pubs.acs.org/JAFC©XXXX American Chemical Society

J. Agric. Food Chem. XXXX, XXX, 000–000 A

DOI:10.1021/jf9025844

Using NIRS To Predict Fiber and Nutrient Content of DrylandCereal Cultivars

TAMI L. STUBBS,*,† ANN C. KENNEDY,‡ AND ANN-MARIE FORTUNA†

†Crop and Soil Sciences Department,Washington State University, Pullman,Washington 99164-6420 and‡USDA-ARS, Land Management and Water Conservation Research Unit, Pullman,

Washington 99164-6421

Residue from cultivars of spring wheat (Triticum aestivum L.), winter wheat, and spring barley

(Hordeum vulgare L.) was characterized for fiber and nutrient traits using reference methods and

near-infrared spectroscopy (NIRS). Calibration models were developed for neutral detergent fiber

(NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), carbon (C), sulfur (S), nitrogen (N),

and C:N. When calibrations were tested against validation sets for each crop year, NIRS was an

acceptable method for predicting NDF (standard error of prediction (SEP) < 0.87; R2 > 0.90) and

ADF (SEP < 0.81; R2 > 0.92) and moderately successful for ADL in 1 year of the study (SEP = 0.44;

R2 = 0.81) but less successful for C, S, N, and C:N (R2 all

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The dryland cereal cropping region of eastern Washingtonstate is characterized by diverse topography andwide variation inannual precipitation. The easternmost part of the region isdistinguished by steep slopes and receives >450 mm averageannual precipitation. The western portion of the cropping area ischaracterized by gently rolling slopes and receives

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SD/SECV ratios>3.0 are acceptable for quantitative prediction,ratios>2.5 and

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Berardo et al. (32) showed that NIRS was capable of predictingthe quality of pigeon pea (Cajanus cajan L.) NDF, ADF, ADL,and other traits for animal feed. They noted that correlation wasgenerally not as strong for ADL but it was an acceptableprediction in their study, as it was in our study.

Malley et al. (28) showed NIRS to be successful in predictingmanure C during composting but moderately successful for C:Nand only moderately useful for N and S prediction. Halgersonet al. (33) found that NIRS was not consistent in predicting S in

alfalfa. Others have foundNIRS to be less accurate for predictionof ADF in poultry litter (22) and unreliable for predicting N inpoultry litter (22, 34). Reeves (35), on the other hand, foundNIRS able to predict totalNbut not S inpoultry litter. LECOwasused in C, N, or S analysis for each of these studies, as we did inour study. Gislum et al. (19), Michel et al. (20), and Galvez-Solaet al. (18), among others, have been successful in using NIRS topredict N and/or C but with different methods for determiningreference values of plants and other materials. Improved calibra-tion equations, possibly on larger populations of samples, willneed to be developed before NIRS can be used to adequatelypredict elemental content of cereal residue.

Environment, Crop Types, and Cultivars. Cereal residue variesin fiber content with growing location (7,8,36) and crop (6,8). Inthis study, NIRS and reference methods equally ranked the fourgrowing locations according to predicted fiber quality traits inspring and winter wheat and spring barley. Pearson correlationcoefficients were greater than 0.90 for NDF, ADF, and ADL forall locations and crops and were below 0.90 for C, S, N, and C:N(Table 4). The Ritzville location had correlation coefficients

Figure 1. Linear regression relationship between laboratory referencemethods and NIRS-predicted values for (a) percent neutral detergent fiber(NDF; R2 = 0.93), (b) percent acid detergent fiber (ADF; R2 = 0.93), and(c) percent acid detergent lignin (ADL; R2 = 0.57) of spring barley, springwheat, and winter wheat residue from 2003 on a dry weight basis.

Table 3. Coefficients of Pearson Correlation between Laboratory ReferenceValues and NIRS-Predicted Values for Cereal Residue Fiber Traits across AllYears, Locations, and Cultivarsa

NDF ADF ADL C S N C:N

NDF 0.9606 0.7633 0.3185 0.1556 -0.3749 -0.5768 0.5332

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ranging from 0.89 to 0.84 for S, N, and C:N, while correlationcoefficients for the same traits at other locations were less than0.75. Nitrogen and C:Nwere not well correlated between analysismethods at Pullman, nor was C at Dayton or C:N at Dusty. Allother locations and all other analyses were well correlated. Wefound that NIRS and reference methods were well correlated forall crops across all traits, except for C:N in springwheat, andN inwinter wheat (Table 4). Pearson correlation coefficients weregreater than 0.90 for NDF, ADF, and ADL of each crop.

Redaelli and Berardo (17) used NIRS to predict the NDF,ADF, and ADL of oat hulls. They showed that oat cultivarsgrown at various locations differed in their fiber contents, andoverall, cultivar played a stronger role than location in determin-ing variability. Al Haj Khaled et al. (37) used NIRS analysis ofleaf blade chemical components (fiber, cellulose, hemicellulose,lignin) to rank grass species based on their nutritive value. Forboth years of this study,NIRS andwet chemistry values for ADFandNDFwere significantly correlated (P

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Received for review July 24, 2009. Revised manuscript receivedOctober

13, 2009. Accepted November 12, 2009.