Statistics, Department of


Date of this Version



Published in Crop Sci. 46:751–757 (2006).


Copyright 2006 Crop Science Society of America


Screening germplasm for chemical and nutritional content can be expensive and time consuming. Near infrared spectroscopy (NIRS) and application of geostatistical models can make screening more efficient. The objectives of this study were to utilize these technologies to: (i) generate chemical and nutritional values for the U.S. photoperiod insensitive sorghum collection, (ii) describe variability for those traits, (iii) identify accessions in the highest and lowest 1% for each trait, and (iv) describe relationships among the accessions. Accessions were grown at Ithaca, NE, during 2001 and 2002. Samples of grain were scanned and NIRS equations developed for starch, fat, crude protein, acid detergent fiber, and phosphorus. The NIRS generated values for each accession can be accessed on GRIN at; verified 22 November 2005. The highest and lowest 1% of accessions was identified for each trait by best linear unbiased predictors (BLUPs). Means and standard deviations for observed values and variances due to accessions were calculated. Rank correlations between BLUPs and observed values ranged from r = 0.82 to r = 0.92. Principal component analysis showed that much of the variation is attributable to a contrast of starch with a weighted average of fat, crude protein, acid detergent fiber, and phosphorus. Cluster analyses showed clusters on the basis of canonical values, but no geographical, taxonomical, or morphological interpretation of the clusters was apparent.