Proceedings
Authors
| Filter results5 paper(s) found. |
|---|
1. Spatial Variability Of Crop And Soil Properties In A Crop-livestock Integrated SystemThe knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the site specific application of lime and fertilizer. The objective of this work was to map and evaluate the spatial variability of the crop, soil chemical and physical properties. The study was conducted in 2 areas of 6.9 and 11.7 ha of a Typic Haplustox in Sao Carlos, SP, Brazil. The summer crops corn and sorghum were sowed together to the forage crop Brachiaria brizantha in the system of crop-pasture... A.C. Bernardi, C.R. Grego, R.G. Andrade, C.M. Vaz, L.M. Rabello, R.Y. Inamasu |
2. Spatial Variability of Soil Properties in Intensively Managed Tropical Grassland in BrazilFor the intensification of tropical grass pastures systems the soil fertility building up by liming and balanced fertilization is necessary. The knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the variable rate application of lime and fertilizers. PA requires methods to indicate the spatial variability of soil and plant parameters. The objective of this work was to map and evaluate the soil properties and maps the site specific liming and fertilizer... G.M. Bettiol, R.Y. Inamasu, L.M. Rabello, A.C. Bernardi, M. Campana, P.P. Oliveira |
3. Evaluation of an Ear Tag Based Accelerometer for Monitoring Rumination Time, Chewing Cycles and Rumination Bouts in Dairy CowsThe objective of this study was to evaluate the ear tag based accelerometer SMARTBOW (Smartbow, Weibern, Austria) for detecting rumination time, chewing cycles and rumination bouts in dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings was tested. Ten Simmental cows... M. Iwersen, S. Reiter, V. Schweinzer, F. Kickinger, M. Öhlschuster, L. Lidauer, W. Auer, M. Drillich, A. Berger |
4. Real-Time Fruit Detection Using Deep Neural NetworksProximal imaging using tractor-mounted cameras is a simple and cost-effective method to acquire large quantities of data in orchards and vineyards. It can be used for the monitoring of vegetation and for the management of field operations such as the guidance of smart spraying systems for instance. One of the most prolific research subjects in arboriculture is fruit detection during the growing season. Estimations of fruit-load can be used for early yield assessments and for the monitoring of... B. Keresztes, J. Da costa, D. Randriamanga, C. Germain, F. Abdelghafour |
5. Supporting and Analysing On-Farm Nitrogen Tramline Trials So Farmers, Industry, Agronomists and Scientists Can LearN TogetherNitrogen fertilizer decisions are considered important for the agronomic, economic and environmental performance of cereal crop production. Despite good recommendation systems large unpredicted variation exists in measured N requirements. There may be fields and farms that are consistently receiving too much or too little N fertilizer, therefore losing substantial profit from wasted fertilizer or lost yield. Precision farming technologies can enable farmers (& researchers) to test appropriate... D. Kindred, R. Sylvester-bradley, S. Clarke, S. Roques, D. Hatley, B. Marchant |