Near infrared (NIR) spectroscopy as a rapid and cost-effective method for nutrient analysis of plant leaf tissues

Prananto, Jeremy Aditya; Minasny, Budiman; Weaver, T. B.

doi:10.1016/bs.agron.2020.06.001

Cited by 54 publications

(35 citation statements)

References 83 publications

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“…Whereas remote sensing applications must deal with issues of atmospheric correction, acquisition of NIR directly on the leaves is the preferred method of NIR spectroscopic analysis for plants. 25 , 26 The results obtained using the NIR spectra of dry, milled leaves were significantly better than those obtained using the NIR spectra of fresh leaves, due to the variable moisture content of the fresh leaves increasing the spectral variance. Previous studies proved that there is a strong water NIR absorption band in the region 1900–1950 nm, and this region is usually used for plant water content analysis.…”

Section: Discussionmentioning

confidence: 93%

Defining Eucalyptus urophylla with its hybrid and the rules of genetic recombination using near infrared spectroscopy

Arnold

ChuBiao

et al. 2021

Journal of Near Infrared Spectroscopy

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Understanding the rules of genetic recombination in controlled pollination directly related to the selection of parental genotypes and the utilization of heterosis, and genotype identification is a primary study of the genetic rules. The aims of this study were to investigate the ability of near infrared (NIR) spectroscopy to accurately and efficiently discriminate pure species and hybrids within the genus of Eucalyptus, to evaluate the transmission of genetic pedigree in control pollination, and reveal the genetic variation within the genotypes studied. NIR spectra were collected both from fresh leaves and dried, milled leaves of seedlings from pure species E. urophylla and E. grandis, and their F1 hybrids. Principal component analysis (PCA) scores plots of NIR spectra from fresh leaves and dry, milled powder from pure species showed clear segregation, although the species clusters were scattered, suggesting different base genetics and high genetic variation within families of the two pure species. Classification using soft independent modelling of class analogy of the NIR spectra of dried leaves was significantly better than using spectra acquired on fresh leaves, meaning the water content had an effect on the analysis. The projections and orthogonal distance between hybrids and parents, as calculated using PCA models, demonstrated the visualized spectral distance between each hybrid and the parents was very different. Clouds of individuals within a hybrid clusters varied from tightly packed to scattered, which reflected the genetic additive effects inherited from female and male parents were different, and their genetic variation was also different after genetic recombination. The varying response values for partial least squares discriminant analysis prediction verified the conclusions shown by projections and orthogonal distance. The results of this study demonstrate the potential of using NIR spectroscopy to rapidly discriminate taxon. The application of NIR spectroscopy to non-destructively confirm taxonomic identity will greatly facilitate the evaluation of the genetic basis and genetic variation available within breeding populations and for accessing the levels of contamination by non-target pollen in control pollination.

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Section: Discussionmentioning

confidence: 93%

Defining Eucalyptus urophylla with its hybrid and the rules of genetic recombination using near infrared spectroscopy

Arnold

ChuBiao

et al. 2021

Journal of Near Infrared Spectroscopy

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“…This method combines the generalised principal component analysis and multilinear regression [39]. It creates an orthogonal latent variable from the spectra and then identifies the relationship from the latent variables to the reference variables [40].…”

Section: Spectral Preprocessing and Calibration Models Developmentmentioning

confidence: 99%

Development of Calibration Models to Predict Mean Fibre Diameter in Llama (Lama glama) Fleeces with Near Infrared Spectroscopy

Amorena

Álvarez

Fernández-Ahumada

2021

Animals

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Llama fibre has the potential to become the most valuable textile resource in the Puna region of Argentina. In this study near infrared reflectance spectroscopy was evaluated to predict the mean fibre diameter in llama fleeces. Analyses between sets of carded and non-carded samples in combination with spectral preprocessing techniques were carried out and a total of 169 spectral signatures of llama samples in Vis and NIR ranges (400–2500 nm) were obtained. Spectral preprocessing consisted in wavelength selection (Vis–NIR, NIR and discrete ranges) and multiplicative and derivative pretreatments; spectra without pretreatments were also included, while modified partial least squares (M-PLS) regression was used to develop prediction models. Predictability was evaluated through R2: standard cross validation error (SECV), external validation error (SEV) and residual predictive value (RPD). A total of 54 calibration models were developed in which the best model (R2 = 0.67; SECV = 1.965; SEV = 2.235 and RPD = 1.91) was obtained in the Vis–NIR range applying the first derivative pretreatment. ANOVA analysis showed differences between carded and non-carded sets and the models obtained could be used in screening programs and contribute to valorisation of llama fibre and sustainable development of textile industry in the Puna territory of Catamarca. The data presented in this paper are a contribution to enhance the scarce information on this subject.

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“…The introduction of on-line and in-line approaches for feed ingredient evaluation based on (near) infrared spectroscopy has been a vast improvement in this respect. Several macronutrients can be well quantified in feed ingredients using near infrared spectroscopy ( Prananto et al, 2020 ), and the potential to quantify variation in digestibility of macronutrients or energy from near infrared spectra of fecal samples has been identified as promising ( Bastianelli et al, 2015 ; Nirea et al, 2018 ), particularly so for crude protein. The implied correlation of digestibility to complete near infrared spectra of feces rather than individual chemical entities, however, introduces risks for spurious associations.…”

Section: Introductionmentioning

confidence: 99%

ASAS-NANP symposium: digestion kinetics in pigs: the next step in feed evaluation and a ready-to-use modeling exercise

Gerrits

Schop

Vries

et al. 2021

Journal of Animal Science

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Growing importance of upcycling agricultural by-products, food waste, and food processing by-products through livestock production strongly increased the variation in the nutritional quality of feed ingredients. Traditionally, feed ingredients are evaluated based on their measured extent of digestion. Awareness increases that in addition to the extent, the kinetics of digestion affects the metabolic fate of nutrients after absorption. Together with a growing body of evidence of complex interactions occurring within the lumen of the digestive tract, this urges the need of developing new approaches for feed evaluation. In a recently developed approach, we propose combining in vitro and in silico methods for feed ingredient evaluation. First steps in the development of such a systems were made by (1) evaluating in vitro the digestion potential of feed ingredients, regarding this as true ingredient properties and (2) predicting in silico the digestive processes like digesta transit, nutrient hydrolysis and absorption using dynamic, mechanistic modeling. This approach allows to evaluate to what extent the digestion potential of each ingredient is exploited in the digestive tract. Future efforts should focus on modeling digesta physicochemical properties and transit, applying in vitro digestion kinetic data of feed ingredients in mechanistic models, and generating reliable in vivo data on nutrient absorption kinetics across feed ingredients. The dynamic modeling approach is illustrated by a description of a modeling exercise that can be used for teaching purposes in digestive physiology or animal nutrition courses. A complete set of equations is provided as an on-line supplement, and can be built in modeling software that is freely available. Alternatively, the model can be constructed using any modeling software that enables the use of numerical integration methods.

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Near infrared (NIR) spectroscopy as a rapid and cost-effective method for nutrient analysis of plant leaf tissues

Cited by 54 publications

References 83 publications

Defining Eucalyptus urophylla with its hybrid and the rules of genetic recombination using near infrared spectroscopy

Defining Eucalyptus urophylla with its hybrid and the rules of genetic recombination using near infrared spectroscopy

Development of Calibration Models to Predict Mean Fibre Diameter in Llama (Lama glama) Fleeces with Near Infrared Spectroscopy

ASAS-NANP symposium: digestion kinetics in pigs: the next step in feed evaluation and a ready-to-use modeling exercise

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