Science AI Journal
Chemistry · Research topic

Open research questions in Spectroscopy and Chemometric Analyses

55 unresolved questions extracted from the limitations and future-work sections of 241 Spectroscopy and Chemometric Analyses papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Future developments are expected to focus on multimodal data fusion frameworks. Deep learning–based feature extraction and transfer learning–enabled model generalization are proposed for improving prediction accuracy and robustness.

    Comparative Evaluation of Hyperspectral, Thermal, and Near-Infrared Imaging Systems for Non-Destructive Prediction of Fruit and Vegetable Quality: A Review · 2026 · DOI

  • The gap in current research is the need for a comparative evaluation of hyperspectral, thermal, and near-infrared imaging systems for predicting physicochemical parameters.

    Comparative Evaluation of Hyperspectral, Thermal, and Near-Infrared Imaging Systems for Non-Destructive Prediction of Fruit and Vegetable Quality: A Review · 2026 · DOI

  • The complexity of non-thermal processes. The need for accurate monitoring and control of process parameters. The limited understanding of emerging trends such as nano-biosensors and artificial intelligence.

    Advances in non-thermal processing techniques and sensor-integration: real-time monitoring and control for food quality and safety · 2026 · DOI

  • The lack of precise monitoring and control systems for non-thermal food processing technologies. The need for advanced spectroscopic tools and emerging trends to enable intelligent control systems.

    Advances in non-thermal processing techniques and sensor-integration: real-time monitoring and control for food quality and safety · 2026 · DOI

  • Further research is needed to explore the potential of miniaturised NIR sensors for assessing milk components linked to metabolic stress indicators. The study suggests that miniaturised NIR sensors could be used in dairy farming.

    Miniaturised near-infrared spectroscopy for non-invasive assessment of de novo fatty acid concentrations in milk from individual cows · 2026 · DOI

  • The performance of miniaturised sensors for biologically meaningful markers remains underexplored. There is a need for a robust, cost-effective pathway for on-farm monitoring of milk components.

    Miniaturised near-infrared spectroscopy for non-invasive assessment of de novo fatty acid concentrations in milk from individual cows · 2026 · DOI

  • There is a need for non-destructive techniques to evaluate internal quality parameters of walnuts. The current methods for walnut kernel weight estimation have limitations in terms of accuracy and reliability.

    Comparative Modelling of Walnut Kernel Weight Using Non-Destructive Physical and Mechanical Measurements · 2026 · DOI

  • Poor image quality, handwritten labels, or non-standard fonts. Double labeling, where both the name and code of an additive are listed. The need for a system that can automatically determine the content of food additives and provide an assessment of potential health risks.

    Method for searching and analyzing e-additives and other components in food products of the population · 2026 · DOI

  • The use of machine learning models can be prone to bias and error. Edge deployment and validation in industrial settings can be challenging due to hardware constraints and latency budgets. The need for large amounts of labeled data for training and validation.

    Multimodal <scp>AI</scp> for Real‐Time Food Safety and Quality: From Sensors to Foundation Models, Edge Deployment, and Regulation · 2026 · DOI

  • Spectral noise and nonlinear relationships in spectral data. Limited generalization to field environments. Need for a non-destructive and accurate approach for maize seed quality assessment.

    Metaheuristic Optimized Fuzzy Ensemble for Maize Seed Quality Prediction Using Vis/NIR Spectroscopy · 2026 · DOI

  • More samples, especially more high-lignin references, would likely raise the scores. The study's results can be improved by using a larger and more independent dataset.

    Machine-learning prediction of biomass chemical composition using derivative thermogravimetric data of different biomass feedstocks · 2026 · DOI

  • Conventional methods for measuring biomass composition are time-consuming and laborious. There is a need for a quick and accurate method to predict biomass composition.

    Machine-learning prediction of biomass chemical composition using derivative thermogravimetric data of different biomass feedstocks · 2026 · DOI

  • Additional validation under field conditions is required before operational deployment. The framework can be extended to other crops and environments. The framework can be integrated with other sensors and technologies, such as unmanned aerial vehicles and satellite imaging.

    Coupling critical nitrogen dilution curve with hyperspectral feature optimization and machine learning for inversion of nitrogen nutrition index in greenhouse cucumber · 2026 · DOI

  • There is a need for rapid, non-destructive, and accurate diagnosis of nitrogen nutritional status in greenhouse cucumber production. Current methods are often destructive, time-consuming, and labor-intensive. There is a lack of integrated diagnostic frameworks that couple the agronomic critical nitrogen dilution curve with machine learning regression models.

    Coupling critical nitrogen dilution curve with hyperspectral feature optimization and machine learning for inversion of nitrogen nutrition index in greenhouse cucumber · 2026 · DOI

  • The need for real-time monitoring in industrial continuous bioprocesses. The complexity of chemometric tools, restricting adoption by non-specialists. The limitation of off-line analytics, which are slow and limit real-time decision-making.

    Development of a chemometric platform for mid-infrared fermentation monitoring · 2026 · DOI

  • Industrial bioprocess development still depends heavily on off-line analytics. Most applications rely on complex chemometric tools, restricting adoption by non-specialists.

    Development of a chemometric platform for mid-infrared fermentation monitoring · 2026 · DOI

  • The uncertainty quantification challenge for mixed-pixel conditions at medium resolution (30 m) satellite data remains inadequately addressed, despite the distance-based method demonstrating advantages in this specific scenario. Future research should develop and validate uncertainty estimation strategies tailored specifically to sub-pixel heterogeneity and mixed spectral signatures common in operational satellite monitoring for plant traits.

    Uncertainty Assessment in Deep Learning-based Plant Trait Retrievals from Hyperspectral data · 2026 · DOI

  • Distance-aware uncertainty methods that explicitly link training samples to out-of-distribution data have not been systematically extended beyond vegetation trait retrieval to other remote sensing applications. The scalability and adaptability of these distance-based approaches should be tested across diverse application domains where robustness under data shift is critical.

    Uncertainty Assessment in Deep Learning-based Plant Trait Retrievals from Hyperspectral data · 2026 · DOI

  • Although standard RGB imag- ing can distinguish red/yellow marrow and muscle from other whitish tissues, it provides limited information for interclass discrimination for a number of categories. Although the reddish appearance of muscle and marrow allows them to be visually separated from the other tissue types, this colour-based distinc- tion was insufficient to discriminate between muscle and marrow themselves.

    Advancing bovine tissue discrimination with Vis–NIR spectroscopy coupled with machine learning methods · 2026 · DOI

  • Existing analytical methods encounter difficulties due to excessive time required to analyze complicated data - Need for improved operational efficiency and analytical precision in pharmaceutical analysis

    ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN PHARMACEUTICAL ANALYSIS: RECENT ADVANCES IN METHOD DEVELOPMENT AND DATA INTERPRETATION · 2026 · DOI

  • The quality assessment of supramolecular complexes remains challenging. Techniques such as scanning electron microscopy and HPLC are typically cumbersome and time-consuming.

    Rapid evaluation of the comprehensive quality of paeonol/cyclodextrin supramolecular complexes using CASSA based on near-infrared spectroscopy combined with artificial intelligence · 2026 · DOI

  • The lack of a non-destructive method for classifying visually similar seed genotypes. The need for a method that can distinguish between different seed classes without supervision.

    Comparative classification of spectrally overlapping Allium seed genotypes using Vis–NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models · 2026 · DOI

  • Future studies can extend the use of PCR to other areas of animal science. Future studies can investigate the application of PCR in other breeds of chicken.

    Prediction of Albumen Index in Tinted Coral Chickens Eggs Using Principal Component Regression · 2026 · DOI

  • The use of PCR for predicting albumen quality remains limited. Most existing studies focus on different species or are based on relatively small sample sizes.

    Prediction of Albumen Index in Tinted Coral Chickens Eggs Using Principal Component Regression · 2026 · DOI

  • Further validation under practical industrial conditions is still required before real-time online implementation. The study suggests evaluating the robustness of the proposed method under different environmental conditions. The study suggests applying the proposed method to other food products and industries.

    Rapid and nondestructive quantitative detection of milk adulteration using hyperspectral imaging and optimized LSTM modeling · 2026 · DOI

Most-cited papers in Spectroscopy and Chemometric Analyses

Most recent work

Find a gap in your own Spectroscopy and Chemometric Analyses sub-topic

This page shows what the Spectroscopy and Chemometric Analyses literature already flags as unresolved. To narrow it to your specific question, run the guided finder — it searches the gap library on demand and checks candidates against 250M+ OpenAlex works.

Open the Research Gap Finder →

Related topics in Chemistry

Synthesis and biological activity
120 open questions
Various Chemistry Research Topics
105 open questions
Analytical Methods in Pharmaceuticals
90 open questions
Metal-Organic Frameworks: Synthesis and Applications
80 open questions
Advanced Proteomics Techniques and Applications
77 open questions
Click Chemistry and Applications
69 open questions
Analytical Chemistry and Chromatography
57 open questions
Edible Oils Quality and Analysis
47 open questions
55 open questions have been extracted from the limitations and future-work passages of 241 Spectroscopy and Chemometric Analyses papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

Tools for your next paper

Gaps & Literature SearchFind open questions in any field — 120,000+ open gaps mined from our own library.Pre-CheckIs your paper ready? A Tier 1–5 acceptance probability in seconds.Journal FinderA ranked shortlist of target journals from a 17,500-venue index.Duplicate Publication CheckerCheck prior-publication & salami-slicing risk across 8 sources.Citation GeneratorFreeA DOI or title → APA, MLA, Vancouver, Chicago, BibTeX, RIS. No signup.Graphical Abstract MakerFreeTurn your findings into a colorblind-safe graphical abstract.

Compare the category — Honest roundups of the AI research tools, ours listed alongside the alternatives.

Command palette

Jump anywhere, run any action.