z-logo
open-access-imgOpen Access
Dynamics of Mean-Variance-Skewness of Cumulative Crop Yield Impact Temporal Yield Variance
Author(s) -
Abdullah A. Jaradat
Publication year - 2011
Publication title -
international journal of agronomy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.493
H-Index - 16
eISSN - 1687-8167
pISSN - 1687-8159
DOI - 10.1155/2011/426582
Subject(s) - skewness , yield (engineering) , statistics , cropping , variance (accounting) , mathematics , production (economics) , cropping system , cumulative distribution function , coefficient of variation , crop yield , tillage , crop rotation , agronomy , probability density function , crop , biology , ecology , agriculture , economics , metallurgy , materials science , accounting , macroeconomics
Farmers' decision to adopt new management or production system depends on production risk. Grain yield data was used to assess production risk in a field experiment composed of two cropping systems (CNV and ORG), each with eight subsystems (two levels each of crop rotation (2-yr and 4-yr), tillage management (conventional, CT and strip, ST), and fertilizer input (fertilized, YF and non-fertilized, NF)). Statistical moments, cumulative yield (CY), temporal yield variance (TYV) and coefficient of variation (CV) were used to assess the risk associated with adopting combinations of new management practices in CNV and ORG. The mean-variance-skewness (M-V-S) statistics derived from yield data separated all 16 subsystems into three clusters. Both cropping systems and clustered subsystems differed as to their ability to maintain a constant yield over years, displayed different yield cumulative probabilities, exhibited significant and different M-V-S relationships, and differed as to the reliability of estimating TYV as a function of CY. Results indicated that differences in management among cropping systems and subsystems contributed differently to the goal of achieving yield potential as estimated by the cumulative density function, and that certain low-input management practices caused a positive shift in yield distribution, and may lower TYV and reduce production risk

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom