Proceedings
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| Filter results6 paper(s) found. |
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1. On-Farm Trials Using Precision Ag in Northeast LouisianaThe availability of yield monitors and precision application equipment on producers’ farms have made it much easier for researchers to take the results from experiment station trials and apply them to producers’ fields. Treatments/methods are applied in strips, by prescription, embedded plots or in combination. Fields are divided into zones for analyzing the harvest yield data. These can include soil type, soil Ec, or other criteria. Treatments are analyzed... D. Burns, D. Overstreet, D. Kruse, R. Frazier, D. Blanche |
2. A Method For Sampling Scab Spots On Apple Leaves In The Orchard Using Machine VisionIntroduction One of the largest threats in apple orchards is scab. Current procedures involve models based on weather data that predict the likelihood of scab attacks. In case of alarm the orchard is sprayed with preventive pesticides and this typically happens 25-30 times per season. The scab attacks the leaves and stays on fallen leaves that reinfect the trees with rainwater, making it an advantage to include a-priori knowledge on previous... M.G. Bertelsen, K. Nielsen, M.R. Nielsen |
3. 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 |
4. 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 |
5. 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 |
6. Advancements in Agrivoltaics: Autonomous Robotic Mowing for Enhanced Management in Solar FarmsAgrivoltaics – the co-location of solar energy installations and agriculture beneath or between rows of photovoltaic panels – has gained prominence as a sustainable and efficient approach to land use. The US has over 2.8 GW in Agrivoltaics, integrating crop cultivation with solar energy. However, effective vegetation management is critical for solar panel efficiency. Flat, sunny agricultural land accommodates solar panels and crops efficiently. The challenge lies in managing grass... S. Behera, S. Pitla |