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1. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea CropThe software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc |
2. Precision Agriculture Education Program In NebraskaWith the cost of agricultural inputs and the instability of commodity prices increasing, demand is growing for training in the essential skills needed to successfully implement site-specific crop management. This set of skills is uniquely interdisciplinary in nature. Thus, it is essential for potential users of precision agriculture to understand the basics of geodetic and electronic control equipment, principles of geographic information systems, fundamentals... V.I. Adamchuk, R.B. Ferguson |
3. A Model For Wheat Yield Prediction Based On Real-time Monitoring Of Environmental Factors... B. Dumont, F. Vancutsem, J. Destain, B. Bodson, F. Lebeau, M. Destain |
4. Comparison Of Spectral Indices Derived From Active Crop Canopy Sensors For Assessing Nitrogen And Water Status... L. Shiratsuchi, R.B. Ferguson, J.F. Shanahan, V.I. Adamchuk, G. Slater |
5. Management Of Remote Imagery For Precision AgricultureSatellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack |
6. Apparent Electrical Conductivity Calibration In Semiarid Soils: Ion-pair CorrectionThe electromagnetic induction sensor (EM38DD) is a field proven portable sensor for rapid measurement of the apparent electrical conductivity (ECa) of soils. Calibration with the electrical conductivity of saturation paste extracts is the most widely used method to correlate ECa with the effective electrical conductivity (ECe). A drawback of this method is the formation of ion pairs in the high ionic strength saturated paste extracts, which effectively decreases the measured ECe, leading to the... X. Amakor, A.R. Jacobson, G.E. Cardon, A. Hawks, W. Barnes |
7. Research On Nutrition Detection Technology Of Soil And Leaf Of Citrus Based On Spectroscopic TechniquesThe diagnosis technique of real-time lossless crop nutrition is the foundation and conditions for the precise and effective fertilization. Currently, the diagnosis of crop nutrition mainly relies on the routine chemical analysis of laboratory. Due to the complicated procedure, time-consuming, high cost and high professional technique requirement, it can hardly meet the need of precise variable fertilization technology. Spectrum technology is the technology of real-time and non-destructive testing,... S. Yi, L. Deng |
8. Assessing the Potential of an Algorithm Based On Mean Climatic Data to Predict Wheat YieldIn crop yield prediction, the unobserved future weather remains the key point of predictions. Since weather forecasts are limited in time, a large amount of information may come from the analysis of past weather data. Mean data over the past years and stochastically generated data are two possible ways to compensate the lack of future data. This research aims to demonstrate that it is possible to predict... F. Vancutsem, V. Leemans, S. Ferrandis vallterra, B. Bodson, J. Destain, M. Destain, B. Dumont |
9. Integrated Crop Canopy Sensing System for Spatial Analysis of In-Season Crop PerformanceOver the past decade, the relationships between leaf color, chlorophyll content, nitrogen supply, biomass and grain yield of agronomic crops have been studied widely.... L. Shiratsuchi, C.C. Lutz, R.B. Ferguson, V.I. Adamchuk |
10. An Approach to Selection of Soil Water Content Monitoring Locations within FieldsIncreased input efficiency is one of the main challenges for a modern agricultural enterprise. One way to optimize production cycles is to rationalize crop residue utilization. In conditions where there is limited use of mineral fertilizers and without applying manure, plant residues may be used as an organic fertilizer as... V.I. Adamchuk, L. Pan, R.B. Ferguson |
11. Landscape Influences on Soil Nitrogen Supply and Water Holding Capacity for Irrigated Corn... T. Shaver, M. Schmer, S. Irmak, S. Van donk, B. Wienhold, V. Jin, A. Bereuter, D. Francis, D. Rudnick, N. Ward, L. Hendrickson, R. Ferguson, V.I. Adamchuk |
12. Development And Evaluation Of A Leaf Monitoring System For Continuous Measurement Of Plant Water Status In Almond And Walnut CropsAbstract: Leaf temperature measurements using handheld infrared thermometers have been used to predict plant water stress by calculating crop water stress index (CWSI). However, for CWSI calculations it is recommended to measure canopy temperature of trees under saturated, stressed and current conditions simultaneously, which is not very practical while using handheld units. An inexpensive, easy to use sensing system was developed to predict plant water status for tree crops by measuring... F. Rojo, J. Roach, R. Coates, S. Upadhyaya, M. Delwiche, C. Han, R. Dhillon |
13. An Evaluation Of HJ-CCD Broadband Vegtation Indices For Leaf Chlorophyll Content EstimationLeaf chlorophyll content is one of the most important biochemical variables for crop physiological status assessment, crop biomass estimation and crop yield prediction in precision agriculture. Vegetation indices were considered effective for chlorophyll content estimation. Although hyperspectral reflectance is proven to be better than multispectral reflectance for leaf chlorophyll content retrieval, the scarcity of available data from satellite hyperspectral... T. Dong, J. Shang, J. Meng, J. Liu |
14. The TOAS Project: UAV Technology For Optimizing Herbicide Applications In Weed-Crop SystemsSite-specific weed management refers to the application of customised control treatments, mainly herbicide, only where weeds are located within the crop-field. In this context, the TOAS project is being developed under the financial support of the European Commission with the main objective of generating georeferenced weed infestation maps of certain herbaceous (corn and sunflower) and permanent woody crops (poplar and olive orchards) by using aerial images collected by an unmanned aerial... J.M. Peña, J. Torres-sanchez, A.I. De castro, J. Dorado, F. Lopez-granados |
15. Nitrogen Fertilisation Recommendations : Could They Be Improved Using Stochastically Generated Climates In Conjunction With Crop Models ?In the context of precision nitrogen (N) management, to ensure that the yield potential could be reached each year, farmers have too often applied quantities of fertilizers much larger than what was strictly required. However, since 2002, the Belgian Government transposed the European Nitrate Directive 91/676/EEC in the Belgian law, with the aim to maintain the productivity and the revenue of Belgian's farmers while reducing the environmental impact of excessive N management... B. Basso, J. Destain, B. Bodson, M. Destain, B. Dumont |
16. In-Season Nitrogen Requirement For Maize Using Model And Sensor-Based Recommendation ApproachesNitrogen (N), an essential element, is often limiting to plant growth. There is great value in determining the optimum quantity and timing of N application to meet crop needs while minimizing losses. Low nitrogen use efficiency (NUE) has been attributed to several factors including poor synchrony between N fertilizer and crop demand, unaccounted for spatial variability resulting in varying crop N needs, and temporal variances in crop N needs. Applying a portion... L.J. Stevens, R.B. Ferguson, D.W. Franzen, N.R. Kitchen |
17. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut TreesA knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightbar... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo |
18. Monitoring Ratio Of Leaf Carbon To Nitrogen In Winter Wheat Based On Hyperspectral MeasurementsThe metabolic status of carbon (C) and nitrogen (N) as two essential elements of crop plants has significant influence on the ultimate formation of yield and quality in crop production. Leaf is the major organ of plant photosynthesis and physiological activity, and in leaf tissues the ratio of carbon to nitrogen (C/N), defined as the ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), can... X. Xu |
19. Research On Measurement Device For NO3- Ion Concentration Of Nutrient SolutionThe management of water and ion concentration in nutrient solution is crucial in precision agriculture. Poor management may leads to the increasing of energy consumption and cost as well as low efficiency. The measurement of ion concentration in nutrient solution is prerequisite for optimal control and management of nutrient solution. Real-time detection of NO3-, as an important component of nitrogenous fertilizer, is always a big problem over the world. The... X. Zhang, Y. Li, K. Xu, X. Sun |
20. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular IndiaGroundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi |
21. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine VisionHand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten |
22. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather InformationCorn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
23. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor AlgorithmNitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
24. Active and Passive Crop Canopy Sensors As Tools for Nitrogen Management in CornThe objectives of this research were to (i) assess the correlation between active and passive crop canopy sensors’ vegetation indices at different corn growth stages and (ii) assess sidedress variable rate nitrogen (N) recommendation accuracy of active and passive sensors compared to the agronomic optimum N rate (AONR). The experiment was conducted near Central City, Nebraska on a Novina sandy loam planted to corn on 15 April 2015. The experiment was a randomized complete-block design with... L. Bastos, R. Ferguson |
25. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case StudyWhile on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate controller... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson |
26. Active and Passive Sensor Comparison for Variable Rate Nitrogen Determination and Accuracy in Irrigated CornThe objectives of this research were to (i) compare active and passive crop canopy sensors’ sidedress variable rate nitrogen (VRN) derived from different vegetation indices (VI) and (ii) assess VRN recommendation accuracy of active and passive sensors as compared to the agronomic optimum N rate (AONR) in irrigated corn. This study is comprised of six site-years (SY), conducted in 2015, 2016 and 2017 on different soil types (silt loam, loam and sandy loam) and with a range of preplant-applied... L. Bastos, R.B. Ferguson |
27. The Impact of Precision Agriculture Technologies on Farm Profitability in KansasEven with more than a decade long adoption of the precision agriculture (PA) technologies in the United States, its impact on farm profitability is still not clear. This paper uses farm level data from Kansas Farm Management Association (KFMA) to conduct the ex-post evaluation of PA technologies on farm profitability in Kansas. The analysis of the data using propensity score matching method indicates that there is on an average $60,000 difference in net returns of the farm with at least one PA... S. Dhoubhadel, T.W. Griffin |
28. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US MidwestEffective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan |
29. Assessing the Potential of Sentinel-1 in Retrieving Mango Phenology and Investigating Its Relation to Weather in Southern GhanaThe rise in global production of horticultural tree crops over the past few decades is driving technology-based innovation and research to promote productivity and efficiency. Although mango production is on the rise, application of the remote sensing technology is generally limited and the available study on retrieving mango phenology stages specifically, was focused on the application of optical data. We therefore sought to answer the questions; (1) can key phenology stages of mango be retrieved... B.A. Torgbor, M.M. Rahman, A. Robson, J. Brinkhoff |
30. Retrieving Nitrogen Levels in Almond Trees Using Hyperspectral Data at Leaf and Canopy LevelAlmonds are a crucial specialty crop in California, dominating approximately 80 percent of the global almond supply. To enhance nitrogen usage efficiency, reduce groundwater contamination, and optimize resource allocation, ongoing research has been dedicated to improving nitrogen management practices in almond cultivation. This study specifically focused on the retrieval of nitrogen levels with uncertainty estimation at both the leaf and canopy levels of almond trees. Hyperspectral data was collected... M. Chakraborty, A. Pourreza |
31. Automated Sow Estrus Detection Using Machine Vision TechnologySuccessful artificial insemination for gilts and sows relies on accurate timing that is determined by estrus check. Estrus checks in current farms are manually conducted by skilled breeding technicians using the back pressure test (BPT) method that is labor-intensive and inefficient due to the large animal-to-staff ratio. This study aimed to develop a robotic imaging system powered by artificial intelligence technology to automatically detect estrus status for gilts and sows in a stall-housing... J. Zhou, Z. Xu, T.J. Safranski, C. Bromfield |
32. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in AlabamaHarvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis |