NDLI: Predicting Weed Species Occurrence Based on Site Properties and Previous Year's Weed Presence

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Predicting Weed Species Occurrence Based on Site Properties and Previous Year's Weed Presence

Content Provider	Springer Nature Link
Author	Anita Dille, J. Mortensen, David A. Young, Linda J.
Copyright Year	2002
Abstract	Probabilities of Setaria spp., Solanum ptycanthum, Helianthus annuus and Abutilon theophrasti occurrence were predicted based on two site property factors and weed species presence in a previous year using logistic regression models. Weed seedling surveys were conducted just prior to post-emergence weed management in two grower-managed fields in the central Platte River Valley of Nebraska, USA at Alda in 1995 and 1996 and at Shelton in 1994, 1995 and 1997. Weed species density data were re-classified as present or absent at each pair of points on the sampling grid, representing quadrat locations either in the pre-emergence herbicide band or between the crop rows. Site property data were collected in March 1995 at Alda and March 1994 at Shelton. Using factor analysis, two independent factors were derived from correlated attributes of relative elevation, percent organic carbon, pH, nitrate, phosphate, and soil texture measured at Alda. Logistic regression models were estimated and parameterized for each weed species at Alda in 1996 based on the two factors (“topography and soil type” and “soil fertility status”) and weed species presence in 1995. Performance of these models for each weed species was evaluated using the independent data set from Shelton. Between and on crop row Setaria spp. and Solanum ptycanthum models described these populations at Alda. At Shelton, on row Setaria spp. occurrence and between row Solanum ptycanthum occurrence were adequately predicted. Helianthus annuus or Abutilon theophrasti occurrence was not well predicted even with knowledge of their presence in the previous year, probably as a result of low actual occurrence within a given year. Maps of predicted occurrence have value in directing weed scouting to field locations where the species is most likely to occur.
Starting Page	193
Ending Page	207
Page Count	15
File Format	PDF
ISSN	13852256
Journal	Precision Agriculture
Volume Number	3
Issue Number	3
e-ISSN	15731618
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2002-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Meteorology/Climatology Remote Sensing/Photogrammetry Agriculture Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences Soil Science & Conservation
Content Type	Text
Resource Type	Article
Subject	Agricultural and Biological Sciences

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