南苏拉威西马洛斯县米糠品质的物理性质和化学成分评价

M. Ridla, Firdayanti Firdayanti, Erica B. Laconi, Nevyani Asikin
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引用次数: 0

摘要

米糠是稻米加工过程中产生的副产品,被广泛用作牲畜饲料原料。然而,米糠的质量在不同的生产区域可能有所不同。本研究旨在根据米糠的物理性质和预测的营养成分含量,对印度尼西亚南苏拉威西岛马洛斯地区的米糠质量进行评价。本研究采用完全随机设计,共10个处理(代表Bonto Marannu、Maccini Baji、Allepolea、Majannang、Salenrang、Turikale、Allatengae、Soreang、Baju Bodoa和tuunikamaseang的碾米厂)和4个重复。采用方差分析(ANOVA)和Duncan多重极差检验对数据进行分析。结果表明,碾米机位置对米糠物理品质和预测营养成分含量有极显著影响(P<0.01)。马罗斯区5个街道10个碾米厂的容重和抽穗密度差异极显著(P<0.01),粗蛋白质和粗纤维预测含量差异极显著(P<0.01)。以Allatengae磨的米糠最高,而Allepolea磨的米糠最低。在本研究中,根据米糠的物理质量和预测的营养成分含量,根据印尼国家标准(2013)将米糠的质量分为I、II、III级
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Rice Bran Quality Based on Physical Properties and Chemical Composition Estimation in Maros Regency, South Sulawesi
Rice bran, a byproduct generated during the rice milling process, is widely utilized as a livestock feed ingredient. However, the quality of rice bran can vary across different production regions. This study aimed to evaluate the quality of rice bran in Maros District, South Sulawesi, Indonesia, based on its physical properties and predicted nutrient contents. The study employed a completely randomized design, with ten treatments (representing rice mills from Bonto Marannu, Maccini Baji, Allepolea, Majannang, Salenrang, Turikale, Allatengae, Soreang, Baju Bodoa, and Tunikamaseang) and four replications. The data were analyzed using analysis of variance (ANOVA) and Duncan's multiple range test. The results revealed a highly significant effect (P<0.01) of the rice mill location on the physical quality and predicted nutrient contents of rice bran. The bulk density and tapped density densities varied (P<0.01) among the ten rice mills located in five sub-districts of Maros District, while the predicted crude protein and crude fiber contents also showed variation (P<0.01). The highest values were observed in the rice bran from the Allatengae mill, while the lowest values were found in the rice bran from the Allepolea mill. In this study, the quality of rice bran was categorized into grades I, II, and III according to Standard Nasional Indonesia (2013), based on its physical quality and predicted nutrient contents
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