Development of near infrared reflectance analysis calibrations for estimating genetic parameters for cellulose content in Eucalyptus globulus

Abstract

Determining kraft pulp yield in the traditional way is slow and expensive, limiting the numbers of samples that may be processed. An alternative is to use a secondary standard, such as cellulose content of the wood, which is strongly correlated with kraft pulp yield. The feasibility and efficiency of predicting cellulose content using near infrared reflectance (NIR) analysis was examined for Eucalyptus globulus Labill. Calibrations for NIR prediction of cellulose content indicated that NIR analysis could be used as a reliable predictor. Standard errors of calibration were 1% or lower, and there was excellent agreement between laboratory and predicted cellulose values. Cellulose content was under moderate genetic control (h2 ranging from 0.32 to 0.57), and genetic correlations with tree diameter and basic density were variable (ranging from –0.11 to –0.51 and –0.33 to 0.67, respectively). The advantages, disadvantages, and potential applications of NIR analysis for predicting cellulose content are examined.

Cellulose content as a selection trait in breeding for kraft pulp yield in Eucalyptus urophylla

“…The reasonably good correlations between pulp yield and cellulose content either from disks or increment cores indicated that cellulose content determined by the diglyme-HCl method is a good predictor of pulp yield as previously has been shown in E. globulus and E. nitens (Wallis et al, 1997;Raymond and Schimleck, 2002;Schimleck et al, 2004). Cellulose content determined by this method had high repeatability (r = 0.96−0.98) with small standard deviation of duplicate measurements (about 1% of the mean) indicating that cellulose content measured by this method can give reliable results.…”

“…The somewhat higher standard deviation obtained for the estimate of pulp yield duplicates (0.68%, or about 1.4% of the mean) contributes to imprecision of the relationships between cellulose and pulp yield. Several recent studies evaluating cellulose content have used NIR (near infrared reflectance) prediction of cellulose, using calibrations developed from a sub-set of the samples that have been chemically analysed for cellulose (Raymond and Schimleck, 2002;Schimleck et al, 2004;Apiolaza et al, 2005). Such calibrations enable accurate prediction of cellulose content from NIR information in E. globulus and E. nitens (R 2 = 0.83−0.92) (Raymond and Schimleck, 2002;Schimleck et al, 2004).…”

“…Several recent studies evaluating cellulose content have used NIR (near infrared reflectance) prediction of cellulose, using calibrations developed from a sub-set of the samples that have been chemically analysed for cellulose (Raymond and Schimleck, 2002;Schimleck et al, 2004;Apiolaza et al, 2005). Such calibrations enable accurate prediction of cellulose content from NIR information in E. globulus and E. nitens (R 2 = 0.83−0.92) (Raymond and Schimleck, 2002;Schimleck et al, 2004). NIR prediction is faster than the direct measure using diglyme-HCl method (Schimleck et al, 2004) and its use would increase the number of samples that can be analysed.…”

“…Cellulose content is strongly correlated with kraft pulp yield (Kube and Raymond, 2002;Wallis et al, 1996) and can therefore be used as an indirect measure of it. The methods to determine cellulose content are simpler and less expensive than the direct measurement of pulp yield, require a much smaller wood sample of about 1 g dry weight, and therefore allow samples to be taken without trees having to be felled (Kube and Raymond, 2002;Raymond and Schimleck, 2002;Wallis et al, 1996). There are several methods to determine cellulose content in wood.…”

“…These focus mainly on two temperate eucalypt species, E. globulus and E. nitens (Apiolaza et al, 2005;Kube et al, 2001;Raymond and Schimleck, 2002;Schimleck et al, 2004), and Populus deltoides (Olson et al, 1985). Narrow-sense heritability of cellulose content is reported to be high, ranging from 0.32 to 1 (Apiolaza et al, 2005;Kube et al, 2001;Raymond and Schimleck, 2002;Schimleck et al, 2004), but the coefficient of additive genetic variation in one study was low (3%) (Apiolaza et al, 2005). Genetic gain in cellulose content from selecting the top 5% of the population, in studies by Kube et al (2001) and Schimleck et al (2004), was about 3-4% of the original population mean, with little effect on growth or wood density.…”