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United States Department of Agriculture

Agricultural Research Service

Title: Relating Potato Yeild and Quality to Variability in Soil Characteristics

Authors
item Redulla, C - WASH. STATE UNIV. PROSSER
item Davenport, J - WASH. STATE UNIV. PROSSER
item Evans, Robert
item Hattendorf, M - VANTAGE POINT FT COLLINS
item Alva, Ashok
item Boydston, Rick

Submitted to: American Journal of Potato Research
Publication Type: Abstract Only
Publication Acceptance Date: August 1, 2001
Publication Date: August 1, 2001
Citation: REDULLA, C., DAVENPORT, J.R., EVANS, R.G., HATTENDORF, M.J., ALVA, A.K., BOYDSTON, R.A. RELATING POTATO YEILD AND QUALITY TO VARIABILITY IN SOIL CHARACTERISTICS. AMERICAN JOURNAL OF POTATO RESEARCH. 78:478. 2001.

Technical Abstract: There is a void in our understanding of the causes of within-field spatial yield variability in potato. To begin to fill this void, a study was conducted from 1997 to 2000 on a commercial farm in eastern Washington. Selected center-pivot irrigated fields were soil-sampled on 0.4-ha grids before potato (Solanum tuberosum L.) planting. The soil samples were analyzed for nitrate-N, ammonium-N,P,K, organic matter, pH, texture, and other chemical properties. Four to five days before commercial harvest, a 3-m length of potato row was harvested at each original grid point using a one-row digger. The potatoes were weighed, sorted into different size classes by weight, and evaluated for specific gravity. Correlation and stepwise regression analyses were done on the data from three fields which had been conventionally (uniformly) fertilized. The soil variable which had the highest r with yield differed among the three fields. Highest correlation coefficient with the yield variable was with sand in one field (r = 0.33, P < 0.01), with clay in a second field (r = 0.20, P = 0.04), and with pH the two other fields (r = -0.22, P = 0.04* and r = -0.18, P = 0.12). Stepwise linear regression analyses with yield as the dependent variable revealed that soil textural class, pH, and OM contributed the largest part of R-square of the model although the highest model R-square obtained was <0.42 indicating other soil, environmental or pest variables contribute to the spatial variability of potato yield and quality.

Last Modified: 8/1/2014
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