Abstract

Due to a combination of durability, strength, and aesthetically pleasing color, teak (Tectona grandis L.f.) is globally regarded as a premier timber species. High value, in combination with comprehensive harvesting restrictions from natural populations, has resulted in extensive teak plantation establishment throughout the tropics and subtropics. Plantations directly depend on the production of healthy seedlings. In order to assist growers in efficiently diagnosing teak seedling nutrient issues, a hydroponic nutrient study was conducted at North Carolina State University. The ability to accurately diagnose nutrient disorders prior to the onset of visual symptoms through the use of near infrared (NIR) technology will allow growers to potentially remedy seedling issues before irreversible damage is done. This research utilized two different near infrared (NIR) spectrometers to develop predictive foliar nutrient models for 13 nutrients and then compared the accuracy of the models between the devices. Destructive leaf sampling and laboratory grade NIR spectroscopy scanning was compared to nondestructive sampling coupled with a handheld NIR device used in a greenhouse. Using traditional wet lab foliar analysis results for calibration, nutrient prediction models for nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), sulfur (S), copper (Cu), molybdenum (Mo), magnesium (Mg), boron (B), calcium (Ca), manganese (Mn), iron (Fe), sodium (Na), and zinc (Z) were developed using both NIR devices. Models developed using both techniques were good for N, P and K (R² > 0.80), while the B model was adequate only with the destructive sampling procedure. Models for the remaining nutrients were not suitable. Although destructive sampling and desktop scanning procedure generally produced models with higher correlations they required work and time for sample preparation that might reduce the value of this NIR approach. The results suggest that both destructive and nondestructive sampling NIR calibrations can be useful to monitor macro nutrient status of teak plants grown in a nursery environment.

© 2021 The Author(s)

Determination of the nutrient profile in plant materials using laser-induced breakdown spectroscopy with partial least squares-artificial neural network hybrid models

Ping Yang, Xiangyou Li, and Zhanglong Nie
Opt. Express 28(15) 23037-23047 (2020)

Nondestructive determination of SSC in an apple by using a portable near-infrared spectroscopy system

Yizhe Zhang, Jipeng Huang, Qiulei Zhang, Jinwei Liu, Yanli Meng, and Yan Yu
Appl. Opt. 61(12) 3419-3428 (2022)

Rapid detection of carbon-nitrogen ratio for anaerobic fermentation feedstocks using near-infrared spectroscopy combined with BiPLS and GSA

Jinming Liu, Nan Li, Feng Zhen, Yonghua Xu, Wenzhe Li, and Yong Sun
Appl. Opt. 58(18) 5090-5097 (2019)

Optical system for tablet variety discrimination using visible/near-infrared spectroscopy

Yongni Shao, Yong He, and Xingyue Hu
Appl. Opt. 46(34) 8379-8384 (2007)

Rapid detection of drought stress in plants using femtosecond laser-induced breakdown spectroscopy

Jeremy N. Kunz, Dmitri V. Voronine, Ho Wai Howard Lee, Alexei V. Sokolov, and Marlan O. Scully
Opt. Express 25(7) 7251-7262 (2017)