Prevention effects of black soybean polyphenols on non-alcoholic fatty liver disease in three different model mice

Non-alcoholic fatty liver disease (NAFLD) and its advanced stage, non-alcoholic steatohepatitis (NASH) are a major health issue throughout the world. Certain food components such as polyphenols are expected to possess...

Sensory evaluation and antimicrobial activity of snack bar from black soybean and black rice containing anthocyanins

Snack bars made from black soybean and black rice could be used as a food product to complement the energy and nutrients needs. Both have anthocyanins content in black soybean and black rice as well as the potential as an antimicrobial agent. The purpose of this study was to obtain an optimal formula, evaluate the sensory acceptance, analyze the total monomeric anthocyanin content of the snack bars, and compare the growth of probiotic and pathogenic bacteria in anthocyanins crude extracts from the snack bars. The production of snack bars was done by using three variations of main ingredients, including 30% of black soybean + 70% of black rice (formula 1), 50% of black soybean + 50% of black rice (formula 2), and 70% of black soybean + 30% of black rice (formula 3). The results performed that consumers acceptance for formulas 2 and 3 was not significantly different (P > 0.05), but significantly higher (P < 0.05) than formula 1. Total monomeric anthocyanin content analyzed by the pH differential method in these three snack bars formulas had no significant difference (P > 0.05). The growth analysis of probiotic and pathogenic bacteria showed that the percentage of growth inhibition of Escherichia coli and Salmonella enterica serovar Typhi bacteria was significantly higher (P = 0.00) compared to Lactobacillus acidophilus. Also, formulas 1 and 2 could significantly inhibit E. coli and S. enterica ser. Typhi bacteria (P = 0.00) compared to formula 3. It could be concluded that formula 2 showed the best snack bar based on sensory evaluation and pathogenic bacteria inhibition assay.

Growth and Yield of Soybean on Various Types and Concentrations of Liquid Organic Fertilizer in Ultisols

The application of a wed-based liquid organic fertilizer can increase the production of black soybeans (Glycine Max L. Merril). The study aimed to identify the best source and dose of liquid organic fertilizer (LOF) for black soybean growth and yield. The researchers used a three-times-repeated Completely Randomized Design (CRD) using a factorial layout. The first factor was the source of LOF, which included Siam weed (Chromolaena odorata, L.), Goat weed (Ageratum conyzoides L.), and yellow creeping daisy (Wedelia trilobata L.). The second factor was the concentration of weed-based LOF, consisted of water (control treatment); 12 ml/L; 16 ml/L; 20 ml/L. The results of the study show, weed-based LOF, namely LOF Yellow creeping daisy, Goat weed, and Siam weed, resulted in no significant difference in the growth and yield of the black soybean. Except for the variables of root fresh weight and number of pods per plant, the variation in concentration of weed-based liquid organic fertilizer had no significant effect on plant growth and yield.

Mega-Environment Analysis and Identify Stable and High-Yielding of New Promising Black Soybean Lines in Indonesia

Stable and high-yielding are the major goals of black soybean breeding. Testing new lines in a mega-environment is one of the development processes in black soybean breeding. The aims of the research were (i) to identify the effects of genotype, environment, and GEIs on the grain yield of soybean lines in Java Island; (ii) to select stable and high yielding soybean lines; and (iii) to determine the discriminative environments, and (iv) to determine the concept of stability measurements on black soybean grain yields. Field trials of 10 new F8 promising lines and three check varieties were conducted under eight different environments during four years (2016–2019). The measurement results showed that the grain yield was influenced by genotype (8.35%), environment (59.49%), and GEIs (32.16%). Grain yield stability measurements showed that the four newly lines was identified had high yields and stable in eight environments, they were A-5A-PSJ (S2), DB-96-CTY (S5), UP 161 (S6), and UP 162 (S7). The Ngawi (2017) followed by Bogor (2019) and Banyuwangi (2016) has the strongest interactive capabilities, and was suitable for used as a trial environments. Grain yield (Y) was identified as having a positive and significant correlation (p < 0.05) with S(3), S(6), NP(2), NP(3), NP(4), KR, and YSI stability measurements, which indicated that they were included in the concept of dynamic stability measurement.