Geostatistical modelling of within-field soil and yield variability for management zones delineation: a case study in a durum wheat field

Geostatistical modelling of within-field soil and yield variability for management zones... The paper proposes a geostatistical approach for delineating management zones (MZs) based on multivariate geostatistics, showing the use of polygon kriging to compare durum wheat yield among the different MZs (polygons). The study site was a durum wheat field in southern Italy and yield was measured over three crop seasons. The first regionalized factor, calculated with factorial cokriging, was used to partition the field into three iso-frequency classes (MZs). For each MZ, the expected value and standard deviation of yield were estimated with polygon kriging over the three crop seasons. The yield variation was only in part related to soil properties but most of it might be ascribable to different patterns of meteorological conditions. Both components of variation (plant and soil) in a cropping system should then be taken into account for an effective management of rainfed durum wheat in precision agriculture. The proposed approach proved multivariate Geostatistics to be effective for MZ delineation even if further testing is required under different cropping systems and management. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Geostatistical modelling of within-field soil and yield variability for management zones delineation: a case study in a durum wheat field

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Publisher
Springer US
Copyright
Copyright © 2016 by Springer Science+Business Media New York
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-016-9462-9
Publisher site
See Article on Publisher Site

Abstract

The paper proposes a geostatistical approach for delineating management zones (MZs) based on multivariate geostatistics, showing the use of polygon kriging to compare durum wheat yield among the different MZs (polygons). The study site was a durum wheat field in southern Italy and yield was measured over three crop seasons. The first regionalized factor, calculated with factorial cokriging, was used to partition the field into three iso-frequency classes (MZs). For each MZ, the expected value and standard deviation of yield were estimated with polygon kriging over the three crop seasons. The yield variation was only in part related to soil properties but most of it might be ascribable to different patterns of meteorological conditions. Both components of variation (plant and soil) in a cropping system should then be taken into account for an effective management of rainfed durum wheat in precision agriculture. The proposed approach proved multivariate Geostatistics to be effective for MZ delineation even if further testing is required under different cropping systems and management.

Journal

Precision AgricultureSpringer Journals

Published: Jul 27, 2016

References

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