Multivariate Calibration for Quantitative Analysis

Romía, Marcelo Blanco; Bernàrdez, Manel Alcalà

doi:10.1016/b978-0-12-374136-3.00003-1

Cited by 15 publications

(6 citation statements)

References 19 publications

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“…On the other hand, the lowest variations in the physicochemical parameters of MEF were observed for bulk density (~2.2 times), moisture content (~1.9 times), pH (~1.7 times), L* (~1.2 times) and h ab (~1.3 times) values. According to Blanco Romía & Alcalà Bernàrdez (2009), the calibration set should ideally encompass all possible sources of variability in the samples to be subsequently predicted.…”

Section: Resultsmentioning

confidence: 99%

Fast and non‐destructive determination of simultaneous physicochemical parameters of Manihot esculenta flour using FT‐NIR spectroscopy and multivariate analysis

Pompeu

Souza

Pena

2021

Int J of Food Sci Tech

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Manihot esculenta flour (MEF) is the main energetic source for a major part of the population in the Amazonian region. In this study, near-infrared spectroscopy (NIRS) was used, for the first time, to predict physicochemical parameters of MEF. The water activity (a W ), ash content, bulk density, moisture content, pH, geometric mean diameter (GMD) and colour parameters of L*, C * ab and h ab were determined for 106 samples of MEF. Calibration equations with independent validation were developed to predict all parameters using the partial least square regression method. The performance of models was evaluated by the root mean standard error of calibration (RMSEC) and validation (RMSEV), and R 2 values. The a W (RMSEC = RMSEV = 0.05), moisture content (RMSEC = 0.35%; RMSEV = 0.45%) and pH (RMSEC = 0.16; RMSEV = 0.18) could be predicted (R 2 > 0.727) by NIRS coupled to multivariate analysis. NIRS and multivariate analysis proved to be a powerful tool to predict multiple physicochemical parameters of MEF.

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Section: Resultsmentioning

confidence: 99%

Fast and non‐destructive determination of simultaneous physicochemical parameters of Manihot esculenta flour using FT‐NIR spectroscopy and multivariate analysis

Pompeu

Souza

Pena

2021

Int J of Food Sci Tech

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“…Ensuring the prediction accuracy of unknown samples requires a multi-step process: selecting a set of representative FT-MIR spectra, determining the property of interest using a reference method, choosing the calibration (3/4) and validation samples (1/4), performing the data pretreatment, applying the classification or quantification algorithm, and validating the model [ 58 , 71 ].…”

Section: Multivariate Analysismentioning

confidence: 99%

Uses of FT-MIR Spectroscopy and Multivariate Analysis in Quality Control of Coffee, Cocoa, and Commercially Important Spices

Castillejos-Mijangos

Acosta-Caudillo

Gallardo-Velázquez

et al. 2022

Foods

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Nowadays, coffee, cocoa, and spices have broad applications in the food and pharmaceutical industries due to their organoleptic and nutraceutical properties, which have turned them into products of great commercial demand. Consequently, these products are susceptible to fraud and adulteration, especially those sold at high prices, such as saffron, vanilla, and turmeric. This situation represents a major problem for industries and consumers’ health. Implementing analytical techniques, i.e., Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with multivariate analysis, can ensure the authenticity and quality of these products since these provide unique information on food matrices. The present review addresses FT-MIR spectroscopy and multivariate analysis application on coffee, cocoa, and spices authentication and quality control, revealing their potential use and elucidating areas of opportunity for future research.

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“…As a result, seed mass and germination timings are now amenable to non-invasive, automated and high-throughput phenotyping. NIR spectroscopy enables large scale studies on seeds and allows the quantification of water, protein, oil, starch and other potential compounds [57]. Further, to dissect macroscopic traits, MRI and X-ray computerized tomography techniques can be employed [58].…”

Section: Seedling Vigourmentioning

confidence: 99%

Using Plant Phenomics to Exploit the Gains of Genomics

et al. 2019

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Agricultural scientists face the dual challenge of breeding input-responsive, widely adoptable and climate-resilient varieties of crop plants and developing such varieties at a faster pace. Integrating the gains of genomics with modern-day phenomics will lead to increased breeding efficiency which in turn offers great promise to develop such varieties rapidly. Plant phenotyping techniques have impressively evolved during the last two decades. The low-cost, automated and semi-automated methods for data acquisition, storage and analysis are now available which allow precise quantitative analysis of plant structure and function; and genetic dissection of complex traits. Appropriate plant types can now be quickly developed that respond favorably to low input and resource-limited environments and address the challenges of subsistence agriculture. The present review focuses on the need of systematic, rapid, minimal invasive and low-cost plant phenotyping. It also discusses its evolution to modern day high throughput phenotyping (HTP), traits amenable to HTP, integration of HTP with genomics and the scope of utilizing these tools for crop improvement.

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Multivariate Calibration for Quantitative Analysis

Cited by 15 publications

References 19 publications

Fast and non‐destructive determination of simultaneous physicochemical parameters of Manihot esculenta flour using FT‐NIR spectroscopy and multivariate analysis

Fast and non‐destructive determination of simultaneous physicochemical parameters of Manihot esculenta flour using FT‐NIR spectroscopy and multivariate analysis

Uses of FT-MIR Spectroscopy and Multivariate Analysis in Quality Control of Coffee, Cocoa, and Commercially Important Spices

Using Plant Phenomics to Exploit the Gains of Genomics

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