2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)最新文献_第6页

Comparison of cosmic-ray neutron sensing and gamma-ray spectrometry for non-invasive soil moisture estimation over a large cropped field 宇宙射线中子感测与伽玛射线能谱法在大面积农田非侵入土壤水分估算中的比较

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964647

S. Gianessi, M. Polo, L. Stevanato, M. Lunardon, G. Baroni

引用次数: 0

Variational Autoencoder for Early Stress Detection in Smart Agriculture: A Pilot Study 智能农业早期应力检测的变分自编码器:试点研究

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964641

Alberto Zancanaro, Giulia Cisotto, Dagmawi Delelegn Tegegn, Sara L. Manzoni, Ivan Reguzzoni, E. Lotti, I. Zoppis

{"title":"Variational Autoencoder for Early Stress Detection in Smart Agriculture: A Pilot Study","authors":"Alberto Zancanaro, Giulia Cisotto, Dagmawi Delelegn Tegegn, Sara L. Manzoni, Ivan Reguzzoni, E. Lotti, I. Zoppis","doi":"10.1109/MetroAgriFor55389.2022.9964641","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964641","url":null,"abstract":"The digitalization of the agrifood market is increasingly demanding for new technologies to support its transition towards smart agriculture, a sustainable food industry, and efficient management of greenhouses and crop breeding. In this work, we aim to exploit two emerging and promising technologies with application to the early detection of stressful conditions in plants. Two high-resolution near-infrared spectrometers, spanning the range from 1350 nm to 2150 nm, were used to acquire the reflectance spectra from a pothos (Epipremnum aureum) in two different hydration conditions, i.e., normal and anomalous. Then, we trained a machine learning model, i.e., a $beta$ -variational autoencoder ($beta$ - VAE), to identify the anomalies in the hydration of the plant over three months of acquisition. We are able to show the feasibility of our proposed combination of near-infrared spectrometry and the $beta$ - VAE to accurately identify anomalies, i.e., to detect stressful conditions in plants. This contributes to the recent and promising advancements in smart agriculture, by exploiting a new generation of high-resolution, portable, and non-destructive near-infrared sensing technology and powerful machine learning data analytics.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"8 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":"116533256","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}

引用次数: 2

Measuring the USLE soil erodibility factor in the unit plots of Sparacia (southern Italy) experimental area 意大利南部Sparacia试验区单元样地USLE土壤可蚀性因子的测定

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964826

V. Bagarello, V. Ferro, V. Pampalone

{"title":"Measuring the USLE soil erodibility factor in the unit plots of Sparacia (southern Italy) experimental area","authors":"V. Bagarello, V. Ferro, V. Pampalone","doi":"10.1109/MetroAgriFor55389.2022.9964826","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964826","url":null,"abstract":"The Universal Soil Loss Equation (USLE) is still widely used to predict soil loss by water erosion and to establish soil conservation measures. In this model, the soil erodibility factor $K$ accounts for the susceptibility of the soil to be eroded due to the detachment and transport processes operated by the erosive agents. According to the USLE scheme, the $K$ factor should be measured on unit plots, i.e., bare plots of given length (22 m) and steepness (9%) tilled along the maximum slope direction, but there is little evidence that there ever existed an actual unit plot between the plots used to develop the USLE. Given the difficulty in collecting sufficient data to adequately measure $K$., the nomograph method was early developed to allow estimation of $K$ based on standard soil properties. First, in this investigation the soil erodibility factor was experimentally determined for the clay soil of the Sparacia (Sicily) experimental station, based on the available measurements collected in two unit plots. Although a limited database was available for this analysis, a very low value (0.0038 t ha h ha−1 MJ−1 mm−1) was determined, which was an order of magnitude lower than the nomograph value. Then, the values of the plot steepness factor $S$ were determined using soil loss measurements collected on plots varying in steepness from 9 to 26% and resulted higher than the estimated values by a well-known literature expression. Finally, the plot length factor $L$ resulted independent of the plot length and equal to one. The former result was explained by the different flow transport capacity in the unit plot and plot with increased steepness, while the result of a constant length factor was supported by other experimental investigations.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"9 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":"122384090","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}

引用次数: 0

Cost-effective tracing techniques for the rapid characterization of spray deposition and drift through electrical conductivity and fluorescence 通过电导率和荧光快速表征喷雾沉积和漂移的成本效益追踪技术

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964955

A. Altana, Lorenzo Becce, E. Avancini, P. Lugli, L. Petti, F. Mazzetto

{"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}

引用次数: 0

A Discrimination of Healthy and Rotten Hazelnuts Using a THz Imaging Scanner 太赫兹成像扫描仪鉴别健康榛子与腐烂榛子

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964672

M. Greco, E. Giovenale, F. Leccese, A. Doria

引用次数: 0

Assessment of the geometrical characteristics of hazelnut intensive orchard by an Unmanned Aerial Vehicle (UAV) 用无人机评价榛子集约化果园几何特征

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964832

Alessandra Vinci, Chiara Traini, D. Farinelli, Raffaella Brigante

{"title":"Assessment of the geometrical characteristics of hazelnut intensive orchard by an Unmanned Aerial Vehicle (UAV)","authors":"Alessandra Vinci, Chiara Traini, D. Farinelli, Raffaella Brigante","doi":"10.1109/MetroAgriFor55389.2022.9964832","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9964832","url":null,"abstract":"Assessing the canopy characteristics of the trees is essential for optimizing agronomic management. In fact, it has been shown that there is a strong relationship between the geometric characteristics (i.e. size and volume) of the tree and quantity of water and fertilizer used for crop management. Normally, tree measurements are carried out using manual method, that is time consuming so seems to be more feasible on few trees. For the first time, this study tested the UAV technology on intensive and high-density hazelnut orchards. The aim was to propose a new automated method for the hazelnut canopy characterization, using a DJI Phantom 4 Multispectral UAV. The results showed a good performance of the method proposed for evaluating the width and the actual volume of the canopy. A criticism was revealed for the height of the canopy probably due to the UAV survey. Anyway, the measurements conducted on the point cloud resulted less time-consuming per each tree and more punctual than manual ones, so less exposed to errors.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"88 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":"128581689","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}

引用次数: 0

On the impact of the stem electrical impedance in neural network algorithms for plant monitoring applications 在植物监测应用的神经网络算法中茎电阻抗的影响

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9965011

Mattia Barezzi, Federico Cum, U. Garlando, Maurizio Martina, D. Demarchi

{"title":"On the impact of the stem electrical impedance in neural network algorithms for plant monitoring applications","authors":"Mattia Barezzi, Federico Cum, U. Garlando, Maurizio Martina, D. Demarchi","doi":"10.1109/MetroAgriFor55389.2022.9965011","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9965011","url":null,"abstract":"Smart agriculture offers an environmental-friendly path with respect to unsustainable farming that depletes the nutrients in the soil leading to a persistent degradation of ecosystems caused by population growth. Artificial Intelligence (AI) can help mitigate this issue by predicting plant health status to reduce the use of chemicals and optimize water usage. This paper proposes a custom framework to train neural networks and a comparison among different models to point out the impact and the importance of the stem electrical impedance in addition to environmental parameters for plant monitoring applications. In particular, the paper demonstrates how stem electrical impedance improves the accuracy of the proposed neural network application for plant status classification. The data set is composed of electrical impedance spectra and environmental data acquired on four tobacco plants for a two-month-long experiment. In this paper, we describe the acquisition system architecture, the feature composition of the data set, a general overview of the developed framework, and the training of the neural networks showing the different results considering both the stem impedance and the environmental parameters.","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"89 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":"121198655","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}

引用次数: 1

Clustering of Remotely Sensed Time Series using Functional Principal Component Analysis to Monitor Crops 基于功能主成分分析的作物遥感时间序列聚类研究

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964799

L. Coviello, Francesco Maria Martini, L. Cesaretti, S. Pesaresi, F. Solfanelli, A. Mancini

引用次数: 0

Assessing the potential for forest residue classification and distribution over clear felled areas using UAVs and Machine Learning: a preliminary case study in South Africa 利用无人机和机器学习评估森林残留物分类和分布的潜力:南非的初步案例研究

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9964572

Alberto Udali, B. Talbot, S. Puliti, J. Crous, E. Lingua, S. Grigolato

引用次数: 1

Effects of different forest recovery management on runoff and soil erosion in an area affected by Vaia storm 不同森林恢复管理对Vaia风暴影响地区径流和土壤侵蚀的影响

2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2022-11-03 DOI: 10.1109/MetroAgriFor55389.2022.9965078

A. Andreoli, Felix Pitscheider, Alessio Rozzoni, E. Tomelleri, F. Comiti

{"title":"Effects of different forest recovery management on runoff and soil erosion in an area affected by Vaia storm","authors":"A. Andreoli, Felix Pitscheider, Alessio Rozzoni, E. Tomelleri, F. Comiti","doi":"10.1109/MetroAgriFor55389.2022.9965078","DOIUrl":"https://doi.org/10.1109/MetroAgriFor55389.2022.9965078","url":null,"abstract":"The current study was carried out in a wind damaged forest area and it aims to estimate the effects of management strategies after storm events on runoff and sediment yield. In order to achieve the goal, four experimental plots have been established on an area hit by two windthrows in 2003 and 2018 (Vaia storm). Each plot bound an area of 27 m2 (4.5 m x 6 m) and is located on a 40% slope facing East, previously covered with subalpine spruce forest at about 1650 m asl. The considered forest treatments were (1) salvage logging and natural regeneration, (2) no intervention, and (3) salvage logging and artificial regeneration. We measured runoff and sediments yield from September 2020 to September 2022. Water and sediments mobilized in the experimental plots are convoyed in a 1 m3 tank where the content is weighted by a load cell, and a pressure transducer records the water level. An in-situ radar rain gauge measures cumulative precipitation and intensity. Moreover, sediments samples were collected twice a year, dried and sieved to obtain the percentage of organic material and the texture of the eroded soil. The first results show a contrasting behaviour in terms of runoff/sediment yield between the four plots upon the occurrence of an intense precipitation event. The differences could be explained by the time passed after the windthrow, and the different forest treatments applied. These and future outcomes will be of paramount importance for adapting management strategies to an increasing frequency of subsequential extreme events (windthrow and precipitation).","PeriodicalId":374452,"journal":{"name":"2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"96 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":"132132209","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}

引用次数: 0