Proceedings
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| Filter results15 paper(s) found. |
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1. Can Active Sensor Based NDVI Consistently Classify Wheat Genotypes?ABSTRACT ... M.A. Naser, R. khosla, S. Haley, R. Reich, L. Longchamps, M. Moragues, G.W. buchleiter, G.S. Mcmaster |
2. Variation in Nitrogen Use Efficiency for Multiple Wheat Genotypes across Dryland and Irrigated Cropping SystemsABSTRACT ... M.A. Naser, R. Khosla, R. Reich, S. Haley, L. longchamps, M. Moragues, G.W. buchleiter, G.S. Mcmaster |
3. Estimation Of Sugar Beet Yield Brfore Harvesting Using Meteorological Data And Spot Satellite DataIn Japan, sugar beet is only cultivated in Hokkaido, the northernmost island. The area of sugar beet cultivation in Tokachi District is 30,000ha, which is equal to about 45% of the total national production area. Because sugar beet is suited to cool weather conditions, it is an important rotation crop in Hokkaido. The production of beet sugar in Hokkaido is about 640,000 tons, which is 75... C. Hongo, K. Niwa |
4. Cognitive Radio In Precision AgricultureThis is an attempt to design a precision agriculture (PA) model, to control the required parameters in greenhouse with wireless sensor network (WSN). This proto type model of wireless sensor and actuators network is designed as per required parameters of available crops in a greenhouse. The design of the sensor node consists of sensors, a micro-controller and a low-powered radio module. Real-time data, enable the operators to characterise the operating parameters of the greenhouse and also... S.P. Nayse, D.D. Choudhari, V.M. Wadhai |
5. Application based Wireless Sensor Node for Underground Moisture Sensing for Precision AgricultureIn this paper, we are attempting to examine the WUWSN (wireless underground water sensor node*) for precision agriculture. The development and function of this sensor along with its software application is described in this paper. The equipment is under testing and the laboratory results and interpretations are discussed in this paper. This equipment is based on the new concept of sensing underground soil moisture. The sensor is cost effective sensor and has a long... S.P. Nayse, A.S. Mohammad |
6. Creation Of Prescription For Optimal Nitrogen Fertilization Through Evaluation Of Soil Carbon Amount Using Remotely Sensed DataIn these years, drastic increase of agricultural production costs has been induced, which was triggered by the sharp rise of costs relating to agricultural production materials such as fertilizers and oil. In Japan, the substantial negative influence is anticipated to spread over to management of the farmers particularly in Hokkaido, the northern part of Japan. As one of the measures against this influence, a plan of effective fertilizer application and also... E. Tamura, K. Aijima, K. Niwa, O. Nagata, K. Wakabayashi, C. Hongo |
7. Study On Plant Health Condition Monitoring Using Acoustic Radiation ForceIn recent years, irrigation method using the negative pressure difference attracts attention from the point of view of water saving. In addition, it is proved that this technique is effective in upbringing of the plant as well as saving of water. By measuring water distribution of soil, active irrigation control will be performed In our previous study, we confirmed that the resonance frequency of a leaf is influenced by the water stress to the plant. Thus the vibration measurement... Y. Nakagawa, M. Sano, T. Shirakawa, K. Yamagishi, T. Sugihara, M. Ohaba, S. Shibusawa, T. Sugimoto |
8. Automatic Detection And Mapping Of Irrigation System Failures Using Remotely Sensed Canopy Temperature And Image ProcessingToday there is no systematic way to identify and locate failures of irrigation systems mainly because of the labor costs associated with locating the failures. The general aim of this study was to develop an airborne thermal imaging system for semi - automatic monitoring and mapping of irrigation system failures, specifically, of leaks and clogs. Initially, leaks and clogs were simulated by setting controlled trials in table grapes vineyards and olive groves. Airborne thermal... V. Alchanatis, Y. Cohen, M. Sprinstin, A. Cohen, I. Zipori, A. Dag, A. Naor |
9. Studies on Soil Spatial Variability and Its Impact on Cane Yield Under Precision Nutrient Management SystemIn present investigation an attempt was made to quantify the soil variability of 30 grids of 10 m x 10 m dimension at research farm of Nandi Sahakari Sakkare Karkhane (NSSK), Krishna Nagar, District. Bijapur. Each grid (10 m x 10 m) showed variation with available nitrogen as low as 140 kg ha-1 to as high as 245 kg/ha with a range of 105 kg/ha, phosphorus as low as 53 kg P2O5 ha-1 and as high as 89.3 kg P2O5 ha-1 with... M. Kumar r, M. Kumar r, D. Nadagouda |
10. Agronomic Characteristics of Green Corn and Correlations with Productivity for the Establishment of Management Zones in Vale Do Ribeira, SP, BrazilIn Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphic... W.J. Souza, V.S. Akune, S.H. Benez, L.C. Citon, P.H. Nakazawa, A.J. Santana neto |
11. Spatial Variability and Correlations Between Soil Attributes and Productivity of Green Corn CropIn Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphic... W.J. Souza, S.H. Benez, P.H. Nakazawa, A.J. Santana neto, L.C. Citon, V.S. Akune |
12. Spotweeds: a Multiclass UASs Acquired Weed Image Dataset to Facilitate Site-specific Aerial Spraying Application Using Deep LearningUnmanned aerial systems (UASs)-based spot spraying application is considered a boon in Precision Agriculture (PA). Because of spot spraying, the amount of herbicide usage has reduced significantly resulting in less water contamination or crop plant injury. In the last demi-decade, Deep Learning (DL) has displayed tremendous potential to accomplish the task of identifying weeds for spot spraying application. Also, most of the ground-based weed management technologies have relied on DL techniques... N. Rai, Y. Zhang, J. Quanbeck, A. Christensen, X. Sun |
13. Comparison of Canopy Extraction Methods from UAV Thermal Images for Temperature Mapping: a Case Study from a Peach OrchardCanopy extraction using thermal images significantly affects temperature mapping and crop water status estimation. This study aimed to compare several canopy extraction methodologies by utilizing a large database of UAV thermal images from a precision irrigation trial in a peach orchard. Canopy extraction using thermal images can be attained by purely statistical analysis (S), a combination of statistical and spatial analyses (SS), or by synchronizing thermal and RGB images, following RGB statistical... L. Katz, A. Ben-gal, I. Litaor, A. Naor, A. Peeters, E. Goldshtein, V. Alchanatis, Y. Cohen |
14. Cultivating Future Leaders in Sustainable Agriculture: Insights from the Digital Agriculture Fellowship Program at the University of California, RiversideFunded by USDA's National Institute of Food and Agriculture’s Sustainable Agricultural Systems Program and housed at the University of California, Riverside (UCR), the Digital Agriculture Fellowship (DAF) aims at equipping undergraduate students with the knowledge and experience necessary to meet the agricultural challenges posed by climate change and sustainability concerns. The program was established in 2020 and will be funded through 2026. Activities span over fifteen months for... E. Scudiero, C.I. Nugent, C. Ng, N. Jones, T. Azzam, N.G. Salunga, S. Lemus |
15. Machine Learning Approach to Study the Effect of Weather and Proposed Climate Change Scenarios on Variability in the Ohio Corn and Soybean YieldClimate is one of the primary factors that affects agricultural production. Climate change and extreme weather events have raised concerns about its effect on crop yields. Climate change patterns affect the crop yield in many ways including the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days. It is important to analyze the effect of climate change on yield variability for a better understanding of the effect... R. Dhillon, G. Takoo |