2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)最新文献_第6页

Performance of different rice varieties under drip irrigation 不同水稻品种在滴灌条件下的生产性能

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277628

S. Monaco, P. Bottazzi, F. Altobelli

{"title":"Performance of different rice varieties under drip irrigation","authors":"S. Monaco, P. Bottazzi, F. Altobelli","doi":"10.1109/MetroAgriFor50201.2020.9277628","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277628","url":null,"abstract":"The world-wide development and spread of water-saving techniques and new rice genotypes to reduce water consumption and increase water productivity (i.e. the amount of rice produced per unit of water) is crucial for maintaining or even increasing rice production area in several regions. The utilization of varieties adapted to aerobic conditions and the application of precision agriculture technologies could maintain yield levels and optimize water use. Rice cultivation under drip-irrigation could represent an opportunity for farmers but needs to be assessed in field experiments. A field experimentation trial comparing the growth, yield and water use efficiency of rice (Oryza sativa L.) varieties under drip irrigation was established in Maremma Toscana, Italy. The results of the first year of experiment at the Grosseto (GR) site showed that the drip irrigation technique could maintain high production level for most of the varieties evaluated, but with significant differences in terms of milling yield. The assessed farm water consumption for rice cultivation seems high and water use could be optimized through water balance assessment.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668566","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

Ploovium: a decision support system for increasing water use efficiency of irrigated crops Ploovium:提高灌溉作物水分利用效率的决策支持系统

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277616

Andrea Martelli, F. Altobelli, A. dalla Marta, Marco Ciarletti

{"title":"Ploovium: a decision support system for increasing water use efficiency of irrigated crops","authors":"Andrea Martelli, F. Altobelli, A. dalla Marta, Marco Ciarletti","doi":"10.1109/MetroAgriFor50201.2020.9277616","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277616","url":null,"abstract":"Irrigation advisory services (IAS), as well as decision supports systems (DSS) designed for irrigation support, are powerful management instruments used to improve efficiency in irrigation water use. In this context, a preliminary research was conducted in an open field asparagus crop in order to: evaluate Ploovium, a DSS based on IoT, artificial intelligence and machine learning, for a predictive optimization of irrigation. This study was carried out in collaboration with LAORE (Agricultural Development Regional Agency of Sardinia Region), and AGRIS Research Centre, on an asparagus in a farm in Villasor (CA). Experimental activities were carried out from August 01 2018 to July 24 2019. Ploovium is an innovative cloud-based solution, able to produce provisional data on the soil’s water behaviour by the following equipment: i) a weather station for measuring rain, air temperature and humidity; ii) a datalogger with soil water sensors at two different depths (30 cm and 80 cm). Ploovium allowed to optimize water consumption and, consequently, to manage the crop in a more efficient way, and to prevent any possible risk with a degree of reliability normally higher than 99%. Ploovium has proved to be a low cost and know-how solution to support the users to save water and irrigation-related costs and to provides precise hints about the texture of the soil.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129494997","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

Is the biochar an effective floating cover for manure storage to reduce ammonia emissions, adsorbing nitrogen at the same timeƒ 生物炭是粪肥储存的有效浮盖，以减少氨排放，同时吸附氮吗

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277602

Ester Scotto di Perta, P. Giudicianni, Antonio Mautone, S. Caro, E. Cervelli, R. Ragucci, S. Pindozzi

引用次数: 2

Vis/NIR hyperspectral imaging to assess freshness of sardines (Sardina pilchardus) 用可见光/近红外高光谱成像技术评估沙丁鱼(沙丁鱼)的新鲜度

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277603

Leonardo Franceschelli, C. Cevoli, A. Benelli, Eleonora Iaccheri, M. Tartagni, A. Berardinelli

引用次数: 2

Preliminary Design of a Remotely Piloted Aircraft System for Crop-Spraying on Vineyards 葡萄园作物喷洒遥控飞机系统初步设计

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277607

N. Bloise, Manuel Carreño Ruiz, D. D’Ambrosio, G. Guglieri

引用次数: 2

Computer Vision Technology for Quality Monitoring in Smart Drying System 智能干燥系统质量监控的计算机视觉技术

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277543

R. Moscetti, Swathi Sirisha Nallan Chakravartula, A. Bandiera, G. Bedini, R. Massantini

{"title":"Computer Vision Technology for Quality Monitoring in Smart Drying System","authors":"R. Moscetti, Swathi Sirisha Nallan Chakravartula, A. Bandiera, G. Bedini, R. Massantini","doi":"10.1109/MetroAgriFor50201.2020.9277543","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277543","url":null,"abstract":"Drying is one of the most viable and effective preservation technologies to improve the shelf-life of foods. Carrots are among the most consumed vegetables, owing to their nutritional profile as well as their wide use in dried foods, ready-to-eat and ready-to-use convenience products like snacks, meals, and soups. As for the dried products, the quality of produce depends on the timely recognition of the dehydration state. Traditional off-line analyses in combination with drying rates to identify the end-time of the process can fail in identifying process discrepancies and avoiding product degradation. The use of computer vision (CV) as a Process Analytical Technology (PAT) tool in the drying system can be of interest to monitor the drying process and product quality. The objective of this study was to study the drying behavior of carrot slices during drying at 35 °C for 36 h using a smart dryer augmented with computer vision system and load cell. The system developed was effective in measuring the weight, size, and color of the untreated (control) and pre-treated (blanched) carrot slices along the drying time. The image analysis and the weight loss of the slices enabled the prediction of relative moisture content (MC) using linear and thin-layer (Newton-Lewis) models in comparison. The applicability of the models was further evaluated by use of different pretreatments (i.e. blanched at 90 °C for 2 min or not blanched). The results showed promising prediction capability for the linear models, which was independent of time with a Root Mean Square Error (RMSE) similar to the thin-layer models, an adj. R2 > 0.99 as well as both Mean BIAS Error (MBE) and reduced Ȥ2 tending towards zero. The blanching treatment affected the model parameters but negligibly affected the model performances.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134099760","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

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/metroagrifor50201.2020.9277559

引用次数: 0

Irrigation scheduling of tomato crop by combining Sentinel-2 imagery with an agro-hydrological model 基于Sentinel-2遥感影像与农业水文模型的番茄灌溉调度研究

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277564

G. Chirico, Maria Rivoli, A. D. Marta, S. Falanga Bolognesi, G. D’Urso

{"title":"Irrigation scheduling of tomato crop by combining Sentinel-2 imagery with an agro-hydrological model","authors":"G. Chirico, Maria Rivoli, A. D. Marta, S. Falanga Bolognesi, G. D’Urso","doi":"10.1109/MetroAgriFor50201.2020.9277564","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277564","url":null,"abstract":"This study explored the possibility to optimize irrigation scheduling through the integrated use of crop data derived from multispectral satellite imagery and an agro-hydrological model. The study was conducted with reference to an industrial tomato crop in an irrigated open field. Three methods for estimating irrigation needs were compared: estimates obtained with a calibrated AquaCrop model; estimates obtained by applying the AquaCrop model with sequential assimilation of crop cover retrieved from multispectral images; estimates obtained with the IRRISAT irrigation advisory service, based only crop state parameters retrieved from satellite multispectral images. The results confirm the usefulness of integrating agro-hydrological models and satellite observations to improve the prediction of crop water requirements. The agro-hydrological model offers more reliable estimates of the water irrigation requirements in the early stages of crop development, being able to simulate the effect of evaporative losses from the soil, when the canopy cover is still small. On the other hand, satellite data allows reducing model simulation errors in the most advanced stages of crop development and during senescence.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131685656","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

Cooperative Agricultural Operations of Aerial and Ground Unmanned Vehicles 空中和地面无人驾驶车辆的农业合作经营

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277573

Martina Mammarella, L. Comba, A. Biglia, F. Dabbene, P. Gay

引用次数: 15

A data-driven methodology to assess the accumulation risk in agricultural insurance contracts 农业保险合同累积风险评估的数据驱动方法

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI: 10.1109/MetroAgriFor50201.2020.9277619

A. Marini, Loris Francesco Termite, Massimiliano Proietti, A. Garinei, G. Ferrari, M. Marconi

引用次数: 1