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| Filter results17 paper(s) found. |
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1. Assessment Of Field Crops Leaf Area Index By The Red-edge Inflection Point Derived From Venus BandsThe red-edge region of leaves spectrum (700-800 nm) corresponds to the spectral region that connects the chlorophyll absorption in the red and the amplified reflectance caused by the leaf structure in the near infrared (NIR) parts of the spectrum. At the canopy level, the inflection point of the red-edge slope is influenced by the plant’s condition that is related to several properties, including Leaf Area Index (LAI) and plant nutritional status.... I. Herrmann, A. Pimstein, A. Karnieli, Y. Cohen, V. Alchanatis , D.J. Bonfil |
2. Hyperspectral Imagery for the Detection of Nitrogen Stress in Potato for In-season Management... T.J. Nigon, C. Rosen, D. Mulla, Y. Cohen, V. Alchanatis, R. Rud |
3. Evaluating Water Status in Potato Fields Using Combined Information from RGB and Thermal Aerial ImagesPotato yield and quality are highly dependent on an adequate supply of water. In this study the combined information from RGB and thermal aerial images to evaluate... Y. Cohen, V. Alchanatis, B. Heuer, H. Lemcoff, M. Sprintsin, C. Rosen, D. Mulla, T. Nigon, Z. Dar, A. Cohen, A. Levi, R. Brikman, T. Markovits, R. Rud |
4. A Method for Combining Spatial and Hyperspectral Information for Delineation of Homogenous Management ZonesHyperspectral (HS) remote sensing is a constantly developing field. New remote sensing applications of different fields constantly appear. The possibility of acquisition information about an object without physical contact is spanning new opportunities in many fields and for precision agricultural in particular. These opportunities demand constant improvement and development of new analysis approaches and algorithms,... Y. Cohen, V. Alchanatis, O. Levi, S. Cohen |
5. Automatic Detection And Mapping Of Irrigation System Failures Using Remotely Sensed Canopy Temperature And Image ProcessingToday there is no systematic way to identify and locate failures of irrigation systems mainly because of the labor costs associated with locating the failures. The general aim of this study was to develop an airborne thermal imaging system for semi - automatic monitoring and mapping of irrigation system failures, specifically, of leaks and clogs. Initially, leaks and clogs were simulated by setting controlled trials in table grapes vineyards and olive groves. Airborne thermal... V. Alchanatis, Y. Cohen, M. Sprinstin, A. Cohen, I. Zipori, A. Dag, A. Naor |
6. Are Thermal Images Adequate For Irrigation Management?Thermal crop sensing technologies have potential as tools for monitoring and mapping crop water status, improving water use efficiency and precisely managing irrigation. As thermal sensors and imagers became more affordable, various platforms were examined to allow for canopy- and field-scale acquisitions of canopy temperature and to extract maps of water status variability. Various canopy temperature statistics and crop water stress index (CWSI) were used to estimate water status... O. Rosenberg, V. Alchanatis, Y. Saranga, A. Bosak, Y. Cohen |
7. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy SensorThe use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be detected... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches |
8. Translating Data into Knowledge - Precision Agriculture Database in a Sugarcane Production.The advent of Information Technology in agriculture, surveying and data collection became a simple task, starting the era of "Big Data" in agricultural production. Currently, a large volume of data and information associated with the plant, soil and climate are collected quick and easily. These factors influence productivity, operating costs, investments and environment impacts. However, a major challenge for this area is the transformation of data and information... G.M. Sanches, O.T. Kolln, H.C. Franco, P.S. Magalhaes, D.G. Duft |
9. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane FieldsOne important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-making... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco |
10. Crop Water Stress Mapping for Site Specific Irrigation by Thermal Imagery and Artificial Reference SurfacesVariable rate irrigation machines or solid set systems have become technically feasible; however, crop water status mapping is necessary as a blueprint to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide these maps in sufficient detail and at a timely delivery. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high- resolution thermal imagery and artificial reference... M. Meron, J. Tsipris, V. Orlov, V. Alchnatis, Y. Cohen |
11. Economic and Environmental Impacts in Sugarcane Production to Meet the Brazilian Ethanol Demands by 2030: The Role of Precision AgricultureThe agreement signed at COP-21 reaffirms the vital compromise of Brazil with sugarcane and ethanol production. To meet the established targets, the ethanol production should be 54 billion liters in 2030. From the agronomic standpoint, two alternatives are possible; increase the planted area and/or agricultural yield. The present study aimed to evaluate the economic and environmental impacts in sugarcane production meeting the established targets in São Paulo state. In this context, were... G.M. Sanches, T.F. Cardoso, M.F. Chagas, A.C. Luciano, D.G. Duft, P.S. Magalhães, H.C. Franco, A. Bonomi |
12. Potential of Apparent Soil Electrical Conductivity to Describe Soil Spatial Variability in Brazilian Sugarcane FieldsThe soil apparent electrical conductivity (ECa) has been highlighted in the literature as a tool with high potential to map the soil fertility of fields. However, sugarcane fields still lack results that show the applicability of this information to define the soil spatial variability and its fertility conditions. The objective of the present paper was to provide a comprehensive assessment of the relationship between ECa, evaluated by electromagnetic induction (EMI) sensor, and the spatial variability... G.M. Sanches, P.S. Magalhães, H.C. Franco, A.Z. Remacre |
13. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape AttributesOne of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity in... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes |
14. Soil and Crop Factors to Site-specific Nitrogen Management on Sugarcane FieldsNitrogen (N) is one of the most widely used fertilizers in crops and the most harmful to the environment. The increase fertilizers consumption, mainly N sources (one of the most widely fertilizer used in sugarcane fields), is one of the main factors underlying the sustainability of the entire production process. Currently, N recommendations in sugarcane are based only on the expected yield. However, there is little agronomic support for nitrogen (N) recommendations based on expected yield, despite... G.M. Sanches, R. Otto, F.R. Pereira |
15. The Use of Spatial and Temporal Measures to Enhance the Sensitivity of Satellite-based Spectral Vegetation Indices to (Water) Stress in Maize FieldsClimate change and water scarcity are reducing the available irrigation water for agriculture thus turning it into a limited resource. Today calculating and estimating crop water requirements are achieved through the ETc FAO-56 model where the effect of climate on crop water requirement is determined through the water evaporation from the soil and plant (ETref), and a calendar crop coefficient (Kc). Models that... Y. Goldwasser, V. Alchanati, E. Goldshtein, Y. Cohen, A. Gips, I. Nadav |
16. Comparison of Canopy Extraction Methods from UAV Thermal Images for Temperature Mapping: a Case Study from a Peach OrchardCanopy extraction using thermal images significantly affects temperature mapping and crop water status estimation. This study aimed to compare several canopy extraction methodologies by utilizing a large database of UAV thermal images from a precision irrigation trial in a peach orchard. Canopy extraction using thermal images can be attained by purely statistical analysis (S), a combination of statistical and spatial analyses (SS), or by synchronizing thermal and RGB images, following RGB statistical... L. Katz, A. Ben-gal, I. Litaor, A. Naor, A. Peeters, E. Goldshtein, V. Alchanatis, Y. Cohen |
17. Data-driven Agriculture and Sustainable Farming: Friends or Foes?Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies... O. Rozenstein, Y. Cohen, V. Alchanatis , K. Behrendt, D.J. Bonfil, G. Eshel, A. Harari, W.E. Harris, I. Klapp, Y. Laor, R. Linker, T. Paz-kagan, S. Peets, M.S. Rutter, Y. Salzer, J. Lowenberg-deboer |