranging from 1.7 to 7.1 kg m-3, depending on the model and crop. For crops with full scale bin data available from previous research, the resulting equations were applied to estimate inventory and were compared with the measured mass of grain in the bin. Results from both equations were similar, and apart from oats, median errors were less than 2.5%. Keywords: Bulk density, Compressibility, Pack factor, Grain storage, Test weight, Stored grain inventory.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","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":"135559921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights Brick-shaped wireless sensors tended to settle about 1/3 of a silo diameter around the center of the peaked grain mass whereas spherical-shaped wireless sensors tended to settle about 3/4 of a silo diameter from the center of the peaked grain mass (and within ¼ diameter of the silo wall). A mix of both spherical- and brick-shaped sensors of different sizes and weights can be used to achieve targeted placement of wireless sensors within the stored grain mass as a function of gravity filling silos of different sizes. Abstract. The most utilized automated stored grain bulk monitoring technology relies on temperature sensors incorporated into steel cables that are suspended from the roof to the floor of silos. However, cable-based sensors are expensive and require reinforcing roofs to account for the frictional forces exerted by the grain mass on the cables during loading, settling and unloading. Two shapes of wireless sensors (brick and spherical) were studied as an alternative. In-silo experiments investigated the distribution of wireless sensors as a function of gravity filling a farm silo and recovering the sensors during unloading. In the first experiment, five of each sensor shape (brick and spherical) were placed one at a time in a grain stream flowing repeatedly at 28.6 and 39.6 metric tons per hour (MT/h). The drop-out height was 5.30 m in the first and 3.94 m in the second trial. The results indicate that the brick-shaped wireless sensors tended to settle about 1/3 of a silo diameter around the center of the peaked grain mass whereas the spherical-shaped wireless sensors tended to settle about 3/4 of a silo diameter from the center of the peaked grain mass (and within ¼ diameter of the silo wall). In the second experiment, 44, 15, 20, and 25 wireless sensors were randomly placed, respectively, in the grain mass to test their recapture rate during four unloading trials. The results indicated that all wireless sensors were recovered resulting in a 100% recapture rate. Key findings of this study point toward the need for a mix of both spherical- and brick-shaped sensors of different sizes and weights to achieve targeted placement and greater distribution of wireless sensors within the stored grain mass as a function of gravity filling silos of different sizes. Keywords: Brick shape sensor, Grain quality, Sensor distribution, Sensor recovery, Spherical shape sensor.
{"title":"Distribution of Brick- Versus Spherical-Shaped Wireless Sensors as a Function of Gravity-Filling a Storage Silo and their Recovery from the Corn Grain Mass during Unloading","authors":"G. Aby, D. Maier","doi":"10.13031/aea.15276","DOIUrl":"https://doi.org/10.13031/aea.15276","url":null,"abstract":"Highlights Brick-shaped wireless sensors tended to settle about 1/3 of a silo diameter around the center of the peaked grain mass whereas spherical-shaped wireless sensors tended to settle about 3/4 of a silo diameter from the center of the peaked grain mass (and within ¼ diameter of the silo wall). A mix of both spherical- and brick-shaped sensors of different sizes and weights can be used to achieve targeted placement of wireless sensors within the stored grain mass as a function of gravity filling silos of different sizes. Abstract. The most utilized automated stored grain bulk monitoring technology relies on temperature sensors incorporated into steel cables that are suspended from the roof to the floor of silos. However, cable-based sensors are expensive and require reinforcing roofs to account for the frictional forces exerted by the grain mass on the cables during loading, settling and unloading. Two shapes of wireless sensors (brick and spherical) were studied as an alternative. In-silo experiments investigated the distribution of wireless sensors as a function of gravity filling a farm silo and recovering the sensors during unloading. In the first experiment, five of each sensor shape (brick and spherical) were placed one at a time in a grain stream flowing repeatedly at 28.6 and 39.6 metric tons per hour (MT/h). The drop-out height was 5.30 m in the first and 3.94 m in the second trial. The results indicate that the brick-shaped wireless sensors tended to settle about 1/3 of a silo diameter around the center of the peaked grain mass whereas the spherical-shaped wireless sensors tended to settle about 3/4 of a silo diameter from the center of the peaked grain mass (and within ¼ diameter of the silo wall). In the second experiment, 44, 15, 20, and 25 wireless sensors were randomly placed, respectively, in the grain mass to test their recapture rate during four unloading trials. The results indicated that all wireless sensors were recovered resulting in a 100% recapture rate. Key findings of this study point toward the need for a mix of both spherical- and brick-shaped sensors of different sizes and weights to achieve targeted placement and greater distribution of wireless sensors within the stored grain mass as a function of gravity filling silos of different sizes. Keywords: Brick shape sensor, Grain quality, Sensor distribution, Sensor recovery, Spherical shape sensor.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights A lateral-approaching and horizontal-pushing automatic transplanting manipulator was developed on the basis of cultural practice for vegetable production. The transplanting manipulator approached the seedlings using a circuitous path, which could get away from the seedling plants for extraction with low damages. Based on the modern mechatronics and pneumatic technology, a set of control system was designed to coordinate each function unit for flexible automation. Abstract. A lateral-approaching and horizontal-pushing transplanting manipulator for greenhouse seedlings was developed to minimize the damage of their stems and leaves during transplanting. The manipulator is composed of a pick-up robotic arm, an end-effector, two conveyors, and a control system. The robotic arm liking a spatial 3-DoF displacement mechanism to achieve a point-to-point circuitous locomotion of the end-effector was designed with the mechanism combination innovation method, which consisted of two crossing high-speed linear modules and a pushing slide cylinder. The end-effector of a pincette-type mechanism uses two cylinder fingers and four pins to pick up and release the seedlings. Each conveyor adopts a flat-belt transmission mode to move the plug tray/growth pot to the working position of the end-effector. The control system coordinates the flexible automation of each component. A physical prototype of the manipulator was constructed and its performance was tested under laboratory conditions. Through the high-speed camera test, the end-effector could approach plug seedling in lateral sliding way to effectively shelter the seedling plants. On the whole, the maximum holding angles of these seedling plants were larger than 45° with little effects on the subsequent growth. The corresponding performance tests showed that the average success ratios for automatic transplanting were up to 97.57% for typical pepper and cabbage seedlings. The lateral-approaching and horizontal-pushing transplanting performance was satisfactory. Keywords: Circuitous path, Greenhouse production, Low damage, Plug seedling, Transplanting.
{"title":"Design and Test of a Lateral-Approaching and Horizontal-Pushing Transplanting Manipulator for Greenhouse Seedlings","authors":"Luhua Han, Menghan Mo, Haorui Ma, F. Kumi, H. Mao","doi":"10.13031/aea.15420","DOIUrl":"https://doi.org/10.13031/aea.15420","url":null,"abstract":"Highlights A lateral-approaching and horizontal-pushing automatic transplanting manipulator was developed on the basis of cultural practice for vegetable production. The transplanting manipulator approached the seedlings using a circuitous path, which could get away from the seedling plants for extraction with low damages. Based on the modern mechatronics and pneumatic technology, a set of control system was designed to coordinate each function unit for flexible automation. Abstract. A lateral-approaching and horizontal-pushing transplanting manipulator for greenhouse seedlings was developed to minimize the damage of their stems and leaves during transplanting. The manipulator is composed of a pick-up robotic arm, an end-effector, two conveyors, and a control system. The robotic arm liking a spatial 3-DoF displacement mechanism to achieve a point-to-point circuitous locomotion of the end-effector was designed with the mechanism combination innovation method, which consisted of two crossing high-speed linear modules and a pushing slide cylinder. The end-effector of a pincette-type mechanism uses two cylinder fingers and four pins to pick up and release the seedlings. Each conveyor adopts a flat-belt transmission mode to move the plug tray/growth pot to the working position of the end-effector. The control system coordinates the flexible automation of each component. A physical prototype of the manipulator was constructed and its performance was tested under laboratory conditions. Through the high-speed camera test, the end-effector could approach plug seedling in lateral sliding way to effectively shelter the seedling plants. On the whole, the maximum holding angles of these seedling plants were larger than 45° with little effects on the subsequent growth. The corresponding performance tests showed that the average success ratios for automatic transplanting were up to 97.57% for typical pepper and cabbage seedlings. The lateral-approaching and horizontal-pushing transplanting performance was satisfactory. Keywords: Circuitous path, Greenhouse production, Low damage, Plug seedling, Transplanting.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights An eighth-scale grain drying system was used to monitor real-time change of bulk density in a bed of wheat during drying. Density was determined from dielectric properties measured by a microwave sensor at the center of the bed. Density was simulated at other locations by modeling heat and mass transfer. Root mean square error (RMSE) when comparing the simulated results to the empirical results at the center of the bed was 0.0054 g/cm3. Abstract. Agricultural commodities such as cereal grains, oilseeds, and nuts are dried before and during storage to minimize, if not prevent, degradation of quality. While drying, heat and mass transfer occur simultaneously resulting in the removal of moisture from the product over time. As the moisture is removed, mass and volume are reduced. Such losses produce shrinkage, and thus, density changes throughout the drying product for the duration of the drying process. Density is an important parameter because it is indicative of other quality parameters such as test weight. It is also critical for operators because it can be used to estimate grain mass in silos, determine resistance to airflow, and predict grain pressure in silos. Despite its usefulness, bulk density is difficult to measure at specific locations within a bed of grain or seed. It can be calculated for small quantities and estimated for large quantities by gravimetric means; however, it has been shown that bulk density varies throughout a bed of grain or seed. Such variances are caused by compaction from upper layers and differences in moisture content. Therefore, an eighth-scale grain drying system was used to observe the real-time change in bulk density within a 153,000-cm3 volume bed of wheat. Bulk density was determined empirically at the center of the volume from dielectric properties measured with a microwave sensor, and it was simulated at other locations by modeling heat and mass transfer. Comparison between the bulk density determined from simulation and that measured empirically at the center of the volume of wheat resulted in a root mean square error (RMSE) of 0.0054 g/cm3; thus, the accuracy of the models was confirmed. Real-time knowledge of bulk density at various locations can aid in monitoring the quality of the product being dried and provide essential information concerning the pressure and airflow throughout the entire volume. Keywords: Bulk density, Dielectric properties, Drying modeling, Grain drying, Microwave sensing, Real-time monitoring.
{"title":"Use of a Microwave Sensor to Monitor Bulk Density during Grain Drying","authors":"M. Lewis, S. Trabelsi","doi":"10.13031/aea.15452","DOIUrl":"https://doi.org/10.13031/aea.15452","url":null,"abstract":"Highlights An eighth-scale grain drying system was used to monitor real-time change of bulk density in a bed of wheat during drying. Density was determined from dielectric properties measured by a microwave sensor at the center of the bed. Density was simulated at other locations by modeling heat and mass transfer. Root mean square error (RMSE) when comparing the simulated results to the empirical results at the center of the bed was 0.0054 g/cm3. Abstract. Agricultural commodities such as cereal grains, oilseeds, and nuts are dried before and during storage to minimize, if not prevent, degradation of quality. While drying, heat and mass transfer occur simultaneously resulting in the removal of moisture from the product over time. As the moisture is removed, mass and volume are reduced. Such losses produce shrinkage, and thus, density changes throughout the drying product for the duration of the drying process. Density is an important parameter because it is indicative of other quality parameters such as test weight. It is also critical for operators because it can be used to estimate grain mass in silos, determine resistance to airflow, and predict grain pressure in silos. Despite its usefulness, bulk density is difficult to measure at specific locations within a bed of grain or seed. It can be calculated for small quantities and estimated for large quantities by gravimetric means; however, it has been shown that bulk density varies throughout a bed of grain or seed. Such variances are caused by compaction from upper layers and differences in moisture content. Therefore, an eighth-scale grain drying system was used to observe the real-time change in bulk density within a 153,000-cm3 volume bed of wheat. Bulk density was determined empirically at the center of the volume from dielectric properties measured with a microwave sensor, and it was simulated at other locations by modeling heat and mass transfer. Comparison between the bulk density determined from simulation and that measured empirically at the center of the volume of wheat resulted in a root mean square error (RMSE) of 0.0054 g/cm3; thus, the accuracy of the models was confirmed. Real-time knowledge of bulk density at various locations can aid in monitoring the quality of the product being dried and provide essential information concerning the pressure and airflow throughout the entire volume. Keywords: Bulk density, Dielectric properties, Drying modeling, Grain drying, Microwave sensing, Real-time monitoring.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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