CONG Yuan-yuan,LIU Hao,YI Zhi-gang,et al.Establishment of NIRS Calibration Models for Sucrose Content in Soybean Based on the Combined Sample Set[J].Soybean Science,2020,39(06):940-946.[doi:10.11861/j.issn.1000-9841.2020.06.0940]
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
- Title:
- Establishment of NIRS Calibration Models for Sucrose Content in Soybean Based on the Combined Sample Set
- Keywords:
- Soybean; Quality; Sucrose content; NIRS calibration model
- 文献标志码:
- A
- 摘要:
- 为快速测定原料大豆的蔗糖指标，及时为调整豆制品生产工艺参数或原料配比提供数据支撑，以满足快速准确鉴定高蔗糖大豆育种新品系的需要，本研究建立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。将天然和人工添加蔗糖的大豆样品结合起来作为混合参试样品集，先利用近红外光谱分析仪采集光谱数据，再通过酶比色法测定化学值，进行光谱数据预处理，采用偏最小二乘回归统计方法建立大豆蔗糖含量的近红外光谱定量分析模型，并利用未知蔗糖含量的大豆种子样品对模型的预测性能进行验证。以混合参试样品集建立的近红外光谱定标模型能够在较宽的蔗糖含量范围（37.83~139.35 g?kg-1）内获得较为精确的预测结果，并将二阶导数联合多元散射校正作为光谱数据的最佳预处理方法。经外部验证，样品的化学测定值与定标模型预测值极显著正相关，且决定系数达0.943，预测均方差为3.17，相对误差为5.923%。所建立近红外光谱定标模型的预测能力较强、适用性较好，能够有效应用于大豆种子蔗糖含量的快速准确测量。
- Abstract:
- This study established a near-infrared spectroscopy calibration model for sucrose content in soybean. It can provide data support for the rapid determination of sucrose in the raw materials of soybean, and then adjust the processing parameters or optimum material proportion of soy products. In addition, it can meet the needs of breeding high-sucrose soybean lines. In this study, natural and sucrose-added soybean samples were combined as the sample set. The spectral data was firstly collected using a near-infrared spectrometer. Then the near-infrared spectroscopy quantitative analysis model of soybean sucrose content was established by the determination of chemical value of enzyme colorimetry, spectral data preprocessing, and partial least square regression statistical method. Finally the prediction performance of the model was verified by using soybean seed samples with unknown sucrose content. In this study, the near-infrared spectroscopy calibration model based on the combined sample set could obtain more accurate prediction results in a wide range of sucrose content (37.83-139.35g?kg-1).The second derivative combined with multivariate scattering correction was used as the best preprocessing method for spectral data. Through external verification, the chemical determination value of the sample showed a significant positive correlation with the prediction value of the calibration model, the determination coefficient was 0.943, the prediction mean square deviation was 3.17, and the relative error was 5.923%. The established near-infrared spectroscopy calibration model has strong predictive ability and good applicability, and could be effectively applied to the rapid and accurate measurement of sucrose content of soybean seeds.
参考文献/References:
［1］Anderson E J, Ali M L, Beavis W D, et al. Soybean ［Glycine max(L.) Merr.］ breeding: History, improvement, production and future opportunities［M］//Advances in Plant Breeding Strategies: Legumes. Springer, 2019: 431-516.［2］邱红梅, 王曙明, 于妍, 等. 大豆低聚糖种质筛选及遗传研究进展［J］. 大豆科学, 2014, 33(5): 768-772. (Qiu H M, Wang S M, Yu Y, et al. Research progression germplasm screening and genetic with oligosaccharides of soybean［J］. Soybean Science, 2014, 33(5): 768-772.)［3］李菁华, 张明聪, 金喜军, 等. 高油型和高蛋白型大豆鼓粒期的糖分积累规律［J］. 大豆科学, 2017, 36(1): 68-73. (Li J H, Zhang M C, Jin X J, et al. Sugar accumulation rule of high oil and high protein soybean during the seed-filling period［J］. Soybean Science, 2017, 36(1): 68-73.)［4］孙明明, 王萍, 李智媛, 等. 大豆活性成分研究进展［J］. 大豆科学, 2018, 37(6): 975-983. (Sun M M, Wang P, Li Z Y, et al. Research progress of soybean active ingredients［J］. Soybean Science, 2018, 37(6): 975-983.)［5］Hagely K B, Jo H, Kim J H, et al. Molecular-assisted breeding for improved carbohydrate profiles in soybean seed［J］. Theoretical and Applied Genetics, 2020, 133(4): 1189-1200.［6］Lee J S, Kim S M, Kang S. Fine mapping of quantitative trait loci for sucrose and oligosaccharide contents in soybean ［Glycine max(L.) Merr.］ using 180 K Axiom SoyaSNP genotyping platform［J］. Euphytica, 2016, 208(1): 195-203.［7］Dobbels A A, Michno J M, Campbell B W, et al. An induced chromosomal translocation in soybean disrupts a KASI ortholog and is associated with a high-sucrose and low-oil seed phenotype［J］. Agronomy and Plant Gentics, 2017, 7(4): 1215-1223.［8］Matei G,Woyann L G, Meneguzzi C, et al. Profiling and genotype×environmentinteractions of seed sugar contents in Brazilian soybean genotypes［J］. Euphytica, 2017, 213(9): 203.［9］Patil G, Vuong T D, Kale S, et al. Dissecting genomic hotspots underlying seed protein, oil, and sucrose content in an interspecific mapping population of soybean using high-density linkage mapping［J］. Plant Biotechnology Journal, 2018, 16(11): 1939-1953.［10］Medic J,Atkinson C, Hurburgh C R. Current knowledge in soybean composition［J］. Journal of the American Oil Chemists′ Society, 2014, 91(3): 363-384.［11］Maupin L M, Rosso M L, Rainey K M. Environmental effects on soybean with modified phosphorus and sugar composition［J］. Crop Science, 2011, 51(2): 642-650.［12］Rosso M L, Burleson S A, Maupin L M, et al. Development of breeder-friendly markers for selection of 〖STBX〗MIPS1〖STBZ〗 mutations in soybean［J］. Molecular Breeding, 2011, 28(1): 127-132.［13］王潇潇, 李军涛, 孙祥丽, 等. 近红外反射光谱快速测定四种大豆制品中寡糖含量的研究［J］. 光谱学与光谱分析, 2018, 38(1): 58-61. (Wang X X, Li J T, Sun X L, et al. Study on rapid determination of oligosaccharides in soybean products by near-infrared reflectance spectroscopy［J］. Spectroscopy and Spectral Analysis, 2018, 38(1): 58-61.)［14］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. (Yang Q N, Zhou Q J, Wang Y B, et al. Establishment of NIRS models for the content of glucose, fructose and sucrose in sweet corn［J］. Journal of Agricultural Science and Technology, 2018, 20(1): 137-146.)［15］薛忠财, 高辉远. 反射光谱技术在监测大豆叶片光化学效率和水分状况中的应用［J］. 大豆科学, 2016, 35(3): 436-441. (Xue Z C, Gao H Y. Application of spectral reflectance technique on monitoring the photochemical efficiency and water condition in soybean leaves［J］. Soybean Science, 2016, 35(3): 436-441.)［16］王铎, 张力, 范素杰, 等. 大豆主要脂肪酸含量近红外模型的建立［J］. 大豆科学, 2017, 36(2): 295-299. (Wang D, Zhang L, Fan S J, et al. Establishment of NIRS model for the main fatty acids in soybean［J］. Soybean Science, 2017, 36(2): 295-299.)［17］Cortés V, Blasco J, Aleixos N, et al. Monitoring strategies for quality control of agricultural products using visible and near-infrared spectroscopy: A review［J］. Trends in Food Science and Technology, 2019, 85: 138-148.［18］王丽萍, 陈文杰, 赵兴忠, 等. 基于近红外漫反射光谱法的大豆粗蛋白和粗脂肪含量的快速检测［J］. 大豆科学, 2019, 38(2): 280-285. (Wang L P, Chen W J, Zhao X Z, et al. Rapid determination of crude protein and crude oil content of soybean based on near infrared diffuse reflectance spectroscopy［J］. Soybean Science, 2019, 38(2): 280-285.)［19］王丽萍, 赵兴忠, 陈文杰, 等. 油菜籽含油量傅里叶变换近红外模型的修正［J］. 激光生物学报, 2013, 22(1): 44-47. (Wang L P, Zhao X Z, Chen W J, et al. Optimization of quantitative analysis model for oil content in rapeseed with Fourier transform near infrared spectroscopy［J］. Acta Laser Biology Sinica, 2013, 22(1): 44-47.)［20］王翠秀, 曹见飞, 顾振飞, 等. 基于近红外光谱大豆蛋白质、脂肪快速无损检测模型的优化构建［J］. 大豆科学, 2019, 38(6): 968-976. (Wang C X, Cao J F, Gu Z F, et al. Rapid nondestructive test of soybean protein and fat by near infrared spectroscopy combined with different model methods［J］. Soybean Science, 2019, 38(6): 968-976.)［21］Wee C D, Hashiguchi M, Ishigaki G, et al. Evaluation of seed components of wild soybean (Glycine soja) collected in Japan using near-infrared reflectance spectroscopy［J］. Plant Genetic Resources, 2018, 16(2): 94-102.［22］Choung M G.Determinationof sucrose content in soybean using near-infrared reflectance spectroscopy［J］. Journal of the Korean Society for Applied Biological Chemistry, 2010, 53(4): 478-484.［23］惠文凯, 王益, 陈晓阳. 麻疯树种子含油量近红外光谱定标模型的建立［J］. 北京林业大学学报, 2018, 40(1): 1-7. (Hui W K, Wang Y, Chen X Y. Calibration model building for investigating seed oil content of Jatropha curcasusing near infrared spectroscopy［J］. Journal of Beijing Forestry University, 2018, 40(1): 1-7.)［24］张娟娟, 熊淑萍, 时雷, 等. 基于近红外光谱分析的土壤全氮含量估测研究［J］. 土壤, 2015, 47(4): 653-657. (Zhang J J, Xiong S P, Shi L, et al. Soil nitrogen content prediction with near infrared spectroscopy［J］. Soils, 2015, 47(4): 653-657.)［25］刘燕德, 肖怀春, 邓清, 等. 柑桔黄龙病近红外光谱无损检测［J］. 农业工程学报, 2016, 32(14): 202-208. (Liu Y D, Xiao H C, Deng Q, et al. Nondestructive detection of citrus greening by near infrared spectroscopy［J］. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(14): 202-208.)［26］芦兵, 孙俊, 杨宁, 等. 基于SAGA-SVR预测模型的水稻种子水分含量高光谱检测［J］. 南方农业学报, 2018, 49(11): 2342-2348. (Lu B, Sun J, Yang N, et al. Hyperspectral detection for moisture in rice seeds by SAGA-SVR prediction model［J］. Journal of Southern Agriculture, 2018, 49(11): 2342-2348.)［27］杨志敏, 丁武, 张瑶. 应用近红外技术快速鉴别原料肉注水的研究［J］. 食品研究与开发, 2012, 33(5): 118-120, 128. (Yang Z M, Ding W, Zhang Y. Study on discrimination of raw meat and water-injected meat based on near-infrared spectroscopy and artificial neural network model［J］. Food Research and Development, 2012, 33(5): 118-120, 128.)［28］杨国强, 张淑娟, 赵艳茹. 基于近红外透射光谱的汾阳王酒快速鉴别［J］. 农业机械学报, 2013, 44(S1): 189-193. (Yang G Q, Zhang S J, Zhao Y R. Fast discrimination of adulterated Fenyangwang wine based on near infrared spectroscopy［J］. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(S1): 189-193.)［29］田晶, 李巧玲. 近红外光谱法快速检测饮料中的食用合成色素［J］. 食品科学, 2018, 39(2): 293-297. (Tian J, Li Q L. Rapid determination of synthetic pigments in fruit-flavored beverage by near infrared spectroscopy［J］. Food Science, 2018, 39(2): 293-297.)［30］曹晓兰, 邓梦洁, 汪佩佩. 基于PLSR的苎麻叶片含水量估测模型建立及优化［J］. 激光生物学报, 2018, 27(5): 467-472. (Cao X L, Deng M J, Wang P P. Building and optimizing of the PLSR based estimation model ramie leaf′s water content［J］. Acta Laser Biology Sinica, 2018, 27(5): 467-472.)［31］张津源, 张德贤, 张苗. 基于连续投影算法的小麦蛋白质含量近红外光谱预测分析［J］. 江苏农业学报, 2019, 35(4): 960-964. (Zhang J Y, Zhang D X, Zhang M. Prediction and analysis of wheat protein content by near-infrared spectroscopy based on successive projections algorithm［J］. Jiangsu Journal of Agricultural Sciences, 2019, 35(4): 960-964.)
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[19]刘玉平,李志刚,李瑞平.不同密度与施氮水平对高油大豆产量及品质的影响[J].大豆科学,2011,30(01):79.[doi:10.11861/j.issn.1000-9841.2011.01.0079]
LIU Yu-ping,LI Zhi-gang,LI Rui-ping.Effects of Different Planting Densities and N-fertilizer Levels on Yield and Quality of Soybean[J].Soybean Science,2011,30(06):79.[doi:10.11861/j.issn.1000-9841.2011.01.0079]
[20]张 伟,王曙明,邱 强,等.从品种志分析吉林省八十五年来大豆育成品种产量和品质的演变[J].大豆科学,2009,28(06):970.[doi:10.11861/j.issn.1000-9841.2009.06.970]
ZHANG Wei,WANG Shu-ming,QIU Qiang,et al.Changes of Yield and Quality Traits of Released Soybean Cultivars during Past 85 Years in Jilin Province[J].Soybean Science,2009,28(06):970.[doi:10.11861/j.issn.1000-9841.2009.06.970]
备注/Memo
收稿日期：2020-04-24