Spatiotemporal Response of Maize Yield to Edaphic and Meteorological Conditions in a Saline Farmland

• Published in: Agronomy journal Vol. 106; no. 6; pp. 2163 - 2174
• Main Authors: Scudiero, Elia, Teatini, Pietro, Corwin, Dennis L., Ferro, Nicola Dal, Simonetti, Gianluca, Morari, Francesco
• Format: Journal Article
• Language: English
• Published: Madison The American Society of Agronomy, Inc 01.11.2014; American Society of Agronomy
• Subjects: Agricultural land
• ISSN: 0002-1962; 1435-0645
• DOI: 10.2134/agronj14.0102

Spatiotemporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatiotemporal variability of maize (Zea mays L.) yield using ground‐based reflectance acquisitions in a salinity‐ and water‐stress‐affected 21‐ha field beside the Venice Lagoon, Italy. Intra‐ and interannual reflectance variations were analyzed across the entire field and at each map cell with time to understand how the different soil‐related stresses (i.e., salinity and water) arise under different meteorological conditions. The results show that the normalized difference vegetation index (NDVI) acquired during the maize flowering and kernel maturation stages (during the three growing seasons of 2010, 2011, and 2012) effectively described yield spatiotemporal variability. In particular, stressed areas exhibited the smallest changes in NDVI during a single growing season. Soil salinity and water stress were responsible for approximately 44% of the intra‐annual NDVI change. When multiyear NDVI data are compared, areas affected by soil salinity show the smallest temporal variability. Nevertheless, areas that are slightly saline and constantly affected by water stress could not be distinguished from highly saline areas. Multiyear reflectance data can be a useful tool to characterize areas where soil salinity is the main factor limiting crop production. In areas where several plant stresses occur simultaneously every year, the proposed approach could be used to guide precision irrigation to make adjustments for within‐field leaching requirement and/or irrigation needs.