ReviewFrontiers in nutrition2022
Recent advancements in NIR spectroscopy for assessing the quality and safety of horticultural products: A comprehensive review.
Review in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Unleashing the power of visible-near infrared spectroscopy: predicting Golden Delicious apple enzyme activity.Journal of the science of food and agriculture · 2026Article
- The contribution of vibrational spectroscopy and data analytics towards the achievement of the global sustainability goals.Journal of the science of food and agriculture · 2026Review
- A homogeneity evaluation method of food soft matter based on moisture content test by casting-near-infrared spectroscopy.Food chemistry: X · 2025Article
- Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Food chemistry. Molecular sciences · 2025Article
- Hormonal Regulation of Avocado (Plant-environment interactions (Hoboken, N.J.) · 2025Article
- A Handheld IoT Vis/NIR Spectroscopic System to Assess the Soluble Solids Content of Wine Grapes.Sensors (Basel, Switzerland) · 2025Article
- Construction and optimization of quantitative analysis models for pigments in broccoli (Food chemistry: X · 2025Article
- The Role of Near-Infrared Spectroscopy in Food Quality Assurance: A Review of the Past Two Decades.Foods (Basel, Switzerland) · 2024Review
- Quantification of Lanthanides on a PMMA Microfluidic Device with Three Optical Pathlengths Using PCR of UV-Visible, NIR, and Raman Spectroscopy.ACS omega · 2024Article
- Development of a Measurement System Using Infrared Spectroscopy-Attenuated Total Reflectance, Principal Component Analysis and Artificial Intelligence for the Safe Quantification of the Nucleating Agent Sorbitol in Food Packaging.Foods (Basel, Switzerland) · 2024Article
- Statistics of maximum photon penetration depth in a two-layer diffusive medium.Biomedical optics express · 2024Article
- An Aquaphotomics Approach for Investigation of Water-Stress-Induced Changes in Maize Plants.Sensors (Basel, Switzerland) · 2023Article
- Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones.Plants (Basel, Switzerland) · 2023Article
- Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review.Foods (Basel, Switzerland) · 2023Review
- OpenVNT: An Open Platform for VIS-NIR Technology.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The qualitative and quantitative evaluation of agricultural products has often been carried out using traditional, i.e., destructive, techniques. Due to their inherent disadvantages, non-destructive methods that use near-infrared spectroscopy (NIRS) coupled with chemometrics could be useful for evaluating various agricultural products. Advancements in computational power, machine learning, regression models, artificial neural networks (ANN), and other predictive tools have made their way into NIRS, improving its potential to be a feasible alternative to destructive measurements. Moreover, the incorporation of suitable preprocessing techniques and wavelength selection methods has arguably proven its practical feasibility. This review focuses on the various computation methods used for processing the spectral data collected and discusses the potential applications of NIRS for evaluating the quality and safety of agricultural products. The challenges associated with this technology are also discussed, as well as potential future perspectives. We conclude that NIRS is a potentially useful tool for the rapid assessment of the quality and safety of agricultural products.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.