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- Shedding light on carob seeds: a non-destructive approach to assess Dehusking efficiency using diffuse reflectance spectroscopy and Kubelka–Munk theoryPublication . Guerra, Rui; Brazio, António; Gonçalves, Sandra; Romano, Anabela; Medronho, BrunoThe carob tree (Ceratonia siliqua L.) is receiving growing attention for its agro-industrial potential, particularly due to its seeds, which are the source of locust bean gum (LBG), a galactomannan-rich polysaccharide with wide applications in food and pharmaceutical industries. Efficient dehusking of carob seeds is critical to maximize LBG purity and yield, yet current industrial methods pose environmental concerns and lack robust quality control tools. In this study, we demonstrate the use of Diffuse Reflectance Spectroscopy (DRS) and Kubelka–Munk (KM) modeling as a rapid, non-destructive technique to assess dehusking efficiency. By combining spectral data from four complementary spectrometers (450–1800 nm), we identified key reflectance and absorbance features capable of distinguishing raw, industrially treated, and laboratory-dehusked seeds. Notably, our laboratory-treated seeds exhibited a considerably lower reflectance in the NIR plateau (800–1400 nm) compared to raw and industry-treated seeds, and their KM-reconstructed skin showed enhanced absorption bands at 960, 1200, and 1400 nm, consistent with more complete husk removal and improved light penetration. Principal Component Analysis revealed tighter clustering and lower variability in lab-processed seeds, indicating superior process reproducibility. These results establish DRS as a scalable, green analytical tool to support quality control and optimization in carob processing.
- Bridging the ESG data gap: transparent metrics and rankings for emerging financial marketsPublication . QACHACH, AZHAR RIM; El Mahrad, Badr; Kharbouch, Omar; Moumen, Aniss; Aoufi, Sara El; Gueddari, Manal El; Abdallah-Ou-Moussa, SoukainaEnvironmental, Social, and Governance (ESG) performance has become a pivotal driver of firm valuation, investment flows, and capital market stability and a critical dimension of corporate sustainability and investor decision-making. Yet, emerging markets face structural barriers to standardized ESG measurement due to limited data availability and inconsistent disclosures. This study addresses this gap by developing a simplified, transparent and indicator-based ESG assessment model tailored to the Moroccan capital market using publicly available data from 20 companies listed in the MASI ESG Index on the Casablanca Stock Exchange. The framework evaluates 12 equally weighted indicators across environmental, social, and governance pillars, and employs the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a Multi-Criteria Decision-Making (MCDM) method, to generate firm-level ESG scores and rankings. In addition to equal-weighted rankings, the model was stress-tested using entropy-based and expert-informed weights. Results reveal a wide disparity in ESG maturity: while environmental reporting is relatively advanced, social and governance disclosures lag behind. Top-ranking firms align closely with international frameworks such as GRI, whereas others lack fundamental transparency. By offering a replicable, low-data ESG scoring method applicable to other emerging markets, this research provides actionable insights for investors, regulators, and corporate leaders. The findings contribute to the financial literature on ESG integration, support the design of sustainable investment strategies, and advance policy efforts to strengthen capital market resilience across the MENA region.