Improvement of the functional value of green soybean (edamame) using germination and tempe fermentation: A comparative metabolomics study

Green soybean, also known as edamame, is a legume with high nutritional and functional value. Despite its growing popularity and potential health benefits, the functionality of green soybean has not been thoroughly studied. Previous research on the functionality of green soybean has largely focused on a limited number of specific, well-studied, bioactive metabolites, without comprehensively investigating the metabolome of this legume. Additionally, very few studies have explored the improvement of the functional value of green soybean. This study aimed to investigate the metabolome profile of green soybean, identify bioactive metabolites, and to further explore the potential improvement of the identified bioactive metabolites using germination and tempe fermentation. A total of 80 metabolites were annotated from green soybean using GC-MS and HPLC-PDA-MS. Among them, 16 important bioactive metabolites were identified: soy isoflavones daidzin, glycitin, genistin, malonyl daidzin, malonyl genistin, malonyl glycitin, acetyl daidzin, acetyl genistin, acetyl glycitin, daidzein, glycitein, and genistein, as well as other metabolites including 3,4-dihydroxybenzoic acid, 3-hydroxyanthranillic acid, 3-hydroxy-3-methylglutaric acid (meglutol), and 4-aminobutyric acid (GABA). Germination and tempe fermentation techniques were employed to potentially improve the concentrations of these bioactive metabolites. While showing improvements in amino acid contents, germination process did not improve bioactive metabolites significantly. In contrast, tempe fermentation was found to significantly increase the concentrations of daidzein, genistein, glycitein, acetyl genistin, acetyl daidzin, 3-hydroxyanthranillic acid, and meglutol (>2-fold increase with p < 0.05) while also improving amino acid levels. This study highlights the potentials of germination and fermentation to improve the functionality of legumes, particularly green soybean.

Physical and chemical properties of edamame during bean development and application of spectroscopy-based machine learning methods to predict optimal harvest time

This study aims to investigate the changes in physical and chemical properties of edamame during bean development and apply a spectroscopy-based machine learning (ML) technique to determine optimal harvest time. The edamame harvested at R5 (beginning seed), R6 (full seed), and R7 (beginning maturity) growth stages were characterized for physical and chemical properties, and pods were measured for spectral reflectance (360-740 nm) using a handheld spectrophotometer. The samples were categorized into 'early', 'ready', and 'late' based on the characterized properties. The results showed that pod/bean weight and pod thickness peaked at R6 and remained stable thereafter. Sugar, starch, alanine, and glycine also peaked at R6 but proceeded to decline. The ML method (random forest classification) using pods' spectral reflectance had a high accuracy of 0.95 for classifying 'early' and 'late' samples and 0.87 for classifying 'early' and 'ready' samples. Therefore, this method can determine the optimal harvest time of edamame.

Haematological profiles of Indonesian fat-tailed sheep under different physiological conditions

The aim of this research was to evaluate the effect of sex, age, feed and physiological conditions on the haematological profiles of Indonesian fat-tailed sheep. A total of 32 healthy Indonesian fat-tailed sheep in different physiological states (i.e. suckling lambs/weaners aged 1-5 months, postweaning lambs aged 6-8 months, lactating ewes, rams, and pregnant ewes) were used in this study. Blood samples were collected from the jugular vein and then transferred into tubes for haematological analysis. The results revealed the following: RBCs, 7.09 ± 0.52 million µL^-1; HCT, 46.76 ± 4.30%; Hb, 9.83 ± 0.57 g dL^-1; MCV, 69.88 ± 5.48 fL; MCH, 14.94 ± 0.71 pg; MCHC, 24.29 ± 1.36 g dL^-1; WBCs, 5.60 ± 1.24 thousand µL^-1; percentage of neutrophils, 58.30 ± 7.31%; percentage of lymphocytes, 41.63 ± 7.31%; and N/L ratio, 0.18 ± 0.05. The physiological status of the sheep affected RBCs, Hb, HCT and MCH (P < 0.05). The sex, age, feed and physiological status of the animals should be considered in the interpretation of haematological profiles in Indonesian fat-tailed sheep.

Effect of different drying techniques on drying kinetics, nutritional components, antioxidant capacity, physical properties and microstructure of edamame

The present study aimed to investigate the effect of hot air drying (HD), microwave rolling-bed drying (MRD), hot air microwave rolling-bed drying (HMRD), pulse-spouted microwave vacuum drying (PSMVD) and freeze-drying (FD) on the drying characteristics, quality properties and microstructure of edamame. Six models were fitted the drying curves, and quality attributes were analyzed. Results indicated that Page model was the most suited model for edamame drying. Compared with HD, MRD and HMRD improved the quality of edamame and decreased the drying time by 45.59% and 36.03% respectively. The FD and PSMVD possessed higher rehydration ability, nutrient retention and antioxidant capacity compared with other methods. Moreover, PSMVD products showed a crunchy texture, the less color change and the shortest drying time (70 min). Microscopy images demonstrated a distinct porous structure in PSMVD, which facilitated the moisture transfer. Overall, PSMVD is a promising dehydration method for obtaining high value-added edamame products.