Proceedings
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| Filter results5 paper(s) found. |
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1. Canopy Reflectance-based Nitrogen Management Strategies For Subsurface Drip Irrigated CottonNitrogen (N) fertilizer management in subsurface drip irrigation (SDI) systems for cotton (Gossypium hirsutum L.) can be very efficient when N is fertigated on a near daily time step. Determining the amounts and timing of the N fertigation, however are questions that weekly canopy reflectance measurements may answer. The main objective of this 3-yr. study was to test two canopy reflectance strategies for adjusting urea ammonium nitrate (UAN) fertilizer in-season injections... K. Bronson |
2. Detection Of Nitrogen Deficiency In Potatoes Using Small Unmanned Aircraft SystemsSmall Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. A nitrogen rate experiment was established in 2013 with ‘Ranger Russet’ potatoes by applying four rates of nitrogen fertilizer (112, 224, 337, and 449 kg N/ha) in a randomized block design with 3 replicates. A Tetracam Hawkeye sUAS and Agricultural Digital Camera Lite sensor were used to collect imagery with near-infrared... D.A. Horneck, D.J. Gadler, A.E. Bruce, R.W. Turner, C.B. Spinelli, J.J. Brungardt, P.B. Hamm, E. Hunt |
3. Precision Nutrient Management Through Use Of LCC And Nutrient Expert In Hybrid Maize Under Laterite Soil Of IndiaNutrient management has played a crucial role in achieving self sufficiency in food grain production. Energy crisis resulted in high price index of chemical fertilizers. Coupled with their limited production, fertilizer cost, soil health, sustainability and pollution have gave rise to interest in precision nutrient management tools. Field experiment was conducted to study the effect of variety and nutrient management on the growth and productivity of maize under lateritic belt of West Bengal... M. Banerjee, S. Dutta, G. Bhuiya, G. Malik, D. Maiti |
4. Deep Learning to Estimate Sorghum Yield with Uncrewed Aerial System ImageryIn the face of growing demand for food, feed, and fuel, plant breeders are challenged to accelerate yield potential through quick and efficient cultivar development. Plant breeders often conduct large-scale trials in multiple locations and years to address these goals. Sorghum breeding, integral to these efforts, requires early, accurate, and scalable harvestable yield predictions, traditionally possible only after harvest, which is time-consuming and laborious. This research harnesses high-throughput... M.A. Bari, A. Bakshi, T. Witt, D. Caragea, K. Jagadish, T. Felderhoff |
5. Proximal, Drone, and Satellite Sensors for In-season Variable Nitrogen Rate Application in Corn: a Comparative Study of Fixed-rate and Sensor-based ApproachesEffective nitrogen (N) management is essential for optimizing corn yield and enhancing agricultural sustainability. Traditional N application methods, typically uniform split pre-plant and in-season applications, often neglect the spatial and temporal variability of N requirements across different fields and years, potentially leading to N overuse. With the rise of precision agriculture technologies, it is crucial to reassess these conventional practices. This study had two main objectives: first,... A. Jakhar, A. Bhattarai, L. Bastos, G. Scarpin |