Developing near infrared spectroscopy models for predicting chemistry and responses to stress in Pinus radiata (D. Don)

Abstract

Incorporating chemical traits in breeding requires the estimation of quantitative genetic parameters, especially the levels of additive genetic variation. This requires large numbers of samples from pedigreed populations. Conventional wet chemistry procedures for chemotyping are slow, expensive and not a practical option. This study focuses on the chemical variation in Pinus radiata, where the near infrared (NIR) spectral properties of the needles, bark and roots before and after exposure to methyl jasmonate (MJ) and artificial bark stripping (strip) treatments were investigated as an alternative approach. The aim was to test the capability of NIR spectroscopy to (i) discriminate samples exposed to MJ and strip assessed 7, 14, 21 and 28 days after treatment from untreated samples, and (ii) quantitatively predict individual chemical compounds in the three plant parts. Using principal components analysis (PCA) on the spectral data, we differentiated between treated and untreated samples for the individual plant parts. Based on partial least squares–discriminant analysis (PLS-DA) models, the best discrimination of treated from non-treated samples with the smallest root mean square error cross-validation (RMSECV) and highest coefficient of determination (r2) was achieved in the fresh needles (r2 = 0.81, RMSECV= 0.24) and fresh inner bark (r2 = 0.79, RMSECV = 0.25) for MJ-treated samples 14 days and 21 days after treatment, respectively. Using partial least squares regression, models for individual compounds gave high (r2), residual predictive deviation (RPD), lab to NIR error (PRL) or range error ratio (RER) for fructose (r2 = 0.84, RPD = 1.5, PRL = 0.71, RER = 7.25) and glucose (r2 = 0.83, RPD = 1.9, PRL = 1.14, RER = 8.50) and several diterpenoids. This provides an optimistic outlook for the use of NIR spectroscopy-based models for the larger-scale prediction of the P. radiata chemistry needed for quantitative genetic studies.

Genomic selection for resistance to mammalian bark stripping and associated chemical compounds in radiata pine

“…The chemical compounds in the bark, i.e. terpenes, phenolics, fatty acids, sugars, and unknown compounds, were predicted for the 6 protected replicates by near-infrared spectroscopy (NIRS) according to the methods documented in Nantongo, Potts, Rodemann et al (2021) and the associated wet chemistry methods documented in Nantongo, Potts, Davies, et al (2022) . In brief, chemical extractions were performed on 150 bark samples and NIRS prediction was used for the rest of the samples.…”

“…In radiata pine, selection for pest resistance has mostly been based on conventional approaches involving visual selection and trait screening over several pedigreed generations ( Carson 1989 ; Dungey et al 2009 ). Although there do not appear to be operational breeding programs focused on reducing the susceptibility of radiata pine to herbivory, various quantitative genetic studies have indicated the potential for selection against insects and mammalian bark damage and the associated chemical traits in various radiata pine populations ( Moreira et al 2013 ; Nantongo et al 2020 ; Nantongo, Potts, Davies, et al 2022 ; Nantongo et al 2021a ). However, estimates of the pedigree-based heritabilities (ranging from 0.07 to 0.50) and genetic correlations among marsupial bark stripping and associated chemical traits, which include terpenes, phenolics, and sugars, are usually low to moderate ( Nantongo et al 2020 , 2021a ), suggesting that these traits would possibly benefit from genomic selection.…”

“…Although there do not appear to be operational breeding programs focused on reducing the susceptibility of radiata pine to herbivory, various quantitative genetic studies have indicated the potential for selection against insects and mammalian bark damage and the associated chemical traits in various radiata pine populations ( Moreira et al 2013 ; Nantongo et al 2020 ; Nantongo, Potts, Davies, et al 2022 ; Nantongo et al 2021a ). However, estimates of the pedigree-based heritabilities (ranging from 0.07 to 0.50) and genetic correlations among marsupial bark stripping and associated chemical traits, which include terpenes, phenolics, and sugars, are usually low to moderate ( Nantongo et al 2020 , 2021a ), suggesting that these traits would possibly benefit from genomic selection. In conifer-herbivore systems, only one study has examined the potential benefits of genomic selection, in this case for white pine weevil resistance in Norway spruce ( Lenz et al 2020 ).…”

End‐user preferences to enhance prospects for varietal acceptance and adoption in potato breeding in Uganda

“…It has been used to assess a wide range of crop traits, including sensory traits and phytochemical variability and to predict nutrient levels in the tubers. [10][11][12] In potatoes, NIRS has predicted sensory texture attributes such as moistness, waxiness, firmness, and mealiness with correlation coefficients between 0.68 and 0.94. 13,14 However, in sub-Saharan Africa, the current literature on cooked potato provides little information regarding the power of instrument-based texture analysis and NIRS to differentiate among potato genotypes for consumer acceptability.…”

“…Near‐infrared spectroscopy is a nondestructive tool that can increase rapidly the speed at which quality traits are evaluated. It has been used to assess a wide range of crop traits, including sensory traits and phytochemical variability and to predict nutrient levels in the tubers 10‐12 . In potatoes, NIRS has predicted sensory texture attributes such as moistness, waxiness, firmness, and mealiness with correlation coefficients between 0.68 and 0.94 13,14 .…”