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Journal ArticleDOI

Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry

TLDR
In this paper, a multivariate calibration technique was used for the determination of moisture content (MC), total soluble solids (TSS), and acidity (expressed as pH) in strawberry images.
About
This article is published in Journal of Food Engineering.The article was published on 2007-07-01. It has received 413 citations till now. The article focuses on the topics: Partial least squares regression.

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Citations
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Hyperspectral imaging – an emerging process analytical tool for food quality and safety control

TL;DR: HSI equipment, image acquisition and processing are described; current limitations and likely future applications are discussed; and recent advances in the application of HSI to food safety and quality assessment are reviewed.
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Plant Disease Detection by Imaging Sensors - Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping.

TL;DR: The most relevant areas of application of sensor-based analyses are precision agriculture and plant phenotyping as discussed by the authors, which is facilitated by highly sophisticated and innovative methods of data analysis that lead to new insights derived from sensor data for complex plant-pathogen systems.
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Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part II: Applications

TL;DR: It is evident that hyperspectral imaging can automate a variety of routine inspection tasks and is anticipated that real-time food monitoring systems with this technique can be expected to meet the requirements of the modern industrial control and sorting systems in the near future.
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Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment

TL;DR: The different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products are explained, with details of the statistical techniques most commonly used for this task.
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LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements

TL;DR: In this paper, the utility of univariate techniques involving narrow band vegetation indices and the red edge inflection point, as well as multivariate calibration techniques, including stepwise multiple linear regression and partial least squares regression, was evaluated in a heterogeneous Mediterranean grassland from spectral reflectance measurements.
References
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Journal ArticleDOI

Partial least-squares regression: a tutorial

TL;DR: In this paper, a tutorial on the Partial Least Squares (PLS) regression method is provided, and an algorithm for a predictive PLS and some practical hints for its use are given.
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Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information

TL;DR: Partial least squares (PLS) as discussed by the authors is one of the most popular spectral analysis methods for spectral analysis, which is composed of a series of simpllfled classical least-squares (CLS) and ILS steps.
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Performance of some variable selection methods when multicollinearity is present

TL;DR: The nature of the VIP method is explored and it is compared with other methods through computer simulation experiments considering four factors–the proportion of the number of relevant predictor, the magnitude of correlations between predictors, the structure of regression coefficients, andThe magnitude of signal to noise.
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Image texture analysis: methods and comparisons

TL;DR: An overview of several different approaches to image texture analysis is provided and insight into their space/frequency decomposition behavior is used to show why they are generally considered to be state of the art in texture analysis.
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