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| Filter results7 paper(s) found. |
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1. Maturity Grape Indicators Obtained By Means Of Earth Observation TechniquesWine producers often need to buy grapes from growers. A good selection of grapes allows obtaining the desired wine quality. This paper presents a procedure to obtain by means of earth observation techniques indices and parameters used in the Spanish vineyards to monitor the state of the grapes. In this way is possible to monitor the ripeness of the grapes or the best time to harvest in such a way that growers can get the highest quality grapes, while producers of wine can select the most appropriate... J. Sanz, A. Romo, J.L. Casanova, S. Fraile |
2. OptiThin - Precision Fruiticulture by Tree-Specific Mechanical ThinningApple cultivars show biennial fluctuations in yields (alternate bearing). The phenomenon is induced by reduced yields in one year due to freeze damage, low pollination rate or other reasons. Consequently, trees develop many flower buds that blossom in the following year. The many flowers lead to a high number of small fruits that won’t be accepted on the market. Endogenous factors (phytohormones and carbohydrate allocation) subsequently establish the biennial cycle. The alternate bearing... A. Betz, H. Benny, M. Jens, M. Özyurtlu, M. Pflanz, T. Rachow-autrum, A. Schischmanow, M. Scheele, J. Schrenk, L. Schrenk, M. Zude, R. Gebbers |
3. Using Precision Agriculture And Remote Sensing Techniques To Improve Genotype Selection In A Breeding ProgramPrecision Agriculture (PA) and Remote Sensing (RS) technologies are increasingly being used as tools to assess crop and soil properties by breeders and physiologists. These technologies are showing potential to improve genotype selections over their traditional field measurements, by providing quick access to crop properties throughout the crop cycle and yield estimation. The objective of this work was to use vegetation indices (VIs) and soil apparent electrical conductivity... F.A. Rodrigues junior, I. Ortiz-monasterio, P.J. Zarco-tejada, K. Ammar, B.G. Gérard |
4. High Resolution Hyperspectral Imagery to Assess Wheat Grain Protein in a Farmer's FieldThe agricultural research sector is working to develop new technologies and management knowledge to sustainably increase food productivity, to ensure global food security and decrease poverty. Wheat is one of the most important crops into this scenario, being among the three most important cereal commodities produced worldwide. Precision Agriculture (PA) and specially Remote Sensing (RS) technologies have become in the recent years more affordable which has improved the availability and flexibility... F.A. Rodrigues jr., I. Ortiz-monasterio, P.J. Zarco-tejada, F.H. Toledo, U. Schulthess, B. Gérard |
5. Use of Precision Technologies to Conduct Successful Within-field, On-farm TrialsPerforming randomized replicated trials in row crop field environments has the potential to increase crop production in environmentally sustainable ways. Successful implementation requires an understanding of implement capabilities and sources of potential systematic error, including operator error. Equipment capabilities can be thought of as a series of several critical “links in a chain,” each with implications that propagate downstream. We will... M. Stelford, A. Krmenec |
6. Variable Rate Nitrogen Approach in a Potato-wheat-wheat Cropping SystemNitrogen application in agriculture is a vital process for optimal plant growth and yield outcomes. Different factors such as topography, soil properties, historical yield, and crop stress affect nitrogen (N) needs within a field. Applying variable N within a field could improve precision agriculture. Optimal N management is a system that involves applying a conservative variable base rate at or shortly after planting followed by in-season assessment and, if needed, variable rate application—with... E.A. Flint, M. Yost, B.G. Hopkins |
7. Spectral Imaging Deep Learning Mapper for Precision AgricultureWith the growing variety of RGB cameras, spectral sensors, and platforms like field robots or unmanned aerial vehicles (UAV) in precision agriculture, there is a demand for straightforward utilization of collected field data. In recent years, deep learning has gained significant attention and delivered impressive results in the realm of computer vision tasks, such as semantic segmentation. These models have also found extensive applications in research related to precision agriculture and spectral... L. Thomas, B. Jakimow, A. Janz, P. Hostert, A. Lajunen |