Next Article in Journal
Soil Conservation Practices and Stakeholder’s Participation in Research Projects—Empirical Evidence from Southern Italy
Next Article in Special Issue
Satellite and Proximal Sensing to Estimate the Yield and Quality of Table Grapes
Previous Article in Journal
Quality and Nutritional Evaluation of Regina Tomato, a Traditional Long-Storage Landrace of Puglia (Southern Italy)
Previous Article in Special Issue
Sampling Stratification Using Aerial Imagery to Estimate Fruit Load in Peach Tree Orchards
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Agriculture 2018, 8(6), 84; https://doi.org/10.3390/agriculture8060084

Use of Farmer Knowledge in the Delineation of Potential Management Zones in Precision Agriculture: A Case Study in Maize (Zea mays L.)

Research Group in AgroICT and Precision Agriculture, Agrotecnio Center, University of Lleida, Av. Rovira Roure 191, 25198 Lleida, Catalonia, Spain
*
Author to whom correspondence should be addressed.
Received: 28 May 2018 / Revised: 8 June 2018 / Accepted: 11 June 2018 / Published: 13 June 2018
(This article belongs to the Special Issue Precision Agriculture)
View Full-Text   |   Download PDF [12270 KB, uploaded 13 June 2018]   |  

Abstract

One of the fields of research in precision agriculture (PA) is the delineation of potential management zones (PMZs, also known as site-specific management zones, or simply management zones). To delineate PMZs, cluster analysis is the main used and recommended methodology. For cluster analysis, mainly yield maps, remote sensing multispectral indices, apparent soil electrical conductivity (ECa), and topography data are used. Nevertheless, there is still no accepted protocol or guidelines for establishing PMZs, and different solutions exist. In addition, the farmer’s expert knowledge is not usually taken into account in the delineation process. The objective of the present work was to propose a methodology to delineate potential management zones for differential crop management that expresses the productive potential of the soil within a field. The Management Zone Analyst (MZA) software, which implements a fuzzy c-means algorithm, was used to create different alternatives of PMZ that were validated with yield data in a maize (Zea mays L.) field. The farmers’ expert knowledge was then taken into account to improve the resulting PMZs that best fitted to the yield spatial variability pattern. This knowledge was considered highly valuable information that could be also very useful for deciding management actions to be taken to reduce within-field variability. View Full-Text
Keywords: Sentinel-2; accumulated NDVI; apparent electrical conductivity; topography; cluster analysis Sentinel-2; accumulated NDVI; apparent electrical conductivity; topography; cluster analysis
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Martínez-Casasnovas, J.A.; Escolà, A.; Arnó, J. Use of Farmer Knowledge in the Delineation of Potential Management Zones in Precision Agriculture: A Case Study in Maize (Zea mays L.). Agriculture 2018, 8, 84.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Agriculture EISSN 2077-0472 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top