Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964955
A. Altana, Lorenzo Becce, E. Avancini, P. Lugli, L. Petti, F. Mazzetto
The investigation of the performance of agricultural sprayer through drift and deposition sampling directly on field is of extreme importance, especially in view of ensuring an effective and optimal administration of plant protection products (PPP), necessary to limit waste of products and damages to the ecosystems. This is however a time and resource-intensive activity, typically resulting in highly variable results due to the unpredictable and uncontrollable atmospheric and operating conditions under which sprayers usually operate. To minimize the measurement uncertainties while also simpli-fying the procedures and reducing costs, in this work we propose a deposition assessment protocol based on the spraying of two distinct tracer solutions, leveraging two well-known phenomena: one based on optical absorbance, and the other on electrical conductivity. Although the selected tracers, namely uranine and potassium chloride, are already extensively used in other applications for their non-toxicity to both bystanders and environment, very little is published about their use in spray drift applications; the results obtained on the test bench promise to reduce the experiment costs, simplify the measurement, increase the reproducibility and facilitate the test automation. A test bench for nozzles has been employed to deposit the solutions on a matrix of Petri dishes; the original weight of deposited material in each sample is used, after complete drying and redissolution in fixed amounts of DI water, to verify the conductivity-concentration and absorbance-concentration laws. The two analyses show promising correlations, justifying an extended test campaign through further experiments, more representative of the actual spraying systems.
{"title":"Cost-effective tracing techniques for the rapid characterization of spray deposition and drift through electrical conductivity and fluorescence","authors":"A. Altana, Lorenzo Becce, E. Avancini, P. Lugli, L. Petti, F. Mazzetto","doi":"10.1109/MetroAgriFor55389.2022.9964955","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964955","url":null,"abstract":"The investigation of the performance of agricultural sprayer through drift and deposition sampling directly on field is of extreme importance, especially in view of ensuring an effective and optimal administration of plant protection products (PPP), necessary to limit waste of products and damages to the ecosystems. This is however a time and resource-intensive activity, typically resulting in highly variable results due to the unpredictable and uncontrollable atmospheric and operating conditions under which sprayers usually operate. To minimize the measurement uncertainties while also simpli-fying the procedures and reducing costs, in this work we propose a deposition assessment protocol based on the spraying of two distinct tracer solutions, leveraging two well-known phenomena: one based on optical absorbance, and the other on electrical conductivity. Although the selected tracers, namely uranine and potassium chloride, are already extensively used in other applications for their non-toxicity to both bystanders and environment, very little is published about their use in spray drift applications; the results obtained on the test bench promise to reduce the experiment costs, simplify the measurement, increase the reproducibility and facilitate the test automation. A test bench for nozzles has been employed to deposit the solutions on a matrix of Petri dishes; the original weight of deposited material in each sample is used, after complete drying and redissolution in fixed amounts of DI water, to verify the conductivity-concentration and absorbance-concentration laws. The two analyses show promising correlations, justifying an extended test campaign through further experiments, more representative of the actual spraying systems.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129221543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964902
Basavaraj R. Amogi, R. Ranjan, L. Khot
To tackle weather uncertainties and associated heat stress to apple fruits, researchers have been exploring development of a real-time crop stress monitoring systems. Our group have been researching one such in-field sensing system that uses localized weather and thermal-RGB imagery proceed on the edge for monitoring fruit surface temperature (FST). Such solutions can be tied with mitigation techniques (e.g., water-based cooling methods) as precision management. However, current edge compute algorithms are limited to segment thermal-RGB imagery for the red pigmented fruits near maturity and lack the green fruit segmentation, limiting the usability of the in-field sensing system. Aim of this study was to develop and validate a color independent fruit segmentation algorithm for successful FST monitoring. Longwave infrared (LWIR) imagery at daily peak air temperature was utilized to achieve temperature gradient aided fruit segmentation and to estimate FST for next 24-h. The algorithm robustness was field evaluated in Fog-Net (combination of fogging and netting) cooling and control treatments (Year 2021). Overall, algorithm accurately detected fruits in early growing season when fruits are green and effectively captured the treatment effects based on FST data. Additionally, the algorithm was also evaluated for computational overhead and estimated FST accuracy on an in-field sensing node (Control treatment) deployed in commercial apple orchard (Year 2022). CPSS took 12 milliseconds to process LWIR image with no CPU throttles and there was no significant difference between $boldsymbol{(mathrm{R}^{2}=0.98}$, p-value = 0.1607) FST estimated using LWIR (FSTi) and thermal-RGB based (FST_Actual) image processing algorithm.
{"title":"Reliable image processing algorithm for sunburn management in green apples","authors":"Basavaraj R. Amogi, R. Ranjan, L. Khot","doi":"10.1109/MetroAgriFor55389.2022.9964902","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964902","url":null,"abstract":"To tackle weather uncertainties and associated heat stress to apple fruits, researchers have been exploring development of a real-time crop stress monitoring systems. Our group have been researching one such in-field sensing system that uses localized weather and thermal-RGB imagery proceed on the edge for monitoring fruit surface temperature (FST). Such solutions can be tied with mitigation techniques (e.g., water-based cooling methods) as precision management. However, current edge compute algorithms are limited to segment thermal-RGB imagery for the red pigmented fruits near maturity and lack the green fruit segmentation, limiting the usability of the in-field sensing system. Aim of this study was to develop and validate a color independent fruit segmentation algorithm for successful FST monitoring. Longwave infrared (LWIR) imagery at daily peak air temperature was utilized to achieve temperature gradient aided fruit segmentation and to estimate FST for next 24-h. The algorithm robustness was field evaluated in Fog-Net (combination of fogging and netting) cooling and control treatments (Year 2021). Overall, algorithm accurately detected fruits in early growing season when fruits are green and effectively captured the treatment effects based on FST data. Additionally, the algorithm was also evaluated for computational overhead and estimated FST accuracy on an in-field sensing node (Control treatment) deployed in commercial apple orchard (Year 2022). CPSS took 12 milliseconds to process LWIR image with no CPU throttles and there was no significant difference between $boldsymbol{(mathrm{R}^{2}=0.98}$, p-value = 0.1607) FST estimated using LWIR (FSTi) and thermal-RGB based (FST_Actual) image processing algorithm.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123972153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964578
Karisma Yumnam, M. Cann, L. Khot, David J. Brown, Joseph P. Boomgard-Zagrodnik, L. Kalcsits
Accurate site-specific weather forecasts, observations, and decision support tools are crucial for timely tree fruit orchard management. However, these tools are often biased as orchards have different microclimates than the standard open field meteorological weather stations. The orchard effects, which are the effects of cropland on hyperlocal weather conditions, need to be corrected or adjusted for accurate site-specific weather. In this study, the orchard effects on solar radiation, air temperature, relative humidity and wind speed are quantified for three commercial apple orchards at seasonal, daily, and hourly time scales. Results suggest that the orchard microclimates have lower average daily solar radiation (28.8 W m−2 to 93.2 W m−2), air temperature (0.23 °C to 1.21 °C), and wind speed (1.1 m s−1 to 1.32 m s−1). Orchard effects have seasonal variability and depend on the phenological growth stages of the canopies. Orchard effects were stronger during the summer season and lowest during the winter season. For instance, the peak air temperature offset during the summer is 3 °C, while the same for the winter season is 1 °C. The orchard effects also differ during daytime and nighttime hours. In particular, the air temperature inside the orchard is cooler by 1 °C to 3 °C during the nighttime while, the same varies from -1.5 °C to 3 °C during daytime. Overall, all the three orchards trained in different architecture show similar pattern of the orchard effects.
准确的特定地点天气预报、观测和决策支持工具对果树果园的及时管理至关重要。然而，这些工具往往有偏差，因为果园的小气候与标准的露天气象气象站不同。果园效应，即农田对超局部天气条件的影响，需要根据准确的特定地点天气进行纠正或调整。本研究在季节、日、小时三个时间尺度上定量分析了果园对太阳辐射、气温、相对湿度和风速的影响。结果表明，果园小气候具有较低的日平均太阳辐射(28.8 ~ 93.2 W m−2)、气温(0.23 ~ 1.21℃)和风速(1.1 ~ 1.32 m s−1)。果园效应具有季节变异性，并取决于冠层的物候生长阶段。果园效应在夏季最强，在冬季最低。例如，夏季的最高气温偏移为3°C，而冬季的最高气温偏移为1°C。果园的效果在白天和夜间也有所不同。特别是，果园内的气温夜间为1 ~ 3°C，白天为-1.5 ~ 3°C。总体而言，三个不同建筑训练的果园都表现出相似的果园效应模式。
{"title":"Quantification of Modern Apple Orchard Effects on Meteorological Variables","authors":"Karisma Yumnam, M. Cann, L. Khot, David J. Brown, Joseph P. Boomgard-Zagrodnik, L. Kalcsits","doi":"10.1109/MetroAgriFor55389.2022.9964578","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964578","url":null,"abstract":"Accurate site-specific weather forecasts, observations, and decision support tools are crucial for timely tree fruit orchard management. However, these tools are often biased as orchards have different microclimates than the standard open field meteorological weather stations. The orchard effects, which are the effects of cropland on hyperlocal weather conditions, need to be corrected or adjusted for accurate site-specific weather. In this study, the orchard effects on solar radiation, air temperature, relative humidity and wind speed are quantified for three commercial apple orchards at seasonal, daily, and hourly time scales. Results suggest that the orchard microclimates have lower average daily solar radiation (28.8 W m−2 to 93.2 W m−2), air temperature (0.23 °C to 1.21 °C), and wind speed (1.1 m s−1 to 1.32 m s−1). Orchard effects have seasonal variability and depend on the phenological growth stages of the canopies. Orchard effects were stronger during the summer season and lowest during the winter season. For instance, the peak air temperature offset during the summer is 3 °C, while the same for the winter season is 1 °C. The orchard effects also differ during daytime and nighttime hours. In particular, the air temperature inside the orchard is cooler by 1 °C to 3 °C during the nighttime while, the same varies from -1.5 °C to 3 °C during daytime. Overall, all the three orchards trained in different architecture show similar pattern of the orchard effects.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116063675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964747
Giovanni Carabin, Lorenzo Becce, Andreas Mandler, F. Mazzetto
The abandonment of mountain agriculture in Europe is a phenomenon that has been going on since the post-war period to the present day. This is because the hostile environment, more adverse climatic conditions, lower yields and lack of space have always favoured crops in flat locations. However, this has led to a more or less marked abandonment of the mountains by the local population. The BROTWEG project was born with the aim of reversing this trend by developing and providing the technologies for sustainable and mechanized cereal cultivation even in the high mountains. This in particular following a short supply chain system: (a) cultivation of cereals in small/medium plots by creating new technologies for mechanised seeding - avoiding the erosion-prone tillage - and harvesting on steep slopes up to 80%, (b) post-harvest operations (drying and milling) carried out directly within the farm, (c) bread-making. In this scenario, monitoring the crops, as well as the field yield, becomes very important and necessary to promptly respond to any issue and thus ensuring a successful harvest. In this work an attempt is made to estimate the field yield by means of spectrographic surveys, conducted with a UAV. The idea is to discern between crops and weeds by evaluating some vegetation indices: when the grain reaches the maturity its viability is very low, whereas that of the weed remains medium/high. Therefore, a low vitality in an area means high productivity since all the analysed space is suppose to be covered by only grain.
{"title":"Primary Production Prediction from Aerial Spectrographic Survey","authors":"Giovanni Carabin, Lorenzo Becce, Andreas Mandler, F. Mazzetto","doi":"10.1109/MetroAgriFor55389.2022.9964747","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964747","url":null,"abstract":"The abandonment of mountain agriculture in Europe is a phenomenon that has been going on since the post-war period to the present day. This is because the hostile environment, more adverse climatic conditions, lower yields and lack of space have always favoured crops in flat locations. However, this has led to a more or less marked abandonment of the mountains by the local population. The BROTWEG project was born with the aim of reversing this trend by developing and providing the technologies for sustainable and mechanized cereal cultivation even in the high mountains. This in particular following a short supply chain system: (a) cultivation of cereals in small/medium plots by creating new technologies for mechanised seeding - avoiding the erosion-prone tillage - and harvesting on steep slopes up to 80%, (b) post-harvest operations (drying and milling) carried out directly within the farm, (c) bread-making. In this scenario, monitoring the crops, as well as the field yield, becomes very important and necessary to promptly respond to any issue and thus ensuring a successful harvest. In this work an attempt is made to estimate the field yield by means of spectrographic surveys, conducted with a UAV. The idea is to discern between crops and weeds by evaluating some vegetation indices: when the grain reaches the maturity its viability is very low, whereas that of the weed remains medium/high. Therefore, a low vitality in an area means high productivity since all the analysed space is suppose to be covered by only grain.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116187246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964881
Nicolas Tapia Zapata, Nikos Tsoulias, Kowshik Kumar Saha, M. Zude-Sasse
Describing and monitoring fruit size along the supply chain plays a key role in assessment of fruit quality by non-destructive technologies contributing to resilience against climate change. Light detection and ranging (LiDAR) laser scanner can provide 3D point cloud of physical objects. This work developed a method to estimate the surface shape of partially scanned spheres (60 mm, 80 mm) previously scanned and manually segmented. The method was tested on a 3D point cloud of a scanned apple described by a Fourier series expansion. An ideal sphere point cloud was obtained by geometry generator software, and subsequently the 2D signature in spherical coordinates of the 3D point cloud was described by 1-D and 2-D Fourier series expansion, which served as the reference 2D signature for each scanned point cloud. Data preprocessing captured outlier removal by means of interquartile range (IQR) algorithm. Subsequently, the eigenvectors of each point cloud were estimated using singular value decomposition algorithm, where an estimated sphere centroid was approximated iteratively based on a root mean squared error (RMSE) minimization of each point cloud respect to an ideal sphere. The $boldsymbol{text { RMSE }_{text {min }}}$ reached 4,94 mm and 4,34 mm for the spheres of 60 and 80 mm diameter, respectively. Moreover, the diameter estimation of an apple was approximated by using a Fourier series expansion, showing an approximated error of 0.99%.
{"title":"Fourier analysis of LiDAR scanned 3D point cloud data for surface reconstruction and fruit size estimation","authors":"Nicolas Tapia Zapata, Nikos Tsoulias, Kowshik Kumar Saha, M. Zude-Sasse","doi":"10.1109/MetroAgriFor55389.2022.9964881","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964881","url":null,"abstract":"Describing and monitoring fruit size along the supply chain plays a key role in assessment of fruit quality by non-destructive technologies contributing to resilience against climate change. Light detection and ranging (LiDAR) laser scanner can provide 3D point cloud of physical objects. This work developed a method to estimate the surface shape of partially scanned spheres (60 mm, 80 mm) previously scanned and manually segmented. The method was tested on a 3D point cloud of a scanned apple described by a Fourier series expansion. An ideal sphere point cloud was obtained by geometry generator software, and subsequently the 2D signature in spherical coordinates of the 3D point cloud was described by 1-D and 2-D Fourier series expansion, which served as the reference 2D signature for each scanned point cloud. Data preprocessing captured outlier removal by means of interquartile range (IQR) algorithm. Subsequently, the eigenvectors of each point cloud were estimated using singular value decomposition algorithm, where an estimated sphere centroid was approximated iteratively based on a root mean squared error (RMSE) minimization of each point cloud respect to an ideal sphere. The $boldsymbol{text { RMSE }_{text {min }}}$ reached 4,94 mm and 4,34 mm for the spheres of 60 and 80 mm diameter, respectively. Moreover, the diameter estimation of an apple was approximated by using a Fourier series expansion, showing an approximated error of 0.99%.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129275160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964631
Ing. Richard Marko, Bc. Zuzana Gáborčíková, Bc. Filip Chalás, Bc. Marek Janec, Bc. Rastislav Kavoň, Bc. Matúš Miklovič, Bc. Peter Nemček, Bc. Katarína Valkovičová, Mgr. Martin Sabo
The amount of CBD in technical hemp is one of the key harvesting factors for farmers. The solutions that currently exist for them are both time-consuming and costly. This project focuses on determining the day of harvesting the hemp based on data from the ion mobility spectrometer. Samples of cannabis used in this project were collected every two days for one month. Data were represented using spectra captured every 180 ms. These data were preprocessed, cleaned, normalized and the most appropriate predictors were selected, aggregated into one row for each measurement and trained regression models that were able to correctly predict the day of harvest with a mean error of about 1.3 day. Research has shown potential in this area and although the work is not yet final, it offers opportunities for adjustment and improvement.
{"title":"Ion Mobility Spectrometry for Rapid HEMP Potency Testing - spectrometric testing of technical hemp","authors":"Ing. Richard Marko, Bc. Zuzana Gáborčíková, Bc. Filip Chalás, Bc. Marek Janec, Bc. Rastislav Kavoň, Bc. Matúš Miklovič, Bc. Peter Nemček, Bc. Katarína Valkovičová, Mgr. Martin Sabo","doi":"10.1109/MetroAgriFor55389.2022.9964631","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964631","url":null,"abstract":"The amount of CBD in technical hemp is one of the key harvesting factors for farmers. The solutions that currently exist for them are both time-consuming and costly. This project focuses on determining the day of harvesting the hemp based on data from the ion mobility spectrometer. Samples of cannabis used in this project were collected every two days for one month. Data were represented using spectra captured every 180 ms. These data were preprocessed, cleaned, normalized and the most appropriate predictors were selected, aggregated into one row for each measurement and trained regression models that were able to correctly predict the day of harvest with a mean error of about 1.3 day. Research has shown potential in this area and although the work is not yet final, it offers opportunities for adjustment and improvement.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115048169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9965022
G. Bortolotti, D. Mengoli, M. Piani, L. C. Grappadelli, L. Manfrini
In Italy, peaches are paid according to size, color and appearance. Real time fruit harvest quality information could support growers and the whole fruit chain improving segmented selection for consumers as well as to increase growers' income. In this study, a computer vision system was tested aiming to quantifying and sizing peaches in bins at harvest time. Two different depth cameras the Intel RealSense D435i and D455, and two different light conditions, natural and artificial, were tested, to assess potential issues and to achieve the most suitable set-up for future developments. Automated fruit detection appeared less difficult, while the system presents generally overestimation in fruit size. The D435i camera in artificial light condition obtained the best outcome with a RMSE of 17.91 mm, compared to the reference diameter of measured fruit. Although the results obtained are with low accuracy and precision, the vision systems technique seems promising and suggests solutions to further improvements. Future studies will focus on improving the system for sizing and color estimation, coupled to georeferenced data directly in the field with the aim of mapping field quality variability. The idea is to develop a low-cost tool that coupled to harvesting platforms connects fruit quality at the time of harvest to post-harvest operations.
{"title":"A computer vision system for in-field quality evaluation: preliminary results on peach fruit","authors":"G. Bortolotti, D. Mengoli, M. Piani, L. C. Grappadelli, L. Manfrini","doi":"10.1109/MetroAgriFor55389.2022.9965022","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9965022","url":null,"abstract":"In Italy, peaches are paid according to size, color and appearance. Real time fruit harvest quality information could support growers and the whole fruit chain improving segmented selection for consumers as well as to increase growers' income. In this study, a computer vision system was tested aiming to quantifying and sizing peaches in bins at harvest time. Two different depth cameras the Intel RealSense D435i and D455, and two different light conditions, natural and artificial, were tested, to assess potential issues and to achieve the most suitable set-up for future developments. Automated fruit detection appeared less difficult, while the system presents generally overestimation in fruit size. The D435i camera in artificial light condition obtained the best outcome with a RMSE of 17.91 mm, compared to the reference diameter of measured fruit. Although the results obtained are with low accuracy and precision, the vision systems technique seems promising and suggests solutions to further improvements. Future studies will focus on improving the system for sizing and color estimation, coupled to georeferenced data directly in the field with the aim of mapping field quality variability. The idea is to develop a low-cost tool that coupled to harvesting platforms connects fruit quality at the time of harvest to post-harvest operations.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128373500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964531
L. Rossi, C. Bibbiani, B. Fronte, E. Damiano, A. Di Lieto
Aquaculture is one of the most important food production sector in the world. Feed represents a relevant cost in fish farming activity, as well as a considerable source of environmental pollution. The need of precisely estimate the fish biomass and stocking density is crucial to avoid overfeeding, thus pollution and economic loss. Recently a cheap dynamic scale (by MEGA Materials srl) has been developed, based on a board of the Arduino family, suitable to measure live-fish weights. Bluetooth transmitter and a specific app allowed the communication to smartphones and laptops. In this validation campaign a comparison of static Lab scale vs. four different acquisition patterns of the dynamic scale is presented, consisting in repeated series of measurement. The aim is to measure the weight of seabream juveniles/adult reared in both off-shore and in-land facilities, saving time and keeping high precision. The comparison of measurement within static Lab scale and dynamic scale shows significant differences (P<0.0001), highlighting that the dynamic scale achieved steady weight measurement after few reps. The most performing measurement setting of dynamic scale was proven to be 8*10, having eight repeated measures each as average out of ten readings in 1 second time-lap.
{"title":"Validation campaign of a smart dynamic scale for measuring live-fish biomass in aquaculture","authors":"L. Rossi, C. Bibbiani, B. Fronte, E. Damiano, A. Di Lieto","doi":"10.1109/MetroAgriFor55389.2022.9964531","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964531","url":null,"abstract":"Aquaculture is one of the most important food production sector in the world. Feed represents a relevant cost in fish farming activity, as well as a considerable source of environmental pollution. The need of precisely estimate the fish biomass and stocking density is crucial to avoid overfeeding, thus pollution and economic loss. Recently a cheap dynamic scale (by MEGA Materials srl) has been developed, based on a board of the Arduino family, suitable to measure live-fish weights. Bluetooth transmitter and a specific app allowed the communication to smartphones and laptops. In this validation campaign a comparison of static Lab scale vs. four different acquisition patterns of the dynamic scale is presented, consisting in repeated series of measurement. The aim is to measure the weight of seabream juveniles/adult reared in both off-shore and in-land facilities, saving time and keeping high precision. The comparison of measurement within static Lab scale and dynamic scale shows significant differences (P<0.0001), highlighting that the dynamic scale achieved steady weight measurement after few reps. The most performing measurement setting of dynamic scale was proven to be 8*10, having eight repeated measures each as average out of ten readings in 1 second time-lap.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"78 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131673225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964833
Ester Scotto di Perta, P. Giudicianni, C. M. Grottola, Antonio Mautone, E. Cervelli, R. Ragucci, S. Pindozzi
Biochar has been recently investigated as an alternative to the floating cover applied during manure storage, for its interesting durability and hydrophobicity. Pyrolysis parameters play an important role in affecting physic-chemical biochar characteristics, such as pH, porosity, and specific surface. This paper aims at comparing the $boldsymbol{text{NH}_{3}}$ emissions that occurred after the application of two types of biochar, produced at 285 and $boldsymbol{450^{circ} mathrm{C}}$ (namely under torrefaction and pyrolysis regime, respectively). Results showed that biochar at $boldsymbol{285^{circ} mathrm{C}}$ emitted 42 % less $boldsymbol{text{NH}_{3}}$ than the other one. Generally, $boldsymbol{text{NH}_{3}}$ emissions rates were in accordance with the free $boldsymbol{text{NH}_{3}}$ in the liquid solution. On the other hand, the greater adsorption capacity of biochar at $boldsymbol{mathbf{4 5 0}^{circ} mathrm{C}}$ does not seem to have played a relevant role in reducing ammonia emissions, confirming that the “lid” action is prevailing in limiting the gaseous exchange.
{"title":"Biochar covering to mitigate the ammonia emissions from the manure storage tank: Effect of the pyrolysis temperature","authors":"Ester Scotto di Perta, P. Giudicianni, C. M. Grottola, Antonio Mautone, E. Cervelli, R. Ragucci, S. Pindozzi","doi":"10.1109/MetroAgriFor55389.2022.9964833","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964833","url":null,"abstract":"Biochar has been recently investigated as an alternative to the floating cover applied during manure storage, for its interesting durability and hydrophobicity. Pyrolysis parameters play an important role in affecting physic-chemical biochar characteristics, such as pH, porosity, and specific surface. This paper aims at comparing the $boldsymbol{text{NH}_{3}}$ emissions that occurred after the application of two types of biochar, produced at 285 and $boldsymbol{450^{circ} mathrm{C}}$ (namely under torrefaction and pyrolysis regime, respectively). Results showed that biochar at $boldsymbol{285^{circ} mathrm{C}}$ emitted 42 % less $boldsymbol{text{NH}_{3}}$ than the other one. Generally, $boldsymbol{text{NH}_{3}}$ emissions rates were in accordance with the free $boldsymbol{text{NH}_{3}}$ in the liquid solution. On the other hand, the greater adsorption capacity of biochar at $boldsymbol{mathbf{4 5 0}^{circ} mathrm{C}}$ does not seem to have played a relevant role in reducing ammonia emissions, confirming that the “lid” action is prevailing in limiting the gaseous exchange.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122427519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.1109/MetroAgriFor55389.2022.9964489
Andrea Mangeruca, G. Ferrari, A. Garinei, Lucia Cisco, Maurizio Sozzi, M. Marconi, M. Crespi, Andrea Chini, E. Piccioni, D. Bavera, G. Frigerio
Snow Water Equivalent (SWE) represents the amount of water available at melt in the snowpack. It is an important source of water, stored during wet season, and made available with a certain delay, during warmer and dryer period, somehow naturally compensating the lack of direct precipitation contribution. This melting water can be used for all the human activities as for drinking water, crop irrigation, energy production, etc. Knowing in advance the amount of this resource and the timing of its availability could be strategic in improving water resources management. An innovative, flexible and reliable methodology is here proposed for SWE assessment.
{"title":"Snow water equivalent (SWE) measurements for better management of water resources to reduce drought risk","authors":"Andrea Mangeruca, G. Ferrari, A. Garinei, Lucia Cisco, Maurizio Sozzi, M. Marconi, M. Crespi, Andrea Chini, E. Piccioni, D. Bavera, G. Frigerio","doi":"10.1109/MetroAgriFor55389.2022.9964489","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964489","url":null,"abstract":"Snow Water Equivalent (SWE) represents the amount of water available at melt in the snowpack. It is an important source of water, stored during wet season, and made available with a certain delay, during warmer and dryer period, somehow naturally compensating the lack of direct precipitation contribution. This melting water can be used for all the human activities as for drinking water, crop irrigation, energy production, etc. Knowing in advance the amount of this resource and the timing of its availability could be strategic in improving water resources management. An innovative, flexible and reliable methodology is here proposed for SWE assessment.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130990832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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