Locally weighted partial least-squares (LW-PLS) is an efficient just-in-time (JIT) modeling method, which can handle process collinearity, nonlinearity, and time-varying characteristics. However, i...

Fast Locally Weighted PLS Modeling for Large-Scale Industrial Processes

Mid infrared spectroscopy and milk quality traits: a data analysis competition at the "International Workshop on Spectroscopy and Chemometrics 2021"

Partial least squares regression (PLSR) is a reference method in chemometrics. In agronomy, it is used for instance to predict components of chemical composition (response variables y) of vegetal materials from spectral near infrared (NIR) data X collected from spectrometers. The principle of PLSR is to reduce the dimension of the spectral data X by computing vectors that are then used as latent variables (LVs) in a multiple linear model. A difficulty is to determine the relevant dimensionality (number of LVs) of the model for the given available data. This step can also become time consuming when many different datasets have to be processed and/or the datasets are frequently updated. An alternative to determinate the relevant PLSR dimensionality is the ensemble learning method “PLSR averaging”. In the past, this method has been demonstrated to be efficient for complex biological materials such as mixed forages, and facilitates to automatize predictions (e.g. in user-friendly web interface platforms). This article presents the extension of the PLSR averaging to a k-nearest neighbors locally weighted PLSR pipeline (kNN-LWPLSR). The kNN-LWPLSR pipeline has the advantage to account for non-linearity between X and y existing for instance in heterogeneous data (e.g. mixing of vegetal species, collection from different geographical areas, etc.). In the article, kNN-LWPLSR averaging is applied to an extensive NIR database built to predict the chemical composition of European and tropical forages and feed. The main finding of the study was the overall superiority of the averaging compared to the usual kNN-LWPLSR. Averaging may therefore be recommended in local PLSR pipelines to predict NIR forage and feed data. 

Averaging a local PLSR pipeline to predict chemical compositions and nutritive values of forages and feed from spectral near infrared data

A chemometric data analysis challenge has been arranged during the first edition of the "International Workshop on Spectroscopy and Chemometrics", organized by the Vistamilk SFI Research Centre and held online in April 2021. The aim of the competition was to build a calibration model in order to predict milk quality traits exploiting the information contained in mid-infrared spectra only. Three different traits have been provided, presenting heterogeneous degrees of prediction complexity thus possibly requiring trait-specific modelling choices. In this paper the different approaches adopted by the participants are outlined and the insights obtained from the analyses are critically discussed.

modeldatatoo: More Data Sets Useful for Modeling Examples

The applicability of vibrational spectroscopy and multivariate analysis for the characterization of animal feed where the reference values do not follow a normal distribution: A new chemometric challenge posed at the 'Chimiométrie 2019' congress

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

A. Laborde

Author Tools

Chat about Author

Papers

The applicability of vibrational spectroscopy and multivariate analysis for the characterization of animal feed where the reference values do not follow a normal distribution: A new chemometric challenge posed at the 'Chimiométrie 2019' congress