{'fraction_non_alphanumeric': 0.013358778625954198, 'fraction_numerical': 0.0, 'mean_word_length': 5.481481481481482, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Prediction of Cooking Time for Soaked and Unsoaked Dry Beans (Phaseolus vulgaris L.) Using Hyperspectral Imaging Technology

Hyperspectral imaging predicted water uptake and cooking time of dry bean from a single scan. Hyperspectral imaging has potential for estimating cooking time of soaked and unsoaked dry bean. Models succeeded for a broad set of cultivars with different cooking properties grown in diverse environments. Periodical updates with new accessions are critical to produce robust sensing calibration models.