2021 article
The use of near infrared spectroscopy to predict foliar nutrient levels of hydroponically grown teak seedlings
Whittier, W. A., Hodge, G. R., Lopez, J., Saravitz, C., & Acosta, J. J. (2021, July 8). JOURNAL OF NEAR INFRARED SPECTROSCOPY.
author keywords: Tectona grandis; teak; near infrared spectroscopy; foliar nutrient; nitrogen; phosphorus; potassium
UN Sustainable Development Goal Categories
2. Zero Hunger
(Web of Science)
Source: Web Of Science
Added: July 26, 2021
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.