The evolution of chemometrics coupled with near infrared spectroscopy for fruit quality evaluation. II. The rise of convolutional neural networks

J Walsh, A Neupane, A Koirala, M Li… - Journal of Near Infrared …, 2023 - opg.optica.org
The Part 1 prequel to this review evaluated the evolution of modelling techniques used in
evaluation of fruit quality over the past three decades and noted a progression towards the …

Visible/near-infrared Spectroscopy and Hyperspectral Imaging Facilitate the Rapid Determination of Soluble Solids Content in Fruits

Y Zhao, L Zhou, W Wang, X Zhang, Q Gu, Y Zhu… - Food Engineering …, 2024 - Springer
Soluble solids content (SSC) is an essential internal quality attribute of fruits that directly
affects consumers' degree of satisfaction. The traditional determination method, the …

[HTML][HTML] Estimation of soluble solids content and fruit temperature in'Rocha'pear using Vis-NIR spectroscopy and the SpectraNet–32 deep learning architecture

JA Martins, D Rodrigues, AM Cavaco… - Postharvest Biology and …, 2023 - Elsevier
Spectra-based methods are becoming increasingly important in Precision Agriculture as
they offer non-destructive, quick tools for measuring the quality of produce. This study …

Hyperspectral model based on genetic algorithm and SA-1DCNN for predicting Chinese cabbage chlorophyll content

D Zhang, J Zhang, B Peng, T Wu, Z Jiao, Y Lu, G Li… - Scientia …, 2023 - Elsevier
Chinese cabbage (Brassica pekinensis L.) is a leafy green vegetable, which is widely grown
and consumed worldwide. Rapidly determining chlorophyll content is crucial for the effective …

1D-inception-resnet for NIR quantitative analysis and its transferability between different spectrometers

A Tan, Y Wang, Y Zhao, Y Zuo - Infrared Physics & Technology, 2023 - Elsevier
The development of portable near-infrared spectrometer has greatly enriched the Near
Infrared Spectroscopy (NIRS) applications. However, the well-built NIR quantitative model …

Near infrared spectroscopy quantification based on Bi-LSTM and transfer learning for new scenarios

A Tan, Y Wang, Y Zhao, B Wang, X Li… - Spectrochimica Acta Part A …, 2022 - Elsevier
This study proposed a deep transfer learning methodology based on an improved Bi-
directional Long Short-Term Memory (Bi-LSTM) network for the first time to address the near …

[HTML][HTML] Use of machine learning tools and NIR spectra to estimate residual moisture in freeze-dried products

A Massei, N Falco, D Fissore - Spectrochimica Acta Part A: Molecular and …, 2023 - Elsevier
Residual Moisture (RM) in freeze-dried products is one of the most important critical quality
attributes (CQAs) to monitor, since it affects the stability of the active pharmaceutical …

Recognizing the sweet and sour taste of pineapple fruits using residual networks and green-relative color transformation attached with Mask R-CNN

P Siricharoen, W Yomsatieankul, T Bunsri - Postharvest Biology and …, 2023 - Elsevier
The aromas and tastes produced by different chemical compounds in fruits are important
drivers of consumption, but they are difficult to discern from visual appearance alone. This …

NIR spectroscopy—CNN‐enabled chemometrics for multianalyte monitoring in microbial fermentation

S Banerjee, S Mandal, NG Jesubalan… - Biotechnology and …, 2024 - Wiley Online Library
As the biopharmaceutical industry looks to implement Industry 4.0, the need for rapid and
robust analytical characterization of analytes has become a pressing priority. Spectroscopic …

[HTML][HTML] Online Detection of Dry Matter in Potatoes Based on Visible Near-Infrared Transmission Spectroscopy Combined with 1D-CNN

Y Guo, L Zhang, Z Li, Y He, C Lv, Y Chen, H Lv, Z Du - Agriculture, 2024 - mdpi.com
More efficient resource utilization and increased crop utilization rate are needed to address
the growing demand for food. The efficient quality testing of key agricultural products such as …