Proceedings
Authors
| Filter results9 paper(s) found. |
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1. Estimation of Rice Yield from MODIS Data in West Java, IndonesiaChiharu Hongo1*, Takaaki Furukawa1, Gunardi Sigit2, Masayasu Maki3, Koki Honma3,... C. Hongo, T. Furukawa, G. Sigit, M. Maki, K. Honma, K. Yoshida, K. Oki, H. Shirakawa |
2. Long Term Effects of Irrigation with Sewage Effluent on Some Soil PropertiesIn the arid and semiarid regions, the use of treated sewage water increases as an alternative for non-renewable resources in irrigation. The objective of this research is to identify the effect of irrigation with sewage effluent and well water for long... M.I. Alwabel, S.A. Alsheri, A.M. Alomran |
3. Remote Collection of Behavioral and Physiological Data to Detect Lame CowsAuthors of abstract: C. Kamphuis, J. Burke, J. Jago ... J. Jago, J. Burke, C. Kamphuis, B. Dela rue |
4. Two On-Farm Tests to Evaluate In-Line Sensors for Mastitis DetectionTo date, there is no independent and uniformly presented information available regarding detection performance of automated in-line mastitis detection systems. This lack of information makes it hard for farmers or... B. Dela rue, J. Jago, C. Kamphuis |
5. Field Evaluation of Automated Estrus Detection Systems - Meeting Farmers' ExpectationAutomated systems for oestrus detection are commonly marketed as a suitable, or in some cases, a higher performing alternative to visual observation. Farmers, particularly those with larger herds relying on less experienced staff, view the perceived benefits of automated systems as both economic and physical, with expectations of improved oestrus detection efficiency with lower labour input. There is little evidence-based information available on the field performance of these systems to... B.T. Dela rue, C. Kamphuis, J.G. Jago, C.R. Burke |
6. Climate Change And Sustainable Precision Crop Production With Regard To Maize (Zea Mays L.)Precision crop production research activities were started during the mid-‘90s at the Institute of Biosystems Engineering, Faculty of Agricultural and Food Sciences, University of West Hungary. On the basis of the experiences with DSSAT (Decision Support System for Agrotechnology Transfer) the impact of climate change on maize yield (three soil types) was investigated until 2100. DSSAT crop growth model is used worldwide. The coupled model intercomparison project... A.J. Kovács, A. Nyéki, G. Milics, M. Neményi |
7. Development of a Sensing Device for Detecting Defoliation in SoybeanEstimating defoliation by insects in an agricultural field, specifically soybean, is performed by manually removing multiple leaf samples, visually inspecting the leaves for feeding, and assigning a value representing a “best guess” at the level of leaf material missing. These estimates can require considerable time and are subjective. The goal of this study was to design a low-cost system containing light sensors and a microcontroller that could remotely record and report long-term... P. Astillo, J. Maja, J. Greene |
8. Compensating for Soil Moisture Effects in Estimation of Soil Properties by Electrical Conductivity SensingBulk apparent soil electrical conductivity (ECa) is the most widely used soil sensing modality in precision agriculture. Soil ECa relates to multiple soil properties, including clay content (i.e., texture) and salt content (i.e., salinity). However, calibrations of ECa to soil properties are not temporally stable, due in large part to soil moisture differences between measurement dates. Therefore, the objective of this research was to investigate the effects of temporal soil moisture variations... K.A. Sudduth, N.R. Kitchen, E.D. Vories, S.T. Drummond |
9. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data AugmentationDigital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier |