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Potential of near infrared spectroscopy to monitor variations in soluble sugars in Loblolly pine seedlings after cold acclimation.

Authors :
Zhao, Xiping
Hui, Bin
Hu, Lixia
Cheng, Qingzheng
Via, Brian K.
Nadel, Ryan
Starkey, Tom
Enebak, Scott
Source :
Agricultural & Forest Meteorology. Jan2017, Vol. 232, p536-542. 7p.
Publication Year :
2017

Abstract

The freeze tolerance of seedlings can be affected by cold acclimation. This acclimation can in turn alter the seedlings absorbance spectra due to variation of soluble sugar content (SSC). If models developed from the absorbance at wavelengths in the near infrared reflectance (NIR) region could provide information concerning the variation in SSC, nursery managers could assess the freeze tolerance of each seedling before planting. The objective of this research was to investigate the potential to use NIR based analysis to study the variation of SSC in Loblolly pine ( Pinus taeda L.) seedlings after cold acclimation. Seventy seedlings were frozen using different cold treatments and 10 seedlings were designated as controls. The standard wet chemistry method was employed to collect the original SSC data, including glucose, fructose and galactose. NIR spectroscopy was completed by using a NIR machine, with a range of 10,000–4000 cm −1 . The results were analyzed using partial least squares regression in an effort to determine the SSC in the leaves, stems and roots. Results showed that the freeze tolerance of seedlings increased after cold acclimation and was positively related to the presence of SSC. After cold acclimation, leaves had the most SSC, and the galactose content was more than that of glucose or fructose in seedlings. Based on the determination coefficient (R 2 ) and the residual predictive deviation (RPD), the predicted results of NIR models were evaluated. The model for leaf galactose (R 2 = 0.88 and RPD = 2.17) was the most stable and accurate model. This paper demonstrates that NIR coupled with chemometric modeling can be a useful tool in the monitoring of SSC variation and this information could be useful in the prediction of freeze tolerance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01681923
Volume :
232
Database :
Academic Search Index
Journal :
Agricultural & Forest Meteorology
Publication Type :
Academic Journal
Accession number :
119651285
Full Text :
https://doi.org/10.1016/j.agrformet.2016.10.012