Based on the measurement of soil penetration resistance (PR), it is possible to identify compacted soil layers, where root growth may be harmed, affecting crop development and yield. The objective of this work was to analyze the use of management zones (MZ), delimited on the basis of mapping of the spatial variability of the soil apparent electrical conductivity (ECa), in the differentiation of soil compaction levels. The work was carried out in a 25.8-ha no-tillage area, cultivated under a center pivot. The ECa was measured under two soil moisture conditions (13.7 and 16.45%), using the Terram® equipment. Soil penetration resistance (PR) was measured using the SoloStar PLG5500 penetrograph. Based on the spatial variability ECa mapping, management zones (2, 3, and 4 zones) were delimited. The mean PR values ??of each MZ were compared by the t-test of means. It was possible to differentiate mean values ??of penetration resistance (PR), which vary from 0.9 to 2.10 MPa, from the characterization of management classes generated on the basis of the ECa spatial variability. The highest stratification of PR values ??was obtained as a function of sampling directed at delimited management zones when the soil had lower moisture content (13.7%). The highest mean PR values ??were obtained for the split of the ECa map into at least three classes. It was identified that for the study area there is no need to perform any mechanical decompaction operation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.