נגישות
menu      
Advanced Search
Syntax
Search...
Volcani treasures
About
Terms of use
Manage
Community:
אסיף מאגר המחקר החקלאי
Powered by ClearMash Solutions Ltd -
Spatiotemporal normalized ratio methodology to evaluate the impact of field-scale variable rate application
Year:
2022
Source of publication :
precision agriculture (source )
Authors :
Ben-Gal, Alon
;
.
Cohen, Yafit
;
.
Volume :
Co-Authors:
  • L. Katz, 
  • A. Ben-Gal, 
  • M. I. Litaor, 
  • A. Naor, 
  • M. Peres, 
  • I. Bahat, 
  • Y. Netzer, 
  • A. Peeters, 
  • V. Alchanatis & 
  • Y. Cohen 
Facilitators :
From page:
0
To page:
0
(
Total pages:
1
)
Abstract:

Wide assimilation of precision agriculture among farmers is currently dependent on the ability to demonstrate its efficiency at the field-scale. Yet, most experiments that compare variable-rate vs uniform application (VRA and UA) are performed in strips, concentrated in a small portion of the field with limited extrapolation to the field scale. A spatiotemporal normalized ratio (STNR) methodology is proposed to evaluate the impact of VRA compared with UA for on-farm trials at the field scale. It incorporates a base year in which the whole plot is managed with UA and consecutive years in which half of the plot is managed with UA and the other half is managed with VRA. Additionally, a novel normalized relative comparison index (NRCI) is presented where the ratios of VRA/UA sub-plots are compared between a base year and a consecutive year, for any measured parameter. The NRCI determines the impact of VRA on variability using statistical measures of dispersion (variability measures) and on performance with statistical measures of central tendency (performance measures). Variability measures with NRCI values lower or higher than 1 indicate VRA management decreased or increased variability. Performance measures with NRCI lower or higher than 1 indicate subplot impairment or improvement, respectively due to VRA management. The methodology was demonstrated on a commercial drip irrigated peach orchard and a wine grape vineyard. NRCI results showed that VRA drip irrigation reduced water status in-field variability but did not necessarily increase yield. The benefits and limitations of the proposed design are discussed.

Note:
Related Files :
Precision irrigation management
Stem water potential
Variability
Variable rate application
Show More
Related Content
More details
DOI :
10.1007/s11119-022-09877-4
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
58276
Last updated date:
23/03/2022 17:51
Creation date:
23/03/2022 17:37
You may also be interested in
Scientific Publication
Spatiotemporal normalized ratio methodology to evaluate the impact of field-scale variable rate application
  • L. Katz, 
  • A. Ben-Gal, 
  • M. I. Litaor, 
  • A. Naor, 
  • M. Peres, 
  • I. Bahat, 
  • Y. Netzer, 
  • A. Peeters, 
  • V. Alchanatis & 
  • Y. Cohen 
Spatiotemporal normalized ratio methodology to evaluate the impact of field-scale variable rate application

Wide assimilation of precision agriculture among farmers is currently dependent on the ability to demonstrate its efficiency at the field-scale. Yet, most experiments that compare variable-rate vs uniform application (VRA and UA) are performed in strips, concentrated in a small portion of the field with limited extrapolation to the field scale. A spatiotemporal normalized ratio (STNR) methodology is proposed to evaluate the impact of VRA compared with UA for on-farm trials at the field scale. It incorporates a base year in which the whole plot is managed with UA and consecutive years in which half of the plot is managed with UA and the other half is managed with VRA. Additionally, a novel normalized relative comparison index (NRCI) is presented where the ratios of VRA/UA sub-plots are compared between a base year and a consecutive year, for any measured parameter. The NRCI determines the impact of VRA on variability using statistical measures of dispersion (variability measures) and on performance with statistical measures of central tendency (performance measures). Variability measures with NRCI values lower or higher than 1 indicate VRA management decreased or increased variability. Performance measures with NRCI lower or higher than 1 indicate subplot impairment or improvement, respectively due to VRA management. The methodology was demonstrated on a commercial drip irrigated peach orchard and a wine grape vineyard. NRCI results showed that VRA drip irrigation reduced water status in-field variability but did not necessarily increase yield. The benefits and limitations of the proposed design are discussed.

Scientific Publication
You may also be interested in