|SCUDIERO, ELIA - University Of California|
|TEATINI, PIETRO - University Of Padua|
|DAL FERRO, NICOLA - University Of Padua|
|SIMONETTI, GIANLUCA - University Of Padua|
|MORARI, FRANCESCO - University Of Padua|
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/29/2014
Publication Date: 8/13/2014
Citation: Scudiero, E., Teatini, P., Corwin, D.L., Dal Ferro, N., Simonetti, G., Morari, F. 2014. Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland. Agronomy Journal. DOI: 10.2134/agronj14.0102.
Interpretive Summary: Understanding the causes of variation in crop yield over space and time is essential to precision agriculture. Especially in rain-fed farming, a large portion of the spatial and temporal variability of crop production depends on soil spatial variability and on the interactions between soil and meteorological settings (i.e., water availability).This study developed an approach using canopy reflectance (i.e., visible and near infra-red) measurements with an on-the-go sensor to understand the reasons for spatio-temporal variability of crop status. In particular the study investigated the possibility of discriminating between salinity and water stress, both of which influence crop yield. Analysis of intra-annual reflectance spatio-temporal variability provided a means of understanding stress onset and impact on a crop according to soil variability and meteorological conditions. However, the intra-annual analysis did not enable a distinction between the two stress types. The inter-annual reflectance spatio-temporal variability identified areas where stress was stable through the years and areas where soil-water content enhances/mitigates soil-plant interaction. Reflectance inter-annual temporal variability in saline areas was significantly lower than in zones of optimal maize growth and affected by water stress only. Where the two stresses superpose the distinction between the areas only affected by salinity from those affected also by water stress was unachievable with this type of data analysis. The ramifications of this work are a better understanding of the interactions of water and salinity stresses as they pertain to yield variations over time and space, which has profound implications for site-specific management in arid regions. Land resource managers, producers, agriculture consultants, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of this site-specific management information
Technical Abstract: Spatio-temporal 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 spatio-temporal 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 inter-annual reflectance variations were analyzed, across the entire field and at each map-cell over time, to understand how the different soil-related stress types (i.e., salinity and water) arise under different meteorological conditions. The results show that normalized difference vegetation index (NDVI), acquired during the maize flowering and kernel maturation stages (over the three growing seasons of 2010, 2011, and 2012), effectively describes yield spatio-temporal variability. In particular, stressed areas exhibited the smallest changes in NDVI over a single growing season. Soil salinity and water stress are responsible for ca. 44% of the intra-annual NDVI change. When multi-year 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. Multi-year 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.