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ISPRS Int. J. Geo-Inf. 2018, 7(2), 61; https://doi.org/10.3390/ijgi7020061

Spatial Analysis of Digital Imagery of Weeds in a Maize Crop

1
Columbia Basin Agricultural Research Center, Oregon State University, 48037 Tubbs Ranch Rd., Adams, OR 97810, USA
2
Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK
3
Department of Crop Protection, Instituto de Ciencias Agrarias, CSIC, Serrano 115 B, 28006 Madrid, Spain
*
Author to whom correspondence should be addressed.
Received: 16 December 2017 / Revised: 6 February 2018 / Accepted: 8 February 2018 / Published: 10 February 2018
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Abstract

Modern photographic imaging of agricultural crops can pin-point individual weeds, the patterns of which can be analyzed statistically to reveal how they are affected by variation in soil, by competition from other species and by agricultural operations. This contrasts with previous research on the patchiness of weeds that has generally used grid sampling and ignored processes operating at a fine scale. Nevertheless, an understanding of the interaction of biology, environment and management at all scales will be required to underpin robust precise control of weeds. We studied the spatial distributions of six common weed species in a maize field in central Spain. We obtained digital imagery of a rectangular plot 41.0 m by 10.5 m (= 430.5 m2) and from it recorded the exact coordinates of every seedling: more than 82,000 individuals in all. We analyzed the resulting body of data using three techniques: an aggregation analysis of the punctual distributions, a geostatistical analysis of quadrat counts and wavelet analysis of quadrat counts. We found that all species were aggregated with average distances across patches ranging from 3 cm–18 cm. Species with small seeds tended to occur in larger patches than those with large seeds. Several species had aggregation patterns that repeated periodically at right angles to the direction of the crop rows. Wheel tracks favored some species (e.g., thornapple), whereas other species (e.g., johnsongrass) were denser elsewhere. Interactions between species at finer scales (<1 m) were negligible, although a negative correlation between thornapple and cocklebur was evident. We infer that the spatial distributions of weeds at the fine scales are products both of their biology and local environment caused by cultivation, with interactions between species playing a minor role. Spatial analysis of such high-resolution imagery can reveal patterns that are not immediately evident from sampling at coarser scales and aid our understanding of how and why weeds aggregate in patches. View Full-Text
Keywords: weeds; spatial distribution; aggregation; variance:mean ratio; geostatistics; variogram; wavelet analysis; plant competition weeds; spatial distribution; aggregation; variance:mean ratio; geostatistics; variogram; wavelet analysis; plant competition
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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).

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San Martín, C.; Milne, A.E.; Webster, R.; Storkey, J.; Andújar, D.; Fernández-Quintanilla, C.; Dorado, J. Spatial Analysis of Digital Imagery of Weeds in a Maize Crop. ISPRS Int. J. Geo-Inf. 2018, 7, 61.

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