Applications of Near-Infrared Spectroscopy (NIRS) in Fish Value Chain

Nieto-Ortega, Sonia; Lara, Rebeca; Foti, Giuseppe; Herreros, Ángela Melado; Olabarrieta, Idoia

doi:10.5772/intechopen.105736

Cited by 4 publications

(3 citation statements)

References 85 publications

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“…In recent years, there has been an exploration of the application of NIRS to recognize different fishery species [16,19]. However, to date, research on species identification utilizing NIRS has predominantly focused on species within the Teleost infraclass.…”

Section: Classification By Speciesmentioning

confidence: 99%

Cuttlefish Species Authentication: Advancing Label Control through Near-Infrared Spectroscopy as Rapid, Eco-Friendly, and Robust Approach

Currò

Balzan

Novelli

et al. 2023

Foods

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Accurate species identification, especially in the fishery sector, is critical for ensuring food safety, consumer protection and to prevent economic losses. In this study, a total of 93 individual frozen–thawed cuttlefish samples from four different species (S. officinalis, S. bertheloti, S. aculeata, and Sepiella inermis) were collected from two wholesale fish plants in Chioggia, Italy. Species identification was carried out by inspection through morphological features using dichotomic keys and then through near-infrared spectroscopy (NIRS) measurements. The NIRS data were collected using a handled-portable spectrophotometer, and the spectral range scanned was from 900–1680 nm. The collected spectra were processed using principal component analysis for unsupervised analysis and a support vector machine for supervised analysis to evaluate the species identification capability. The results showed that NIRS classification had a high overall accuracy of 93% in identifying the cuttlefish species. This finding highlights the robustness and effectiveness of spectral analysis as a tool for species identification, even in complex spatial contexts. The findings emphasize the potential of NIRS as a valuable tool in the field of fishery product authentication, offering a rapid and eco-friendly approach to species identification in the post-processing stages.

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Section: Classification By Speciesmentioning

confidence: 99%

Cuttlefish Species Authentication: Advancing Label Control through Near-Infrared Spectroscopy as Rapid, Eco-Friendly, and Robust Approach

Currò

Balzan

Novelli

et al. 2023

Foods

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“…Studies have shown that techniques such as machine vision and NIR spectroscopy achieve promising results in accuracy and rapidity. Nieto-Ortega et al [ 28 ] summarized the application of near-infrared spectroscopy in the fish value chain—proximate composition, freshness, species identification, farmed vs. wild fish and types of farming, geographical origin, unfrozen vs. frozen–thawed fish, fish safety, etc. The purpose of the present study was to determine the suitability of NIR spectroscopy for the rapid, cheap, and non-destructive detection of fresh and freeze–thawed fish and propose a classification model for applications in routine fish control.…”

Section: Introductionmentioning

confidence: 99%

Near-Infrared Spectroscopy for Rapid Differentiation of Fresh and Frozen–Thawed Common Carp (Cyprinus carpio)

Atanassova,

Yorgov,

Stratev

et al. 2024

Sensors

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This study aimed to investigate near-infrared spectroscopy (NIRS) in combination with classification methods for the discrimination of fresh and once- or twice-freeze–thawed fish. An experiment was carried out with common carp (Cyprinus carpio). From each fish, test pieces were cut from the dorsal and ventral regions and measured from the skin side as fresh, after single freezing at minus 18 °C for 15 ÷ 28 days and 15 ÷ 21 days for the second freezing after the freeze–thawing cycle. NIRS measurements were performed via a NIRQuest 512 spectrometer at the region of 900–1700 nm in Reflection mode. The Pirouette 4.5 software was used for data processing. SIMCA and PLS-DA models were developed for classification, and their performance was estimated using the F1 score and total accuracy. The predictive power of each model was evaluated for fish samples in the fresh, single-freezing, and second-freezing classes. Additionally, aquagrams were calculated. Differences in the spectra between fresh and frozen samples were observed. They might be assigned mainly to the O–H and N–H bands. The aquagrams confirmed changes in water organization in the fish samples due to freezing–thawing. The total accuracy of the SIMCA models for the dorsal samples was 98.23% for the calibration set and 90.55% for the validation set. For the ventral samples, respective values were 99.28 and 79.70%. Similar accuracy was found for the PLS-PA models. The NIR spectroscopy and tested classification methods have a potential for nondestructively discriminating fresh from frozen–thawed fish in as methods to protect against fish meat food fraud.

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“…Near infrared spectroscopy (NIRS) associated with chemometric techniques has been applied in agriculture for a long time (Pasquini, 2003;Nieto-Ortega et al, 2023). The main applications involve quality analysis and characterization of foods and soils (Cunha Júnior et al, 2015;Li at al., 2020;Sohn et al, 2021).…”

Section: Introduction Introduction Introduction Introductionmentioning

confidence: 99%

NIRS and multivariate methods for discrimination of morning glory species at different growth stages

BRAGA,

De CARVALHO,

CORREA da SILVA

et al. 2023

Not Bot Horti Agrobo

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Morning glory species are weeds very common in tropical crops, where they cause direct and indirect damage. The management of these species primarily relies on the application of herbicides, disregarding the growth stage and spatial distribution. Studies addressing new techniques for identifying these species may contribute to the development of proximal sensors for carrying out specific and rational management. Thus, the objective of this work was to use near infrared spectroscopy (NIRS) and multivariate analysis to discriminate two species of morning glory in three growth stages. NIRS spectra were collected from Ipomoea hederifolia and Merremia aegyptia were collected at three different stages in the spectral range of 4.000 to 10.000 cm-1. PCA and PC-LDA were used to analyze the entire spectrum and specific bands. NIRS associated with PCA and PC-LDA were sufficient to discriminate I. hederifolia and M. aegyptia species and their growth stages. PCA allowed a proper segregation of stages and species when applied individually PC-LDA correctly classified between 90.93 to 100% of species and stages. The best discrimination results were observed in the NIR spectra ranges from 4.500 to 6.000 cm-1 and 4.500 to 6.000 + 6.500 to 7.750 cm-1. This study represents an advance in the research and implementation of NIRS technology to discriminate weed species for the future development of equipment to assist in the adoption and/or performance of a specific management of weeds, capable of contributing to the reduction in the use of herbicides in crops.

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Applications of Near-Infrared Spectroscopy (NIRS) in Fish Value Chain

Cited by 4 publications

References 85 publications

Cuttlefish Species Authentication: Advancing Label Control through Near-Infrared Spectroscopy as Rapid, Eco-Friendly, and Robust Approach

Cuttlefish Species Authentication: Advancing Label Control through Near-Infrared Spectroscopy as Rapid, Eco-Friendly, and Robust Approach

Near-Infrared Spectroscopy for Rapid Differentiation of Fresh and Frozen–Thawed Common Carp (Cyprinus carpio)

NIRS and multivariate methods for discrimination of morning glory species at different growth stages

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