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作物学报

作物学报 ›› 2025, Vol. 51 ›› Issue (7): 1757-1768.doi: 10.3724/SP.J.1006.2025.44194

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

基于近红外快速检测技术的谷子淀粉多样性分析及模型构建

王若楠1,2**(), 张颖星1,2**, 于筱菡2, 刘少雄2, 王跃1,2, 薛亚鹏1,2, 辛旭霞1,2, 张莉1,*(), 刘敏轩2,*()   

  1. 1山西农业大学农学院, 山西晋中 030801
    2中国农业科学院作物科学研究所, 北京 100081
  • 收稿日期:2024-11-22 接受日期:2025-03-26 出版日期:2025-07-12 网络出版日期:2025-04-02
  • 通讯作者: *张莉, E-mail: zhangli7912@163.com; 刘敏轩, E-mail: liuminxuan@caas.cn
  • 作者简介:王若楠, E-mail: w15517079126@163.com
    **同等贡献
  • 基金资助:
    国家重点研发计划项目“杂粮抗逆抗病种质资源的系统挖掘与精准鉴定”(2023YFD1202703-2);国家自然科学基金项目“种质资源遗传基础解析”(32241041);财政部和农业农村部国家现代农业产业技术体系建设专项(CARS-06-14.5-A2)

Near-infrared spectroscopic evaluation of starch diversity and model construction in foxtail millet

WANG Ruo-Nan1,2**(), ZHANG Ying-Xing1**,2, YU Xiao-Han2, LIU Shao-Xiong2, WANG Yue1,2, XUE Ya-Peng1,2, XIN Xu-Xia1,2, ZHANG Li1,*(), LIU Min-Xuan2,*()   

  1. 1College of Agronomy, Shanxi Agricultural University, Jinzhong 030801, Shanxi, China
    2Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2024-11-22 Accepted:2025-03-26 Published:2025-07-12 Published online:2025-04-02
  • Contact: *E-mail: zhangli7912@163.com; E-mail: liuminxuan@caas.cn
  • About author:**Contributed equally to this work
  • Supported by:
    National Key Research and Development Program of China “Systematic Mining and Precise Identification of Resistant and Disease-resistant Germplasm Resources of Mixed Grains”(2023YFD1202703-2);National Natural Science Foundation of China “Genetic Basis Analysis of Mixed Grains Germplasm Resources”(32241041);China Agriculture Research System of MOF and MARA(CARS-06-14.5-A2)

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摘要：

建立谷子种质资源品质性状的快速、高效检测对挖掘具有优异品质性状的资源具有重要意义。本研究选取来自于国内外不同生态区谷子种质资源657份, 采用双波长法测定种子的直链淀粉、支链淀粉和总淀粉含量, 在此基础上选择550份种质用Unscrambler X 10.4化学计量软件构建直链淀粉、支链淀粉和总淀粉的近红外模型, 利用标准正常化结合散射处理(SNV and Detrend)和一阶导数处理参数对原始光谱进行预处理, 用偏最小二乘法(PLS)构建光谱模型。试验结果表明, 657份谷子种质的直链淀粉含量为2.99%~22.40%, 平均值为16.25%; 支链淀粉含量为52.77%~76.09%, 平均值为59.56%; 总淀粉含量为62.53%~83.31%, 平均值为75.81%; 直支比为0.04~0.40, 平均值为0.28。国外种质的直链淀粉和总淀粉的变异系数最高, 分别为30.08%、5.07%; 与国内种质相比, 国外种质的平均总淀粉含量最低, 平均值为75.19%, 幅度范围为64.65%~ 82.38%。国内5个生态区谷子种质的淀粉含量差异明显, 内蒙古高原区直链淀粉、总淀粉和直支比的变异系数最高, 分别为29.40%、4.07%、30.77%; 东北春谷区种质的支链淀粉的变异系数最高, 为6.00%; 南方谷子栽培区种质的直链淀粉、支链淀粉、总淀粉和直支比的变异系数最低, 分别为8.21%、4.40%、2.97%和10.71%。本研究筛选出的高直支比和高支链淀粉含量在前5名的材料均来自于华北夏谷区、黄土高原区和东北春谷区, 其中黄土高原区二毛尖的直支比和直链淀粉最高(0.40、22.40%), 华北夏谷区半芒红谷的支链淀粉含量最高(76.09%)。直链淀粉、支链淀粉和总淀粉的近红外预测模型校正相关系数(R2cal)分别为0.910、0.848和0.717, 交叉验证决定系数(R2cv)分别为0.902、0.830和0.675, 外部验证决定系数(R2val)分别为0.903、0.826和0.702, 定标标准误差(SEC)分别为1.156、1.234和1.367, 交叉检验标准误差(RMSECV)分别为1.208、1.288和1.471, 验证标准偏差(RMSEP)分别为1.130、1.260和1.649, 外部验证相对分析误差(RPD)分别为3.415、2.539和1.765, 最佳因子分别为9、10、10。研究表明, 国内外不同生态区的谷子种质在淀粉含量上呈显著多样性, 且本研究开发的近红外光谱(NIRS)模型可用于预测谷子的直链淀粉和支链淀粉含量, 总淀粉含量虽然可以粗略预测, 但仍需进一步的调整和优化以提高准确性。

关键词: 谷子, 不同生态区, 近红外光谱, 直链淀粉, 支链淀粉

Abstract:

Developing rapid and efficient methods for assessing quality traits in foxtail millet germplasm is crucial for identifying superior genetic resources. In this study, we analyzed 657 foxtail millet germplasms from diverse ecological regions, both domestic and international. The double-wavelength method was used to determine amylose, amylopectin, and total starch contents in seeds. Of these, 550 germplasms were selected to develop near-infrared spectroscopy (NIRS) models for predicting amylose, amylopectin, and total starch contents using Unscrambler X 10.4 chemometric software. Standard normal variate transformation combined with scatter correction and first derivative was applied for spectral preprocessing, and partial least squares regression was used to construct the predictive models. The results showed that amylose content across the 657 germplasms ranged from 2.99% to 22.40% (mean: 16.25%), amylopectin content from 52.77% to 76.09% (mean: 59.56%), total starch content from 62.53% to 83.31% (mean: 75.81%), and the amylose-to-amylopectin ratio from 0.04 to 0.40 (mean: 0.28). Among all tested germplasms, foreign accessions exhibited the highest coefficients of variation (CVs) for amylose (30.08%) and total starch (5.07%). Compared to domestic germplasms, foreign germplasms had lower average total starch (75.19%) contents, with ranges of 64.65%-82.38%, respectively. Significant differences in starch content were observed among foxtail millet germplasms from five domestic ecological regions. The Inner Mongolia Plateau region exhibited the highest CVs for amylose content (29.40%), total starch content (4.07%), and the amylose-to-amylopectin ratio (30.77%) among all domestic regions. The highest CV for amylopectin content (6.00%) was observed in the Northeast Spring Millet region, whereas the Southern region exhibited the lowest CVs for amylose (8.21%), amylopectin (4.40%), total starch (2.97%), and the amylose-to-amylopectin ratio (10.71%). Germplasms with the highest amylose-to-amylopectin ratios and amylopectin contents were primarily from the North China Summer Millet region, Loess Plateau region, and Northeast Spring Millet region. Notably, Ermaojian from the Loess Plateau region had the highest amylose-to-amylopectin ratio (0.40) and amylose content (22.40%), while Banmanghonggu from the North China Summer Millet region had the highest amylopectin content (76.09%). The NIRS models developed for amylose, amylopectin, and total starch contents achieved calibration correlation coefficients of 0.910, 0.848, and 0.717, respectively; cross-validation determination coefficients of 0.902, 0.830, and 0.675; and external validation determination coefficients of 0.903, 0.826, and 0.702. The standard errors of calibration were 1.156, 1.234, and 1.367, while the root mean square errors of cross-validation were 1.208, 1.288, and 1.471, and the root mean square errors of prediction were 1.130, 1.260, and 1.649, respectively. The ratio of performance to deviation for external validation was 3.415, 2.539, and 1.765, with optimal factor numbers of 9, 10, and 10, respectively. This study highlights the substantial variation in starch content among foxtail millet germplasms from different ecological regions, both domestically and internationally. The NIRS models developed here are effective for predicting amylose and amylopectin contents in foxtail millet. However, further refinement is needed to improve the accuracy of total starch content predictions.

Key words: foxtail millet, different ecological regions, near infrared spectroscopy, amylose, amylopectin

表1

657份参试谷子的产地和所属生态区"

序号
No.		 所属生态区
Ecological region		 原产地
Origin		 淀粉含量测定样品数
Number of samples for starch content		 近红外模型构建样品数
Number of samples for NIRS model
1 中国东北春谷区
Northeast spring millet region, China		 中国黑龙江; 中国吉林; 中国辽宁
Heilongjiang, China; Jilin, China; Liaoning, China		 45 39
2 中国华北夏谷区
North China summer- sowing region, China		 中国山东; 中国河北; 中国河南; 中国北京; 中国天津
Shandong, China; Hebei, China; Henan, China; Beijing, China; Tianjin, China		 522 432
3 中国内蒙古高原区
Inner Mongolia plateau, China		 中国内蒙古; 中国河北; 中国辽宁
Inner Mongolia, China; Hebei, China; Liaoning, China		 26 22
4 中国黄土高原区
Loess plateau, China		 中国山西; 中国陕西
Shanxi, China; Shaanxi, China		 29 25
5 中国南方谷子栽培区Southern region, China 中国湖南; 中国广东; 中国海南; 中国贵州; 中国广西; 中国云南; 中国西藏
Hunan, China; Guangdong, China; Hainan, China; Guizhou, China; Guangxi, China; Yunnan, China; Xizang, China		 17 17
6 国外
Foreign		 日本, 朝鲜, 德国, 美国, 其他
Japan, D.P.R. Korea, Germany, USA, and others		 18 15

图1

657份谷子种质直链淀粉、支链淀粉、总淀粉含量和直支比分布直方图"

表2

657份谷子直链淀粉、支链淀粉和总淀粉含量及直支比总体分布特征"

品质性状
Quality trait		 最小值
Min. (%)		 最大值
Max. (%)		 极差
Extreme difference		 平均值Mean (%) 标准差
SD		 变异系数CV
(%)		 遗传多样性指数
H′
直链淀粉Amylose 2.99 22.40 19.41 16.25 4.10 25.23 1.46
支链淀粉Amylopectin 52.77 76.09 23.32 59.56 3.32 5.57 1.95
总淀粉Starch 62.53 83.31 20.78 75.81 2.70 3.56 2.22
直支比
Amylose-to-amylopectin ratio		 0.04 0.40 0.36 0.28 0.08 28.57 1.59

表3

不同生态区谷子淀粉含量比较"

生态区
Ecological region		 品质性状
Quality trait		 平均值
Mean±SD (%)		 幅度
Range (%)		 变异系数
CV (%)
东北春谷区
Northeast spring millet region, China		 直链淀粉Amylose 16.89±3.08 3.06-21.74 18.24
支链淀粉Amylopectin 59.51±3.57 54.11-68.97 6.00
总淀粉Starch 76.40±2.46 69.92-83.31 3.22
直支比Amylose-to-amylopectin ratio 0.29±0.06 0.05-0.40 20.69
华北夏谷区
North China summer-
sowing region, China		 直链淀粉Amylose 16.17±4.23 2.99-22.03 26.16
支链淀粉Amylopectin 59.56±3.36 52.77-56.09 5.64
总淀粉Starch 75.73±2.67 62.53-82.30 3.53
直支比Amylose-to-amylopectin ratio 0.28±0.08 0.04-0.40 28.57
内蒙古高原区
Inner Mongolia plateau, China		 直链淀粉Amylose 15.61±4.59 3.05-21.06 29.40
支链淀粉Amylopectin 60.23±3.29 54.04-66.61 5.46
总淀粉Starch 75.84±3.09 66.70-81.43 4.07
直支比Amylose-to-amylopectin ratio 0.26±0.08 0.05-0.38 30.77
黄土高原区
Loess plateau, China		 直链淀粉Amylose 17.23±3.27 3.49-22.40 18.98
支链淀粉Amylopectin 59.01±3.02 53.55-65.56 5.12
总淀粉Starch 76.25±2.62 69.05-81.34 3.41
直支比Amylose-to-amylopectin ratio 0.29±0.06 0.05-0.40 20.69
南方谷子栽培区
Southern region, China		 直链淀粉Amylose 16.69±1.37 14.20-19.28 8.21
支链淀粉Amylopectin 59.97±2.64 55.89-65.10 4.40
南方谷子栽培区
Southern region, China		 总淀粉Starch 76.66±2.28 72.57-81.63 2.97
直支比Amylose-to-amylopectin ratio 0.28±0.03 0.23-0.34 10.71
国外
Foreign		 直链淀粉Amylose 15.99±4.81 3.08-20.23 30.08
支链淀粉Amylopectin 59.20±2.89 54.65-65.76 4.88
总淀粉Starch 75.19±3.81 64.65-82.38 5.07
直支比Amylose-to-amylopectin ratio 0.27±0.08 0.05-0.36 29.63

表4

高直支比、直链淀粉和支链淀粉优异资源清单"

品质性状
Quality trait		 品种名称
Cultivar name		 表型值
Phenotypic parameter		 生态区
Ecological region
直支比
Amylose-to-
amylopectin ratio		 二毛尖 Ermaojian 0.40 黄土高原区Loess plateau
大瓦屋里 Dawawuli 0.40 华北夏谷区North China summer-sowing region
莱芜县 Laiwuxian 0.40 东北春谷区Northeast spring millet region
大叶青 Dayeqing 0.40 华北夏谷区North China summer-sowing region
红苗 Hongmiao 0.40 东北春谷区Northeast spring millet region
直链淀粉
Amylose		 二毛尖 Ermaojian 22.40% 黄土高原区Loess plateau
白谷 Baigu 22.03% 华北夏谷区North China summer-sowing region
大叶青 Dayeqing 21.99% 华北夏谷区North China summer-sowing region
大瓦屋里 Dawawuli 21.76% 华北夏谷区North China summer-sowing region
莱芜县 Laiwuxian 21.74% 东北春谷区Northeast spring millet region
支链淀粉
Amylopectin		 半芒红谷 Banmanghonggu 76.09% 华北夏谷区North China summer-sowing region
黄棒头 Huangbangtou 75.00% 华北夏谷区North China summer-sowing region
黄壳狗尾粟Huangkegouweisu 73.06% 华北夏谷区North China summer-sowing region
黄粘谷Huangzhangu 72.59% 华北夏谷区North China summer-sowing region
七里香酒小谷Qilixiangjiuxiaogu 71.16% 华北夏谷区North China summer-sowing region

表5

谷子样品淀粉指标相关统计参数"

项目
Item		 样本数
Number of samples		 品质性状
Quality trait		 最大值
Max. (%)		 最小值
Min. (%)		 平均数
Mean (%)		 标准差
SD
校正集
Calibration set		 400 直链淀粉Amylose 22.03 3.00 16.01 4.29
支链淀粉Amylopectin 76.09 52.77 59.70 3.42
总淀粉Starch 82.38 63.74 75.70 2.80
验证集
Validation set		 150 直链淀粉Amylose 21.47 3.05 16.42 3.86
支链淀粉Amylopectin 69.00 53.86 59.61 3.20
总淀粉Starch 83.31 62.53 76.03 2.91

图2

谷子种质原始近红外光谱图"

图3

谷子一阶导数处理近红外光谱图"

表6

谷子样品集定标模型参数"

品质性状
Quality trait		 定标标准偏差
SEC		 交叉检验标准误差RMSECV 校正决定系数
R2cal		 交叉验证决定系数
R2cv
直链淀粉Amylose 1.156 1.208 0.910 0.902
支链淀粉Amylopectin 1.234 1.288 0.848 0.830
总淀粉Starch 1.367 1.471 0.717 0.675

表7

外部验证模型参数"

品质性状
Quality trait		 验证标准偏差
RMSEP		 外部验证决定系数
R2val		 相对分析误差
RPD
直链淀粉 Amylose 1.130 0.903 3.415
支链淀粉 Amylopectin 1.260 0.826 2.539
总淀粉 Starch 1.649 0.702 1.765

图4

外部验证直链淀粉、支链淀粉和总淀粉预测值与化学值的相关性"

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