[1]逯紫妍,黄璐,袁晓天,等.鲜食大豆可溶性糖组分快速检测方法[J].江苏农业学报,2026,42(08):1671-1678.[doi:doi:10.3969/j.issn.1000-4440.2026.08.016]
　LU Ziyan,HUANG Lu,YUAN Xiaotian,et al.A rapid detection method for soluble sugar components in vegetable soybeans[J].,2026,42(08):1671-1678.[doi:doi:10.3969/j.issn.1000-4440.2026.08.016]
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鲜食大豆可溶性糖组分快速检测方法()

江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
42
期数:
2026年08期
页码:
1671-1678
栏目:
加工贮藏·质量安全
出版日期:
2026-08-31

文章信息/Info

Title:
A rapid detection method for soluble sugar components in vegetable soybeans
作者:
逯紫妍1; 黄璐2; 袁晓天3; 王侃3; 梁文香4; 张晓燕2; 袁星星2; 陈新2; 薛晨晨2
(1.江苏大学食品科学与工程学院,江苏镇江212013；2.江苏省农业科学院经济作物研究所,江苏南京210014；3.南京财经大学食品科学与工程学院,江苏南京210095；4.淮阴工学院计算机与软件工程学院,江苏淮安223001)
Author(s):
LU Ziyan1; HUANG Lu2; YUAN Xiaotian3; WANG Kan3; LIANG Wenxiang4; ZHANG Xiaoyan2; YUAN Xingxing2; CHEN Xin2; XUE Chenchen2
(1.School of Food Science and Engineering, Jiangsu University, Zhenjiang 212013, China;2.Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China;3.College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210095, China;4.School of Computer and Software Engineering, Huaiyin Institute of Technology, Huai’an 223001, China)
关键词:
鲜食大豆; 可溶性糖组分; 快速检测; 近红外光谱; 偏最小二乘法
Keywords:
vegetable soybean; soluble sugar components; rapid detection; near-infrared spectroscopy; partial least squares method
分类号:
S565.1
DOI:
doi:10.3969/j.issn.1000-4440.2026.08.016
文献标志码:
A
摘要:
为实现鲜食大豆可溶性糖组分的快速检测,本研究以150份鲜食大豆资源为材料,采集12 500～4 000 cm-1波数范围内的近红外光谱,结合高效液相色谱法(HPLC)测定的可溶性糖组分含量,基于偏最小二乘法(PLS)构建鲜食大豆可溶性糖组分含量的检测模型。结果表明,150份鲜食大豆总可溶性糖含量、蔗糖含量、葡萄糖含量、果糖含量、棉子糖含量和水苏糖含量分别为22.73～83.08 mg/g、17.18～71.55 mg/g、0.82～2.60 mg/g、0.66～1.79 mg/g、未检出～3.09 mg/g和未检出～2.35 mg/g。在验证集上,PLS法构建的大豆可溶性糖组分含量检测模型对总可溶性糖含量与蔗糖含量的预测决定系数分别为0.900 5和0.810 4,对果糖含量、葡萄糖含量、棉子糖含量及水苏糖含量的预测决定系数分别为0.811 1、0.837 1、0.806 4、0.803 6。本研究建立了鲜食大豆糖组分的快速检测方法,为高糖优质品种的快速筛选与育种提供了技术支撑。
Abstract:
To realize the rapid detection of soluble sugar components in fresh soybean, 150 vegetable soybean resources were used as materials in this study. The near-infrared spectra within the range of 12 500-4 000 cm-1 were collected, and the content of soluble sugar components was determined by high performance liquid chromatography (HPLC). The detection model of soluble sugar components in vegetable soybean was constructed based on partial least squares (PLS). The results showed that the total soluble sugar content, sucrose content, glucose content, fructose content, raffinose content and stachyose content of 150 vegetable soybeans were 22.73-83.08 mg/g, 17.18-71.55 mg/g, 0.82-2.60 mg/g, 0.66-1.79 mg/g, not detected to 3.09 mg/g and not detected to 2.35 mg/g, respectively. On the validation set, the coefficients of determination for prediction of the total soluble sugar content and sucrose content by PLS method-based model for determining soybean soluble sugar component content were 0.900 5 and 0.810 4, respectively. The coefficients of determination for prediction of the fructose content, glucose content, raffinose content and stachyose content were 0.811 1, 0.837 1, 0.806 4 and 0.803 6, respectively. In this study, a rapid detection method for sugar components in vegetable soybean was established, which provided technical support for rapid screening and breeding of high-sugar and high-quality varieties method.

参考文献/References:

[1]张秋英,李彦生,杜明,等. 菜用大豆食用品质及调控[C]//中国作物学会大豆专业委员会. 第24届全国大豆科研生产研讨会论文集. 银川:中国作物学会大豆专业委员会,2014:86.
[2]陈四维,钟文娟,廖蕤,等. 四川菜用大豆产业发展现状及对策[J]. 中国种业,2024(11):8-13.
[3]张诗琦,黄璐,程茜,等. 不同播期对鲜食大豆品质的影响[J]. 园艺学报,2025,52(1):213-228.
[4]卜远鹏,刘娜,张古文,等. 菜用大豆种质资源的农艺性状多样性评价及核心种质与食味品质评价体系的构建[J]. 浙江农业学报,2023,35(6):1307-1314.
[5]Ishimaru K, Hirotsu N, Kashiwagi T, et al. Overexpression of a maize SPS gene improves yield characters of potato under field conditions[J]. Plant Production Science,2008,11(1):104-107.
[6]张玉梅,丁文涛,蓝新隆,等. 大豆地方种质资源鲜籽粒可溶性糖含量的全基因组关联分析[J]. 中国农业科学,2024,57(11):2079-2091.
[7]黄美. 我国大豆地方品种群体籽粒可溶性糖含量的遗传变异和QTL关联定位研究[D]. 南京:南京农业大学,2012.
[8]Zhang Q Y, Li Y S, Chin K L, et al. Vegetable soybean:seed composition and production research[J]. Italian Journal of Agronomy,2017,12(3):872.
[9]李兵,肖香兰,杨永红,等. 国内外淀粉含量的检测标准现状及检测方法研究进展[J]. 食品安全质量检测学报,2021,12(9):3830-3839.
[10]程茜,黄璐,沈旭,等. 基于电子舌和人工感官评价的菜用大豆食用品质特性分析[J]. 江苏农业科学,2023,51(7):161-167.
[11]丁雪梅,张晓君,赵云,等. 蒽酮比色法测定可溶性糖含量的试验方法改进[J]. 黑龙江畜牧兽医,2014(23):230-233.
[12]李晓旭,李家政. 优化蒽酮比色法测定甜玉米中可溶性糖的含量[J]. 保鲜与加工,2013,13(4):24-27.
[13]沈诗钰,孙威江,唐琴,等. 基于近红外光谱技术的白茶可溶性糖总量快速测定研究[J]. 天然产物研究与开发,2019,31(1):16-23.
[14]康玉民,杨振,顾丛丛. 近红外光谱技术在食品检测中的应用研究[J]. 食品安全导刊,2025(16):155-157.
[15]李博,朱莉,姚庆宇,等. 基于近红外光谱的草莓多品质参数通用预测模型研究[J]. 现代食品科技,2025,41(8):227-236.
[16]吴琪,陈孝敬,石文,等. 结合近红外光谱和模型更新的苹果品质无损检测[J]. 分析测试学报,2025,44(6):1154-1160.
[17]程维民. 基于近红外光谱的单粒水稻理化特性与食味品质关联性研究[D]. 合肥:中国科学技术大学,2023.
[18]杨光辉,张永立,王美蟠,等. 近红外光谱检测鲜食玉米可溶性固形物含量[J]. 光谱学与光谱分析,2025,45(7):1932-1939.
[19]李文君,雷荣,曾艳,等. 基于近红外光谱技术的不同种皮色大豆种子活力预测模型的构建[J]. 中国油料作物学报,2025,47(4):1051-1064.
[20]李基业,张博,谷子丰,等. 近红外光谱技术快速预测大豆中主要抗营养因子含量[J]. 中国畜牧杂志,2024,60(12):344-348.
[21]余新金,熊倩,甘蓓,等. 有机与非有机大豆的营养成分分析及近红外鉴别[J]. 食品安全质量检测学报,2023,14(7):139-147.
[22]温冰消,刘卫国,李虹桥,等. 基于近红外法的鲜食大豆品质快速分析技术[J]. 分子植物育种,2018,16(12):4062-4067.
[23]郭鲁平,黄璐,程茜,等. 江苏省春播鲜食大豆主栽品种营养和功能品质研究[J]. 大豆科学,2023,42(1):91-98.
[24]Nicola B M,Beullens K,Bobelyn E,et al. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy:a review[J]. Postharvest Biology and Technology,2007,46(2):99-118.
[25]杨哲萱,周立红,章顺楠,等. NIRS技术在中药生产中的应用及其验证方法探讨[J]. 中草药,2013,44(10):1342-1348.
[26]王骏超,葛俊锋. NIRS数据样本选择与预处理方法综述[J]. 国外电子测量技术,2019,38(3):1-7.
[27]Fazeli Burestan N, Afkari Sayyah A H, Taghinezhad E. Prediction of some quality properties of rice and its flour by near-infrared spectroscopy (NIRS) analysis[J]. Food Science & Nutrition,2021,9(2):1099-1105.
[28]Fearn T. Assessing calibrations:SEP,RPD,RER and R2[J]. NIR News,2002,13(6):12-13.
[29]姜春姣,李进,孙昊杰,等. 基于相同化学值分设备构建花生蔗糖近红外模型[J]. 中国油料作物学报,2025,47(5):1298-1305.
[30]丛媛媛,刘浩,衣志刚,等. 基于混合样品集的大豆种子蔗糖含量近红外光谱定标模型建立[J]. 大豆科学,2020,39(6):940-946.
[31]杨泉女,周权驹,王蕴波,等. 甜玉米葡萄糖、果糖和蔗糖含量近红外反射光谱模型构建[J]. 中国农业科技导报,2018,20(1):137-146.
[32]黄璐,王富豪,郭鲁平,等. 基于近红外光谱法的绿豆淀粉和蛋白质无损快速检测[J]. 江苏农业科学,2022,50(19):187-191.

备注/Memo

备注/Memo:
收稿日期：2026-01-06基金项目：国家重点研发计划项目(2024YFD1201400)；生物育种钟山实验室项目(ZSBBL)作者简介：逯紫妍(1998-),女,河南郑州人,硕士研究生,主要从事豆类功能育种与综合利用研究。(E-mail)1126450036@qq.com通讯作者：薛晨晨,(E-mail)xuecc@jaas.ac.cn
更新日期/Last Update: 2026-09-16