Proceedings
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| Filter results8 paper(s) found. |
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1. Use of Active Crop Canopy Reflectance Sensor for Nitrogen Sugarcane FertilizationResearches about the use of ground-based canopy reflectance sensors aiming the nitrogen management fertilization on variable-rate over the sugarcane crop have been conducted in São Paulo, Brazil since 2007. Sugarcane response to nitrogen is variable, making difficult the development of models to estimate its demands.... L.R. Amaral, G. Portz, H. Rosa, J. Molin |
2. 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 |
3. Factors Related To Adoption Of Precision Agriculture Technologies In Southern BrazilThe adoption of technologies which allow the increase of food production with improving quality in addition to reduce the foot prints in the environment is important for agribusiness development. Precision Agriculture (PA) stands out as an option to aid the achievement of these goals. Brazil plays an important role to supply agricultural products and to demand technologies. However, research has focused on technical and economic implementation of PA technologies. Therefore, more information... A.A. Anselmi, L.C. Federizzi , C. Bredemeier, J.P. Molin |
4. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural NetworkIn this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color Index... M.R. De souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros |
5. Dynamic Feeding Intake Monitoring in Growing-Finishing Pigs Reared Under Precision Feeding StrategiesPigs exposed to challenges with no prior experience change their daily feeding intake pattern. A method identifying deviations from normal feeding patterns could be used to develop a model framework to estimate individual nutrient requirements of challenged pigs fed with precision feeding systems. The objective of this study was to develop a tool for early identification of feed intake deviations in precision fed growing-finishing pigs. Feed intake measurements collected during 84 d in 126 growing–finishing... L. Hauschild, A.R. Kristensen, I. Andretta, C. Pomar, A. Remus |
6. Precision Feeding Can Significantly Reduce Lysine Intake and Nitrogen Excretion Without Compromising the Performance of Growing PigsThe impact of using a mathematical model estimating real-time daily lysine requirements in a sustainable precision feeding program for growing pigs was investigated in two performance trials. Three treatments were tested in the first trial (60 pigs of 41.2±0.5 kg): a three-phase feeding program (3P) obtained by blending fixed proportions of feeds A (high nutrient concentration) and B (low nutrient concentration); and two daily-phase feeding programs in which the blended proportions of feeds... C. Pomar, I. Andretta, J. Rivest, L. Hauschild, J. Pomar |
7. Environmental Impacts of Precision Feeding Programs Applied in Brazilian Pig ProductionThis study was undertaken to evaluate the effect that switching from conventional to precision feeding systems during the growing-finishing phase would have on the potential environmental impact of Brazilian pig production. Standard life-cycle assessment procedures were used, with a cradle-to-farm gate boundary. The inputs and outputs of each interface of the life cycle were organized in a model. Grain production was independently characterized in the Central-West and South regions of Brazil,... C. Pomar, I. Andretta, L. Hauschild, M. Kipper, P.S. Pires |
8. Field Phenotyping and an Example of Proximal Sensing of PhotosynthesisField phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning systems.... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska |