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

{"title":"e-SmallFarmer - A solution for small farming","authors":"D. Pinto, R. Alves, Paulo Matos, D. Pousa","doi":"10.1109/MetroAgriFor50201.2020.9277558","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277558","url":null,"abstract":"The emergence of concepts such as Internet of Things, Cloud Computing has been adding improvements in different sectors of human life activity. The agricultural sector is no exception, and it begins to appear the first systems that use these new concepts, as is the case of, use of drones and associated technology applied to fighting pests or the use of sensor networks to monitor productions. However, the technological gap between urban and rural areas is becoming ever wider, and the arrival of these new concepts in rural areas is taking place very slowly. In order to accelerate this technological transformation, it’s necessary to find tools that reduce these differences, leveraging these rural regions in terms of technology and, at the same time, providing access to new markets. In this article is proposed, a solution to the problem of the lack of production flow, allowing producers in low-density regions to access markets that until now would be impossible to reach, while providing an solution to the problem of shortage of labour and the increase in abandoned land in Portugal.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"27 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":"123220732","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}

{"title":"Effect of mitigation techniques on ammonia emissions and nutrients recovery: the role of fertigation with digestate","authors":"V. Guido, A. Finzi, P. Piazzi, O. Ferrari, Celeste Righi Ricco, E. Riva, G. Provolo","doi":"10.1109/MetroAgriFor50201.2020.9277608","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277608","url":null,"abstract":"Digestate is an important source of nutrients for crops but if not properly managed its use can cause environmental problems, mainly caused by nitrogen losses. Appropriate techniques are required for its field application in order to reduce nitrogen losses and increase the nitrogen use efficiency (NUE). Under the ARIMEDA project (LIFE16 ENV/ES/000400), two different fertigation techniques (drip and pivot irrigation systems) were assessed on maize by using the digestate liquid fraction. A two-year field test was carried out in Lombardy, testing fertigation with pivot or drip systems compared to reference fields irrigated using the same systems and fertilized with digestate applied at base dressing with broadcast spreader. Both pivot and drip irrigation systems were suitable for fertigation of maize with digestate. The obtained results reveal the feasibility and the positive effect on nitrogen use efficiency and nitrogen emissions of this technique, if digestate is properly managed, adequately filtered according to the fertigation technique and combined with appropriate spreading technique in pre-sowing fertilisation.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"65 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":"124885966","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}

{"title":"Analysis of performances of a commercial three-dimensional (3D) reconstruction camera","authors":"D. Giora, A. Pezzuolo, D. Tomasi, F. Marinello, L. Sartori","doi":"10.1109/MetroAgriFor50201.2020.9277585","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277585","url":null,"abstract":"In the last decade, the interest on instrumentation for three-dimensional (3D) reconstruction has increased, in particular for the possibility of characterizing phenology and physical characteristics of agricultural products. The present work evaluates the suitability of a low-cost instrument for fast generation of three-dimensional digital models: focus of the present study is the evaluation of accuracy of 3D point clouds. The instrument relies on an IR-depth sensing camera and an RGB camera, both allowing rapid digital reconstruction of scanned objects. The evaluation has been carried on a bunch of grapes under different operating parameters (e.g. scanning speed, distances of the target from the instrument) reproduced in laboratory conditions.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"151 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":"122086723","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}

{"title":"Towards rapid detection and mapping of powdery mildew in apple orchards","authors":"A. Chandel, L. Khot, B. Sallato","doi":"10.1109/MetroAgriFor50201.2020.9277544","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277544","url":null,"abstract":"Powdery mildew (PM) in apples is a critical fungal disease that adversely affects yield and fruit quality. Conventional PM identification techniques are laborious. This study evaluated the suitability of non-destructive low altitude imaging in the visible (RGB) and multispectral domain for PM detection in apple orchards. Imagery snapshots were acquired at known locations of PM infestation in apple trees using two small unmanned aerial systems (UAS). One UAS employed a consumer grade RGB camera while other UAS had a five-band multispectral imaging sensor. Custom image processing algorithms were developed for RGB and multispectral imagery analysis. The RGB images were classified using k-means and resulted in PM detection accuracy of 76.4%. A strong agreement was also observed between the number of actual PM clusters and clusters that were classified (R2 = 0.94). Seven vegetation indices (VIs) were extracted from the multispectral imagery as the potential chlorophyll variation indicators. Such indices showed significant difference (p < 0.05) for PM infected leaves and the healthy leaves. Modified Simple Ratio-Red, Modified Simple Ratio-Blue and Optimized Soil Adjusted Vegetation Index were the key differentiators showing low values for PM (Mean: 0.01–0.05) and high values for healthy leaves (Mean: 0.51–0.84). Overall, results showed the potential to detect and quantify PM infestation in apple orchards at high spatial resolution. Additional efforts are needed to translate these results to map PM infestation at the orchard block level that could aid in site-specific remedial measures.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"87 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":"124557120","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}

{"title":"Characterization of the main physico-chemical parameters in three styles of craft beer","authors":"L. Liguori, Giovanni de Francesco, G. Perretti, D. Albanese","doi":"10.1109/MetroAgriFor50201.2020.9277673","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277673","url":null,"abstract":"The beer is a widely consumed drink, appreciated for its sensory characteristics. Beer also contains beneficial compounds for health derived from its raw materials. In recent years there is an expansion of craft breweries in many countries, with a growing market share. Consumers are more and more attracted by craft beers that are perceived as higher quality and with a more complex flavour profile than commercial ones. Drawbacks are the difficulty to standardize method used for their production causing variability in some quality parameters. In this study the results of the main physico-chemical parameters used for the characterization of beer are reported with the aim to highlight as the type of recipe affect the quality of three styles of craft beer: Session India Pale Ale, Dark Ale and Blonde Ale.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"19 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":"131437807","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}

{"title":"On-the-go variable rate fertilizer application on vineyard using a proximal spectral sensor","authors":"M. Sozzi, Enrico Bernardi, A. Kayad, F. Marinello, D. Boscaro, A. Cogato, F. Gasparini, D. Tomasi","doi":"10.1109/MetroAgriFor50201.2020.9277569","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277569","url":null,"abstract":"Spatial variability represents a challenge for viticulture. Variable-rate fertilization is a promising technology to manage different vigor and yield zones within the. In this study, on-the-go variable rate fertilization system was implemented and tested, based on commercial spectral sensors. GreenSeeker Normalized Difference Vegetation Index (NDVI) sensor was mounted in front of a tractor and connected to the electronic control unit of a variable rate spreader. Fertilizer rate was based on threshold values of NDVI, calibrated previously in ten sampling points by a GreenSeeker handheld sensor. The sampling points were selected according to the agronomist expertise on vineyard variability. A couple of GreenSeeker sensors carried by tractor and connected to the fertilizer electronic control unit were used for fertilizer dosage definition. Fertilizer application was evaluated comparing the amount of fertilizer distributed in the sample points with the prescribed dose. Results showed good accuracy of distribution compared with the prescribed amount of fertilizer. Similarly, the fertilizer distribution showed a significant correlation (R2 = 0.65, p-value < 0.01) with the Leaf Area Index collected in the sampling points. The effects of variable rate fertilizer application on vine vigor were preliminary assessed measuring vine shoot length the day when fertilizer was applied and 14 days after fertilizer application. Linear regression for vine shoots growth rate based on applied fertilizer showed an R2 of 0.6, suggesting a positive effect of the on-the-go variable rate fertilizer application on vines growth. Fertilization effects on field variability were then assessed considering three variability coefficients of NDVI (ʍ, Gini, and CV). The comparison between variability coefficients of the years before and after the fertilizer application showed a reduction of 37%, 43%, and 40% for ı, Gini, and CV, respectively. The results highlight the potential of proximal spectral sensors for on-the-go variable rate fertilization and reduction of in-field variability in vineyards.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"41 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":"131587828","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}

{"title":"Calibration equation and field test of a capacitive soil moisture sensor","authors":"Gilberto Souza, Brenno Tondato de Faria, Rafael Gomes Alves, Fábio Lima, P. Aquino, J. Soininen","doi":"10.1109/MetroAgriFor50201.2020.9277634","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277634","url":null,"abstract":"A key point to decrease water usage in agriculture is to employ precision agriculture by adopting technologies such as the Internet of Things (IoT). Many solutions using the IoT rely on the use of soil moisture sensors to gather data, in real-time, from the plant’s root zone. This study presents a linear calibration curve, obtained by the thermogravimetric method, for a capacitive soil moisture sensor for a silty clay soil sampled at the FEI University Center. The curve obtained has an adjusted R2 of 0.86 and a residual standard error of 2.8%. The soil sensor was tested in the field during the end of February revealing that the sensor is capable of indicating changes in soil moisture within the error obtained from the calibration procedure and that it can be used to indicate changes by rain or irrigation procedures.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"19 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":"114516802","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}

{"title":"Neural networks for Pest Detection in Precision Agriculture","authors":"A. Segalla, G. Fiacco, Luca Tramarin, M. Nardello, D. Brunelli","doi":"10.1109/MetroAgriFor50201.2020.9277657","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277657","url":null,"abstract":"Apple is one of the most produced fruit crops in the world. Recent advances in Artificial Intelligence and the Internet of Things can reduce production costs and improve crop quality by providing prompt detection of dangerous parasites. This paper presents an effective solution to automate the detection of the Codling Moths. The system takes pictures of trapped insects in the orchard, analyzes them through a DNN algorithm, and sends alarms to the farmer in case of a positive detection. The system is fully autonomous and can operate unattended for the entire crop season. Detection reports are used for optimizing the treatment with chemicals only when threats are identified. The prototype is designed with an embedded platform powered by a small solar panel to achieve an energy-neutral balance.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"246 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":"124708404","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}

{"title":"Using a gamma-ray spectrometer for soil moisture monitoring: development of the the gamma Soil Moisture Sensor (gSMS)","authors":"S. van der Veeke, R. Koomans, H. Limburg","doi":"10.1109/MetroAgriFor50201.2020.9277560","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277560","url":null,"abstract":"A new type of soil moisture sensor has been developed that uses gamma-rays emitted by the soil to determine the soil moisture content. Natural radionuclides emit radiation that is detected by this gamma Soil Moisture Sensor (gSMS). Gamma-rays are attenuated by moisture in the soil and therefore the flux of gamma photons could act as a proxy for the amount of moisture present in the soil. Preliminary results show that the total gamma flux seen by the sensor is also influenced by variations in atmospheric radon concentrations. Therefore, the total gamma count cannot be used as a proxy for soil moisture and spectral analysis is needed to filter out the radon-induced noise and correlate the 40K and 232Th concentration with the soil moisture content. Static measurements have been initiated to determine the accuracy needed for establishing the soil moisture content variation over time.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"25 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":"125142813","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}

{"title":"Design Concept and Modelling of a Tracked UGV for Orchard Precision Agriculture","authors":"Roberto Tazzari, D. Mengoli, L. Marconi","doi":"10.1109/MetroAgriFor50201.2020.9277577","DOIUrl":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277577","url":null,"abstract":"We present a ground robotic platform suited to agriculture applications. The design is specifically targeted for small/medium farms and it is characterized by marked features in terms of flexibility, reconfigurability and robustness.We present the tracked vehicle design concept as well as the mechanical model by emphasizing some aspects that make the platform particularly suited to operate in \"all-terrains\". We also present experimental results to validate the model.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"161 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":"114652722","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}