Near-infrared reflectance spectroscopy allows rapid and simultaneous evaluation of chloroplast pigments and antioxidants, carbon isotope discrimination and nitrogen content in Populus spp. leaves

Fernàndez-Martínez, Jordi; Joffre, Richard; Zacchini, Massimo; Fernández‐Marín, Beatriz; Garcı́a-Plazaola, José Ignacio; Fleck, Isabel

doi:10.1016/j.foreco.2017.05.041

Cited by 11 publications

(5 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…NIR spectroscopy quickly forecasts the chemical composition in a single measurement, solely from the spectral properties without further analyses, thereby making it unnecessary to carry out time-consuming and expensive biochemical analyses for each separate nutrient. 10 One of the goals of this study was to investigate the use of NIR spectroscopy to determine macro and micronutrient levels in teak seedlings and then verify the accuracy of these levels based on known values using wetlab results. The use of both a handheld and laboratory NIR spectrometers to accurately predict foliar levels of N, P, K, and B in teak seedlings will have great utility to teak growers working with this valuable species.…”

Section: Discussionmentioning

confidence: 99%

“…These results are comparable to those of nitrogen levels in Populus spp. leaves, 10 foliar potassium in white pine and red oak, 27 and nitrogen and phosphorus levels in red spruce and balsam fir. 28 Unfortunately, predictive models for the remaining macro and micronutrients using NIR were poor and will need further investigation to prove useful.…”

Section: Discussionmentioning

confidence: 99%

“…9 A calibration model based on the relationship between chemical measurements and spectral features using NIR spectroscopy is then utilized to determine the concentration of a particular organic constituent. 10 Utilizing spectral NIR data calibrated with wetlab foliar nutrient values predictive foliar nutrient models can be developed for crops of interest.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The use of near infrared spectroscopy to predict foliar nutrient levels of hydroponically grown teak seedlings

Whittier

Hodge

López

et al. 2021

Journal of Near Infrared Spectroscopy

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The use of near infrared spectroscopy to predict foliar nutrient levels of hydroponically grown teak seedlings

Whittier

Hodge

López

et al. 2021

Journal of Near Infrared Spectroscopy

View full text Add to dashboard Cite

show abstract

“…76 Studies have shown that there is a very high increase in reflectance during N starvation, which can reach 90% depending on the degree of deficiency. 21 , 72,77,78…”

Section: Resultsmentioning

confidence: 99%

Estimation of critical nitrogen contents in peach orchards using visible-near infrared spectral mixture analysis

Dedeoğlu

2020

Journal of Near Infrared Spectroscopy

View full text Add to dashboard Cite

The aim of this study was to predict the critical nitrogen (N) content in peach trees using spectrometric measurements. A nutrient-controlled hydroponics experiment was designed for this purpose. Peach saplings were grown under three N conditions: deficient, sufficient, and excessive. The reflectance values of a plant leaves were measured using a handheld field spectroradiometer fitted with a plant probe. The N contents of leaves were determined in the laboratory and Gaussian mixture discriminant analysis (GMDA) was used to estimate N levels in the leaves from reflectance values. The N levels were categorized for each of the three different N conditions. The wavelengths at 425 nm, 574 nm, 696 nm, and 700 nm were found to be diagnostic of the different N levels. The model developed here classified the experimental plants with high accuracy for NDeficient, 89.28%; NSufficient, 96.30%; and NExcess, 71.42% with 85.71% coefficients. The reliability of the model was also tested under field conditions using 96 peach trees representing the three different N status. Leaves were analyzed by reflectance at 425 nm, 574 nm, 696 nm, and 700 nm, which functioned in real N, percentage classes determined based on the laboratory analyses of the orchard samples, and the data were categorized as NDeficient, NSufficient, and NExcess with a similarity ratio of 77.78%, 80%, and 67.74%, respectively with the general correct classification rate of 75%. The study findings showed that the model developed using hyperspectral reflectance data can discriminate different N nutritional status in plants with an accuracy of ≥70% and can be applied under field conditions. The results of this research provide a new perspective for future studies by showing that GMDA with hyperspectral remote sensing may be useful for the classification of different plant nutrient contents.

show abstract

“…Other promising methods, spectroscopic data, and chemometric modeling have been proposed for the quantification of antioxidant compounds in wine [11,12], honey [13,14], coffee [15], dark soy sauce [16], roselle tea [17], olive oil [18], chocolate [19], apples [20], raw propolis [21], and Populus spp. leaves [22]. In most of these studies, a single technique has been used for prediction of antioxidants.…”

Section: Introductionmentioning

confidence: 99%

Data Fusion Approach Improves the Prediction of Single Phenolic Compounds in Honey: A Study of NIR and Raman Spectroscopies

Tahir¹,

Arslan²,

Mahunu³

et al. 2019

eFood

View full text Add to dashboard Cite

The combination of Near-Infrared Spectroscopy (NIR) and Raman Spectroscopy (RS) of 100 honey samples collected from different countries were used to develop the calibration model for determination of single phenolic compound. In highperformance liquid chromatography with diode-array detection analysis, 16 phenolic compounds were identified with p-hydroxybenzoic acid being the major compound detected in all honey samples. Thus, p-hydroxybenzoic acid was used for developing prediction models. Spectral data were modeled individually and using data fusion methodologies. The performance of the model based on RS spectra [ R p 2 = 0.9500, Root Mean Standard Error of Prediction (RMSEP) = 6.83] was higher than that based on the NIR spectra (R p 2 = 0.8147, RMSEP = 13.80). The application of both low-level (R p 2 = 0.9553, RMSEP = 6.59) and mid-level (R p 2 = 0.9563, RMSEP = 7.95) data fusion together with Partial Least Squares (PLS) had effectively improved the prediction models of NIR but did not enhance prediction models based on RS technique. The results demonstrated that the NIR, RS, and data fusion approaches together with the PLS model could be used as alternative quantitative methods for determination of p-hydroxybenzoic acid in honey samples.

show abstract

Near-infrared reflectance spectroscopy allows rapid and simultaneous evaluation of chloroplast pigments and antioxidants, carbon isotope discrimination and nitrogen content in Populus spp. leaves

Cited by 11 publications

References 63 publications

The use of near infrared spectroscopy to predict foliar nutrient levels of hydroponically grown teak seedlings

The use of near infrared spectroscopy to predict foliar nutrient levels of hydroponically grown teak seedlings

Estimation of critical nitrogen contents in peach orchards using visible-near infrared spectral mixture analysis

Data Fusion Approach Improves the Prediction of Single Phenolic Compounds in Honey: A Study of NIR and Raman Spectroscopies

Contact Info

Product

Resources

About