scholarly journals Structure Theorems for Real-Time Variable Rate Coding With and Without Side Information

2012 ◽  
Vol 58 (12) ◽  
pp. 7135-7153 ◽  
Author(s):  
Y. Kaspi ◽  
N. Merhav
Keyword(s):  
Real Time ◽  
Side Information ◽  
Time Variable ◽  
Variable Rate ◽  
Structure Theorems ◽  
Rate Coding

scholarly journals Image processing based real-time variable-rate chemical spraying system for disease control in paddy crop

2020 ◽  
Vol 4 ◽  
pp. 21-30
Author(s):  
V.K. Tewari ◽  
C.M. Pareek ◽  
Gurdeep Lal ◽  
L.K. Dhruw ◽  
Naseeb Singh
Keyword(s):  
Image Processing ◽  
Disease Control ◽  
Real Time ◽  
Time Variable ◽  
Variable Rate ◽  
Paddy Crop

scholarly journals Progress and development on biological information of crop phenotype research applied to real-time variable-rate fertilization

Plant Methods ◽  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Yinyan Shi ◽  
Yang Zhu ◽  
Xiaochan Wang ◽  
Xin Sun ◽  
Yangfen Ding ◽  
...  
Keyword(s):  
Real Time ◽  
Time Variable ◽  
Biological Information ◽  
Variable Rate

Real-Time Variable Rate Spraying in Orchards and Vineyards: A Review

2018 ◽  
Vol 99 (2) ◽  
pp. 385-390 ◽  
Author(s):  
Sachin Vilas Wandkar ◽  
Yogesh Chandra Bhatt ◽  
H. K. Jain ◽  
Sachin M. Nalawade ◽  
Shashikant G. Pawar
Keyword(s):  
Real Time ◽  
Time Variable ◽  
Variable Rate ◽  
Variable Rate Spraying

Use of geographic information systems and remote sensing as automated tool for variable rate irrigation prescriptions

2019 ◽  
Author(s):  
◽  
Anh Thi Tuan Nguyen
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Regression Models ◽  
Field Data ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Crop Growth ◽  
Variable Rate ◽  
Water Application ◽  
Center Pivot

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Economic as well as water shortage pressure on agricultural use of water has placed added emphasis on efficient irrigation management. Center pivot technology has made great improvement with variable rate irrigation (VRI) technology to vary water application spatially and temporally to maximize the economic and environmental return. Proper management of VRI systems depends on correctly matching the pivot application to specific field temporal and areal conditions. There is need for a tool to accurately and inexpensively define dynamic management zones, to sense within-field variability in real time, and control variable rate water application so that producers are more willing to adopt and utilize the advantages of VRI systems. This study included tests of the center pivot system uniformity performance in 2014 at Delta Research Center in Portageville, MO. The goal of this research was to develop MOPivot software with an algorithm to determine unique management areas under center pivot systems based on system design and limitations. The MOPivot tool automates prescriptions for VRI center pivot based on non-uniform water needs while avoiding potential runoff and deep percolation. The software was validated for use in real-time irrigation management in 2018 for VRI control system of a Valley 8000 center pivot planted to corn. The water balance model was used to manage irrigation scheduling. Field data, together with soil moisture sensor measurement of soil water content, were used to develop the regression model of remote sensing-based crop coefficient (Kc). Remote sensing vegetation index in conjunction with GDD and crop growth stages in regression models showed high correlation with Kc. Validation of those regression models was done using Centralia, MO, field data in 2016. The MOPivot successfully created prescriptions to match system capacity of the management zone based on system limitations for center pivot management. Along with GIS data sources, MOPivot effectively provides readily available graphical prescription maps, which can be edited and directly uploaded to a center pivot control panel. The modeled Kc compared well with FAO Kc. By combining GDD and crop growth in the models, these models would account for local weather conditions and stage of crop during growing season as time index in estimating Kc. These models with Fraction of growth (FrG) and cumulative growing degree days (cGDD) had a higher coefficient of efficiency, higher Nash-Sutcliffe coefficient of efficiency and higher Willmott index of agreement. Future work should include improvement in the MOPivot software with different crops and aerial remote sensing imagery to generate dynamic prescriptions during the season to support irrigation scheduling for real-time monitoring of field conditions.

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