Proceedings
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| Filter results7 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. Multi-objective Optimization Analysis Model for County Range Soil Nutrients Sampling Point Layout Based on Improved Genetic AlgorithmThe layout of soil nutrients sampling points directly influence on the representative of soil samples and the precision of fertilization, also on sampling efficiency and sampling costs. By analyzing the various factors of county range farmland soil nutrients sampling, and setting the boundary conditions and objective function, the paper established multi-objective optimization... C. Tian'en |
3. Detection Of Fruit In Canopy Night-Time Images: Two Case Studies With Apple And MangoReliable estimation of the expected yield remains a major challenge in orchards. In a recent work we reported the development of an algorithm for estimating the number of fruits in images of apple trees acquired in natural daylight conditions. In the present work we tested this approach with night-time images of similar apple trees and further adapted this approach to night-time images of mango trees. Working with the apple images required only... R. Linker, A. Payne, K. Walsh, O. Cohen |
4. NIRS Sensor Controlled Total-Mixed-Ration For Nutrient Optimized Feeding Of Dairy CattleThe exact regulation of dry matter, energy and ingredients in fodder rations provides a large advantage in order to optimize an economical animal nutrition. Feed mixer wagons are used to feed Gras and Maize silage together with other components. It can be used in combination with a transponder system for feed concentrate as well as for feeding of a total mixed ration. The online measurement system based on NIR-spectrometric sensors to measure DM-content and other nutrients should... P. Büscher, P. Twickler, D. Marquering, M. Müller, D. Maack |
5. Recognition And Classification Of Weeds In Sugarcane Using The Technique Of The Bag Of WordsThe production of sugar and ethanol in Brazil is very prominent economically and the reducing costs and improving the production system being necessary. The management crops operations of sugarcane and the control of weed is one of the processes that cause the greatest increase in production costs; because the competition that exists between cane plants and weed, for water, nutrients and sunlight is big, contribute to the loss of up to 20% of the useful cane. The use of image processing techniques... W.E. Santiago, A.R. Barreto, D.G. Figueredo, R.C. Tinini, B.T. Mederos, N.J. Leite |
6. Hay Yield Estimation Using UAV-based Imagery and a Convolutional Neural NetworkYield monitoring systems are widely used commercially in grain crops to map yields at a scale of a few meters. However, such high-resolution yield monitoring and mapping for hay and forage crops has not been commercialized. Most commercial hay yield monitoring systems only obtain the weight of individual bales, making it difficult to map and understand the spatial variability in hay yield. This study investigated the feasibility of an unmanned aerial vehicle (UAV)-based remote sensing system for... K. Lee, K.A. Sudduth, J. Zhou |
7. 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 |