Evolution of a novel sensing system for monitoring the quality deterioration in pearl millet (Pennisetum glaucum L.) grains coupled with rancidity indicators and GC-MS analysis: A potential cardinal approach

Abstract

Pearl millet (Pennisetum glaucum L.) is a nutri-cereal and a good source of energy, carbohydrate, protein, fat, vitamins, bioactive compounds, and minerals. Despite having superior nutritional profile compared to other cereal grains, the full potential of the pearl millet grain is limited due to its low shelf life owing to the development of rancidity during storage. In this study, a sensing system was developed to monitor the quality deterioration in pearl millet grains based on the volatile organic compounds (VOCs) evolved from the head space of the grains. The developed sensing system equipped with the metal oxide semiconductor (MOS) sensors and an algorithm to define rancidity index, successfully categorized the pearl millet grains into fresh (≤2.7), about to spoil (>2.7 to ≤ 2.9), and spoiled (>2.9), based on the volatile characteristics. The validation of the developed sensing system indicates a high concentration of alcohol (8.44 %) and aldehyde (3.54 %) compounds in the spoiled grain, followed by the about to spoil grain lots by GC-MS analysis and rancidity indicators (FFA, AV, PV). The higher R² (0.9711) and low error values (0.0014–1.0325) of the sensor data fitted with linear support vector machine (SVM) indicates the accuracy of the developed sensing system followed by linear regression and boosted trees. Timely monitoring of the spoilage in pearl millet grain can facilitate proper remedial measures and thereby extend the shelf life of the product. Because of its precision, convenience, and flexibility, the developed sensing system finds an efficient way for identifying whether the pearl millet grains are fresh or deteriorated.