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Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

De Faveri, J.a., Verbyla, A.P.b., Pitchford, W.S.c., Venkatanagappa, S.d. f. and Cullis, B.R.e. (2015) Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials. Crop and Pasture Science, 66 (9). pp. 947-962.

Full text not currently attached. Access may be available via the Publisher's website or OpenAccess link.

Article Link(s): http://dx.doi.org/10.1071/CP14312

Publisher URL: http://www.publish.csiro.au/paper/CP14312.htm


Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.

Item Type:Article
Business groups:Horticulture and Forestry Science
Subjects:Science > Statistics > Statistical data analysis
Agriculture > Agriculture (General) > Methods and systems of culture. Cropping systems
Plant culture > Harvesting, curing, storage
Plant culture > Field crops > Forage crops. Feed crops
Deposited On:17 Apr 2016 23:53
Last Modified:03 Sep 2021 16:50

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