Pub Date : 2017-07-01DOI: 10.1017/S2040470017001352
Y. Cohen, N. Agam, I. Klapp, A. Karnieli, O. Beeri, V. Alchanatis, N. Sochen
To use VRI systems, a field is divided into irrigation management zones (IMZs). While IMZs are dynamic in nature, most of IMZs prescription maps are static. High-resolution thermal images (TI) coupled with measured atmospheric conditions have been utilized to map the within-field water status variability and to delineate in-season IMZs. Unfortunately, spaceborne TIs have coarse spatial resolution and aerial platforms require substantial financial investments, which may inhibit their large-scale adoption. Three approaches are proposed to facilitate large-scale adoption of TI-based IMZs: 1) increase of the capacity of aerial TI by enhancing their spatial resolution; 2) sharpening the spatial resolution of satellite TI by fusing satellite multi-spectral images in the visible-near-infrared (VIS-NIR) range; 3) increase the capacity of aerial TI by fusing satellite multi-spectral images in the VIS-NIR range. The scientific and engineering basis of each of the approaches is described together with initial results.
{"title":"Future approaches to facilitate large-scale adoption of thermal based images as key input in the production of dynamic irrigation management zones","authors":"Y. Cohen, N. Agam, I. Klapp, A. Karnieli, O. Beeri, V. Alchanatis, N. Sochen","doi":"10.1017/S2040470017001352","DOIUrl":"https://doi.org/10.1017/S2040470017001352","url":null,"abstract":"To use VRI systems, a field is divided into irrigation management zones (IMZs). While IMZs are dynamic in nature, most of IMZs prescription maps are static. High-resolution thermal images (TI) coupled with measured atmospheric conditions have been utilized to map the within-field water status variability and to delineate in-season IMZs. Unfortunately, spaceborne TIs have coarse spatial resolution and aerial platforms require substantial financial investments, which may inhibit their large-scale adoption. Three approaches are proposed to facilitate large-scale adoption of TI-based IMZs: 1) increase of the capacity of aerial TI by enhancing their spatial resolution; 2) sharpening the spatial resolution of satellite TI by fusing satellite multi-spectral images in the visible-near-infrared (VIS-NIR) range; 3) increase the capacity of aerial TI by fusing satellite multi-spectral images in the VIS-NIR range. The scientific and engineering basis of each of the approaches is described together with initial results.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"20 1","pages":"546-550"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85741892","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 : 2017-07-01DOI: 10.1017/S2040470017000590
Galibjon M. Sharipov, D. Paraforos, H. Griepentrog
One of the significant obstacles in achieving a reliable seed germination and even plant field emergence in no-till seeding is a variation in the desired seeding depth. This is caused by the inappropriate response of the seeder motion dynamics to harsh soil conditions and to high operating speed. In order to assess the dynamic response of a no-till seeder, a mathematical model, which simulated the vertical motion of a seeding aggregate, was developed. A correlation between the simulated and the measured parameters resulted in a root-mean-squared (RMS) error of 17.2% and 6.4% for impact force and pitch angle, respectively. The simulated impact force frequencies of interests were detected at the critical frequencies of the measured forces with high coherence values.
{"title":"Modelling and simulation of a no-till seeder vertical motion dynamics for precise seeding depth","authors":"Galibjon M. Sharipov, D. Paraforos, H. Griepentrog","doi":"10.1017/S2040470017000590","DOIUrl":"https://doi.org/10.1017/S2040470017000590","url":null,"abstract":"One of the significant obstacles in achieving a reliable seed germination and even plant field emergence in no-till seeding is a variation in the desired seeding depth. This is caused by the inappropriate response of the seeder motion dynamics to harsh soil conditions and to high operating speed. In order to assess the dynamic response of a no-till seeder, a mathematical model, which simulated the vertical motion of a seeding aggregate, was developed. A correlation between the simulated and the measured parameters resulted in a root-mean-squared (RMS) error of 17.2% and 6.4% for impact force and pitch angle, respectively. The simulated impact force frequencies of interests were detected at the critical frequencies of the measured forces with high coherence values.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"34 1","pages":"455-460"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76297073","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 : 2017-07-01DOI: 10.1017/S2040470017001054
P. Rydahl, N.-P. Jensen, M. Dyrmann, P. H. Nielsen, R. Jørgensen
In order to exploit potentials of 20–40% reduction of herbicide use, as documented by use of Decision Support Systems (DSS), where requirements for manual field inspection constitute a major obstacle, large numbers of digital pictures of weed infestations have been collected and analysed manually by crop advisors. Results were transferred to: 1) DSS, which determined needs for control and connected, optimized options for control returned options for control and 2) convolutional, neural networks, which in this way were trained to enable automatic analysis of future pictures, which support both field- and site-specific integrated weed management.
{"title":"RoboWeedSupport - Presentation of a cloud based system bridging the gap between in-field weed inspections and decision support systems","authors":"P. Rydahl, N.-P. Jensen, M. Dyrmann, P. H. Nielsen, R. Jørgensen","doi":"10.1017/S2040470017001054","DOIUrl":"https://doi.org/10.1017/S2040470017001054","url":null,"abstract":"In order to exploit potentials of 20–40% reduction of herbicide use, as documented by use of Decision Support Systems (DSS), where requirements for manual field inspection constitute a major obstacle, large numbers of digital pictures of weed infestations have been collected and analysed manually by crop advisors. Results were transferred to: 1) DSS, which determined needs for control and connected, optimized options for control returned options for control and 2) convolutional, neural networks, which in this way were trained to enable automatic analysis of future pictures, which support both field- and site-specific integrated weed management.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"71 1","pages":"860-864"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80655020","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 : 2017-07-01DOI: 10.1017/S2040470017000954
A. Robson, M. Rahman, Jasmine Muir, A. Saint, C. Simpson, C. Searle
This paper evaluates the potential of very high resolution multispectral (Worldview-3) satellite imagery for mapping yield parameters in avocado and macadamia orchards. An evaluation of 18 structural and pigment based vegetation indices (VIs) derived from Worldview-3 imagery identified a positive relationship to nut/ fruit weight (kg/tree) R 2 >0.69 for macadamia and R 2 >0.68 for avocado; and nut/ fruit number (per tree) R 2 >0.6 for macadamia and R 2 >0.61 for avocado. Using the algorithms derived between the optimal VI and the measured parameter, yield and nut/ fruit number maps were derived for each block. In the absence of a commercial yield monitor, the resulting yield maps offer significant benefit to growers for improving orchard management, harvest scheduling, and forward selling decisions.
{"title":"Evaluating satellite remote sensing as a method for measuring yield variability in Avocado and Macadamia tree crops","authors":"A. Robson, M. Rahman, Jasmine Muir, A. Saint, C. Simpson, C. Searle","doi":"10.1017/S2040470017000954","DOIUrl":"https://doi.org/10.1017/S2040470017000954","url":null,"abstract":"This paper evaluates the potential of very high resolution multispectral (Worldview-3) satellite imagery for mapping yield parameters in avocado and macadamia orchards. An evaluation of 18 structural and pigment based vegetation indices (VIs) derived from Worldview-3 imagery identified a positive relationship to nut/ fruit weight (kg/tree) R 2 >0.69 for macadamia and R 2 >0.68 for avocado; and nut/ fruit number (per tree) R 2 >0.6 for macadamia and R 2 >0.61 for avocado. Using the algorithms derived between the optimal VI and the measured parameter, yield and nut/ fruit number maps were derived for each block. In the absence of a commercial yield monitor, the resulting yield maps offer significant benefit to growers for improving orchard management, harvest scheduling, and forward selling decisions.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"2 1","pages":"498-504"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80896871","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 : 2017-07-01DOI: 10.1017/S2040470017000619
J. Geipel, A. Korsaeth
{"title":"Hyperspectral Aerial Imaging for Grassland Yield Estimation","authors":"J. Geipel, A. Korsaeth","doi":"10.1017/S2040470017000619","DOIUrl":"https://doi.org/10.1017/S2040470017000619","url":null,"abstract":"","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"4 1","pages":"770-775"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89930146","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 : 2017-07-01DOI: 10.1017/S2040470017000450
I. Hajdu, I. Yule
{"title":"Application of a Wireless Sensor Network for Multi-Depth Soil Moisture Monitoring at Farm Scale in New Zealand’s Hill Country","authors":"I. Hajdu, I. Yule","doi":"10.1017/S2040470017000450","DOIUrl":"https://doi.org/10.1017/S2040470017000450","url":null,"abstract":"","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"21 1","pages":"412-417"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89961656","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 : 2017-07-01DOI: 10.1017/S2040470017000668
S. Higgins, J. Schellberg, J. Bailey
{"title":"A review of Precision Agriculture as an aid to Nutrient Management in Intensive Grassland Areas in North West Europe","authors":"S. Higgins, J. Schellberg, J. Bailey","doi":"10.1017/S2040470017000668","DOIUrl":"https://doi.org/10.1017/S2040470017000668","url":null,"abstract":"","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"24 1","pages":"782-786"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82487719","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 : 2017-07-01DOI: 10.1017/S2040470017000929
A. Matese, S. F. D. Gennaro, C. Miranda, A. Berton, L. G. Santesteban
New remote sensing technologies have provided unprecedented results in vineyard monitoring. The aim of this work was to evaluate different sources of images and processing methodologies to describe spatial variability of spectral-based and canopy-based vegetation indices within a vineyard, and their relationship with productive and qualitative vine parameters. Comparison between image-derived indices from Sentinel 2 NDVI, unfiltered and filtered UAV NDVI and with agronomic features have been performed. UAV images allow calculating new non-spectral indices based on canopy architecture that provide additional and useful information to the growers with regards to within-vineyard management zone delineation.
{"title":"Evaluation of spectral-based and canopy-based vegetation indices from UAV and Sentinel 2 images to assess spatial variability and ground vine parameters","authors":"A. Matese, S. F. D. Gennaro, C. Miranda, A. Berton, L. G. Santesteban","doi":"10.1017/S2040470017000929","DOIUrl":"https://doi.org/10.1017/S2040470017000929","url":null,"abstract":"New remote sensing technologies have provided unprecedented results in vineyard monitoring. The aim of this work was to evaluate different sources of images and processing methodologies to describe spatial variability of spectral-based and canopy-based vegetation indices within a vineyard, and their relationship with productive and qualitative vine parameters. Comparison between image-derived indices from Sentinel 2 NDVI, unfiltered and filtered UAV NDVI and with agronomic features have been performed. UAV images allow calculating new non-spectral indices based on canopy architecture that provide additional and useful information to the growers with regards to within-vineyard management zone delineation.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"373 1","pages":"817-822"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84816235","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 : 2017-07-01DOI: 10.1017/S2040470017000486
F. Navarro, B. Ingram, R. Kerry, B. Ortiz, B. Scully
Aflatoxin is a fungal toxin contaminating corn and causing liver cancer in humans and animals. Contamination is driven by high temperatures and drought. Aflatoxin assessment is expensive so extension services need to identify high risk areas so irrigation, planting strategies and corn varieties can be adapted. This research presents a web-based decision support tool for risk illustrated with a case study from southern Georgia. The tool employs the approach, developed by Kerry et al. (2017b) where exceedance of key thresholds in temperatures, rainfall, soil type and corn production are used to determine risk. The tool also includes NDVI to indicate drought stress and could be further expanded to include new risk factors and adapted to other crops.
{"title":"A Web-based GIS Decision Support Tool for Determining Corn Aflatoxin Risk: A Case Study Data from Southern Georgia, USA","authors":"F. Navarro, B. Ingram, R. Kerry, B. Ortiz, B. Scully","doi":"10.1017/S2040470017000486","DOIUrl":"https://doi.org/10.1017/S2040470017000486","url":null,"abstract":"Aflatoxin is a fungal toxin contaminating corn and causing liver cancer in humans and animals. Contamination is driven by high temperatures and drought. Aflatoxin assessment is expensive so extension services need to identify high risk areas so irrigation, planting strategies and corn varieties can be adapted. This research presents a web-based decision support tool for risk illustrated with a case study from southern Georgia. The tool employs the approach, developed by Kerry et al. (2017b) where exceedance of key thresholds in temperatures, rainfall, soil type and corn production are used to determine risk. The tool also includes NDVI to indicate drought stress and could be further expanded to include new risk factors and adapted to other crops.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"3 1","pages":"718-723"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81562527","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 : 2017-07-01DOI: 10.1017/S204047001700108X
S. Gutiérrez, M. Diago, J. Fernández-Novales, J. Tardáguila
The goal of this work was the assessment of commercial vineyard water status using on-the-go thermal imaging. On-the-go thermal imaging acquisition was conducted with a thermal camera operating at 1.20m distance from the canopy, mounted on a quad moving at 5 km/h. Canopy temperature, cross water stress index (CWSI) and stomatal conductance index (Ig) were strongly and significantly correlated to stem water potential (Ψstem) in east and west side of the canopy. For CWSI, the values of the coefficient of determination (R ) were 0.88*** and 0.73*** for east and west sides, respectively. As regards the index Ig, its relationships with Ψstem showed R = 0.89*** and R= 0.77*** for east and west sides, respectively. These results are promising and evidence the potential of on-the-go thermal imaging to become a new tool to evaluate the vineyard water status.
{"title":"On-the-go thermal imaging for water status assessment in commercial vineyards","authors":"S. Gutiérrez, M. Diago, J. Fernández-Novales, J. Tardáguila","doi":"10.1017/S204047001700108X","DOIUrl":"https://doi.org/10.1017/S204047001700108X","url":null,"abstract":"The goal of this work was the assessment of commercial vineyard water status using on-the-go thermal imaging. On-the-go thermal imaging acquisition was conducted with a thermal camera operating at 1.20m distance from the canopy, mounted on a quad moving at 5 km/h. Canopy temperature, cross water stress index (CWSI) and stomatal conductance index (Ig) were strongly and significantly correlated to stem water potential (Ψstem) in east and west side of the canopy. For CWSI, the values of the coefficient of determination (R ) were 0.88*** and 0.73*** for east and west sides, respectively. As regards the index Ig, its relationships with Ψstem showed R = 0.89*** and R= 0.77*** for east and west sides, respectively. These results are promising and evidence the potential of on-the-go thermal imaging to become a new tool to evaluate the vineyard water status.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"31 1","pages":"520-524"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84094905","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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