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1. Analysis of High Yield Condition Using a Rice Yield Predictive ModelRice production in Japan is facing problems of yield and quality instability owing to recent climate changes and a decline in rice prices, and possible competition with foreign inexpensive rice. Thus, it is becoming more important to stably achieve high yield and quality, while reducing production costs. Various data, including crop growth, farmer’s management styles, yield and quality, has recently become accessible in actual fields using advanced information and communication technologies.... Y. Hirai, T. Yamakawa, E. Inoue, T. Okayasu, M. Mitsuoka |
2. Design and Performance Experiment of an Outer Grooved-Wheel Fertilizer Apparatus with the Helical ToothTraditional outer groove-wheel fertilizer apparatus (OGWFA) with the straight tooth exists the problem of breakage and pulsation in the fertilizing process. A new type of OGWFA with the helical tooth has been designed to solve this problem, and the amount of fertilizer can be adjusted. The helix angle of the helical tooth has been optimized by theory analysis and DEM simulation. It reveals that the helix angle should be ranged from 34.4° to 68.8°. The performances of the OGWFA with the... D. Jun, X. Junfang, Z. Wangyuan, W. Qiaohua, D. Youchun, S. Caixia, Z. Zhihui |
3. Estimating Litchi Canopy Nitrogen Content Using Simulated Multispectral Remote Sensing DataThis study aims at evaluating the performance of seven highly spatial resolution remote sensing data in litchi canopy nitrogen content estimation. The litchi canopy reflectance were collected by ASD field spectrometer. Then the canopy spectral data were resampled based on the spectral response functions of each satellite sensors (Geo-eye, GF-WFV1, Rapid-eye, WV-2, Landsat 8, WV-3, and Sentinel-2). The spectral indices in literature were derived based on the simulated data. Meanwhile, the successive... D. Li, H. Jiang, S. Chen, C. Wang |
4. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in ArgentinaThe lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomist... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito |
5. Evaluation of Fall and Spring Nitrogen Rates Effect on Cereal Rye Forage Crude Protein and Tillering Using NDVI and Canopeo to Make Infield Nitrogen Rate DecisionsFall applied nitrogen has been used to increase plant tiller and protein in wheat but less research has been done of its effects on cereal rye forage and how NDVI and Canopeo readings can be used to make nitrogen application management decisions. This study took place at the Ohio State University North Central Agricultural Research Station in Fremont, Ohio. The experiment is a randomized complete block split-plot design with four nitrogen rates in the fall (0, 30, 60, and 90 lbs/ac) and in the... K. Stahl, J.M. Hartschuh, A. Gahler |
6. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and VisionAdvancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi |