基于生态效应的水稻籽粒蛋白质含量预测模型研究

doi:10.17521/cjpe.2005.0084

摘要/Abstract

摘要：

在中国、日本、泰国不同生态环境下进行多品种籼型和粳型水稻(Oryza sativa)的区域种植试验,通过分析水稻籽粒蛋白质含量与纬度、海拔、抽穗后温度和太阳辐射等气候生态因子的相互关系,确立了影响水稻籽粒蛋白质积累的主要气候生态因子函数,并使用权重系数来进一步修订各气候生态因子对水稻籽粒蛋白质的作用,构建出基于生态效应(主要气候生态因子函数)的水稻籽粒蛋白质含量预测模型。利用不同年份、不同生态点、不同品种类型的试验资料对所建模型进行了检验,籼稻和粳稻籽粒蛋白质含量的预测误差RMSE平均分别为0.27%和0.24%;籼稻试验点和粳稻试验点的预测误差平均为0.25%和0.22%,表明模型总体上具有较好的预测性和实用性。

关键词: 水稻, 蛋白质, 生态环境, 预测模型

Abstract:

Grain protein content in rice (Oryza sativa) is an important indication of rice nutritional quality and is determined by both genotype and environmental factors. Much attention has been paid to the relationships between protein accumulation in rice grains and environmental factors. Modeling changes of protein content in rice under different environmental conditions is of great help for predicting rice quality and ecological zoning. In this study, Indica and Japonica rice varieties grown under different ecological environments in China (Jiangsu), Japan (Iwate, Shimane, Kyoto) and Thailand (Changmai) were grown for two years, and the relationships between grain protein content and environmental factors, including latitude (x₁), altitude (x₂), ecological height, latitude, altitude, (x₃), and average temperature (x₄), lowest temperature (x₅), highest temperature (x₆) and solar radiation during the grain filling period were analyzed. Environmental factor-driven equations were established for Indica rice: f (x₁) =8.4E-$04x_1^2$ +0.049 05x₁+0.282 1, f(x₂) =2.82E-$07x_2^2$-3.8E-04x₂+1.128 6, f (x₃) = 9.2E-$10x_3^2$-3.1E-05x₃+1.255 6, f (x₄) =-0.007 $02x_4^2$+0.303 7x₄-2.285, f (x₅)=-0.009 $18x_5^2$+0.313 9x₅-1.684 6, f (x₆)= -0.006 $99x_6^2$+0.372 8x₆-3.971 7; and for Japonica rice: f (x₁)=-0.000 $695x_1^2$+0.038 51x₁+0.466 1, f (x₃)= 4.02E-$10x_3^2$-1.2E-05x₃+1.090 4, f (x₄)= -0.004 $16x_4^2$++0.185 9x₄-1.077 4, f (x₅)=-0.006 $54x_5^2$+0.228 6x₅-0.996 8, f (x₆)=-0.004 $12x_6^2$+0.226x₆-2.099 1. By using a weighted method to modify the impacts of environmental factors on grain protein accumulation, an ecological model was developed for predicting grain protein content in Indica rice: PC=PC₀×[0.138 9×f(x₁)+0.152 6×f(x₂)+0.187 4×f(x₃)+0.180 2×f(x₄)+0.168 5×f(x₅)+0.173 4×f(x₆)]; and PC=PC₀×[0.262 3×f(x₁)+0.09×f(x₃)+0.202 3×f(x₄) +0.246 1×f(x₅)+0.198 4×f(x₆)] for Japonica rice, where PC₀ is the specific protein content of cultivar. The model was validated using the data sets for different years, eco-sites and varieties. The root mean square error (RMSE) was 0.27% and 0.24% for Indica rice and Japonica rice, respectively, and the RMSE was 0.25% and 0.22% for the growing areas of Indica and Japonica rice types, respectively. The results indicated that the model was accurate and applicable for predicting protein content in rice under different conditions. Yet, more experimental data in different eco-environments are required for wider testing of the present model.

Key words: Rice (Oryza sativa), Protein content, Ecological environment, Predictive model

李卫国, 戴廷波, 朱艳, 曹卫星. 基于生态效应的水稻籽粒蛋白质含量预测模型研究. 植物生态学报, 2005, 29(4): 630-635. DOI: 10.17521/cjpe.2005.0084

LI Wei-Guo, DAI Ting-Bo, ZHU Yan, CAO Wei-Xing. AN ECOLOGICAL MODEL FOR PREDICTING PROTEIN CONTENT IN RICE GRAINS. Chinese Journal of Plant Ecology, 2005, 29(4): 630-635. DOI: 10.17521/cjpe.2005.0084

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2005.0084

https://www.plant-ecology.com/CN/Y2005/V29/I4/630

图/表 5

表1 不同类型水稻籽粒蛋白质含量与气候因子的关系函数

Table 1 Relationship equation between climatic factors and grain protein content in different rice cultivars

籼稻 Indica rice	决定系数 $R i 2$	极值 Y_max	籼稻 Indica rice	决定系数 $R i 2$	极值 Y_max
y₁=-0.006 8 $x 1 2$ +0.398x₁+2.29	0.693 6^*	8.116	y₁=-0.005 6 $x 1 2$ +0.311x₁+3.76	0.895 2^**	8.062
y₂=2E-06 $x 2 2$ -0.002 7x₂+8.0	0.767 2^*	7.085	y₂=8E-07 $x 2 2$ -0.000 8x₂+8.02	0.102 7	8.017
y₃=6E-09 $x 3 2$ -0.000 2x₃+8.19	0.942 1^**	6.052	y₃=3E-09 $x 3 2$ -9E-05x₃+8.15	0.305 5	7.479
y₄=-0.055 1 $x 4 2$ +2.384x₄-17.93	0.905 6^**	7.848	y₄=-0.033 9 $x 4 2$ +1.515x₄-8.78	0.686 9^*	8.148
y₅=-0.073 $x 5 2$ +2.497x₅-13.4	0.871 9^**	7.955	y₅=-0.054 5 $x 5 2$ +1.904x₅-8.30	0.835 8^**	8.331
y₆=-0.054 9 $x 6 2$ +2.928x₆-31.19	0.846 8^**	7.854	y₆=-0.033 7 $x 6 2$ +1.849x₆-17.17	0.672 2^*	8.181
y₇=-0.089 4x₇+8.4843	0.409 7	8.005	y₇=-0.084 6x₇+8.9531	0.409 7	8.241
y₈=0.244 8 $x 8 2$ -4.43x₈+27.64	0.110 8	7.984	y₈=0.237 3 $x 8 2$ -4.17x₈+26.109	0.300 9	8.195

表1 不同类型水稻籽粒蛋白质含量与气候因子的关系函数

Table 1 Relationship equation between climatic factors and grain protein content in different rice cultivars

籼稻 Indica rice	决定系数 $R i 2$	极值 Y_max	籼稻 Indica rice	决定系数 $R i 2$	极值 Y_max
y₁=-0.006 8 $x 1 2$ +0.398x₁+2.29	0.693 6^*	8.116	y₁=-0.005 6 $x 1 2$ +0.311x₁+3.76	0.895 2^**	8.062
y₂=2E-06 $x 2 2$ -0.002 7x₂+8.0	0.767 2^*	7.085	y₂=8E-07 $x 2 2$ -0.000 8x₂+8.02	0.102 7	8.017
y₃=6E-09 $x 3 2$ -0.000 2x₃+8.19	0.942 1^**	6.052	y₃=3E-09 $x 3 2$ -9E-05x₃+8.15	0.305 5	7.479
y₄=-0.055 1 $x 4 2$ +2.384x₄-17.93	0.905 6^**	7.848	y₄=-0.033 9 $x 4 2$ +1.515x₄-8.78	0.686 9^*	8.148
y₅=-0.073 $x 5 2$ +2.497x₅-13.4	0.871 9^**	7.955	y₅=-0.054 5 $x 5 2$ +1.904x₅-8.30	0.835 8^**	8.331
y₆=-0.054 9 $x 6 2$ +2.928x₆-31.19	0.846 8^**	7.854	y₆=-0.033 7 $x 6 2$ +1.849x₆-17.17	0.672 2^*	8.181
y₇=-0.089 4x₇+8.4843	0.409 7	8.005	y₇=-0.084 6x₇+8.9531	0.409 7	8.241
y₈=0.244 8 $x 8 2$ -4.43x₈+27.64	0.110 8	7.984	y₈=0.237 3 $x 8 2$ -4.17x₈+26.109	0.300 9	8.195

表2 不同类型水稻籽粒蛋白质含量的气候因子函数

Table 2 Climatic factor equations for grain protein content in different rice cultivars

籼稻蛋白质因子函数 Factor equation of Indic rice	r_i	粳稻蛋白质因子函数 Factor equation of Japonica rice	r_i
f(x₁)=-0.000 84 $x 1 2$ +0.049 05x₁+0.282 1	0.139 8	f(x₁)=-0.000 695 $x 1 2$ +0.038 51x₁+0.466 1	0.262 3
f(x₂)= 2.82E-07 $x 2 2$ -0.000 38x₂+1.128 6	0.152 6
f(x₃)= 9.2E-10 $x 3 2$ -3.1E-05x₃+1.255 6	0.187 4	f(x₃)= 4.02E-10 $x 3 2$ -1.2E-05x₃+1.090 4	0.09
f(x₄)=-0.007 02 $x 4 2$ +0.303 7x₄-2.285	0.180 2	f(x₄)=-0.004 16 $x 4 2$ +0.185 9x₄-1.077 4	0.202 3
f(x₅)=-0.009 18 $x 5 2$ +0.313 9x₅-1.684 6	0.168 5	f(x₅)=-0.006 54 $x 5 2$ +0.228 6x₅-0.996 8	0.246 1
f(x₆)=-0.006 99 $x 6 2$ +0.372 8x₆-3.971 7	0.173 4	f(x₆)=-0.004 12 $x 6 2$ +0.226x₆-2.099 1	0.198

表2 不同类型水稻籽粒蛋白质含量的气候因子函数

Table 2 Climatic factor equations for grain protein content in different rice cultivars

籼稻蛋白质因子函数 Factor equation of Indic rice	r_i	粳稻蛋白质因子函数 Factor equation of Japonica rice	r_i
f(x₁)=-0.000 84 $x 1 2$ +0.049 05x₁+0.282 1	0.139 8	f(x₁)=-0.000 695 $x 1 2$ +0.038 51x₁+0.466 1	0.262 3
f(x₂)= 2.82E-07 $x 2 2$ -0.000 38x₂+1.128 6	0.152 6
f(x₃)= 9.2E-10 $x 3 2$ -3.1E-05x₃+1.255 6	0.187 4	f(x₃)= 4.02E-10 $x 3 2$ -1.2E-05x₃+1.090 4	0.09
f(x₄)=-0.007 02 $x 4 2$ +0.303 7x₄-2.285	0.180 2	f(x₄)=-0.004 16 $x 4 2$ +0.185 9x₄-1.077 4	0.202 3
f(x₅)=-0.009 18 $x 5 2$ +0.313 9x₅-1.684 6	0.168 5	f(x₅)=-0.006 54 $x 5 2$ +0.228 6x₅-0.996 8	0.246 1
f(x₆)=-0.006 99 $x 6 2$ +0.372 8x₆-3.971 7	0.173 4	f(x₆)=-0.004 12 $x 6 2$ +0.226x₆-2.099 1	0.198

图1 不同生态区籼稻品种(A)和粳稻品种(B)籽粒蛋白质含量模拟值与观测值的比较

Fig.1 Comparison between simulated and measured grain protein contents of Indica rice (A) and Japonica rice (B) under different eco-environments

表3 不同品种不同种植区水稻籽粒蛋白质含量预测的RMSE

Table 3 RMSEs for protein contents of different rice cultivars under different environments

籼稻 Indica rice	RMSE (%)	籼稻种植区 Indica rice region	RMSE (%)	籼稻 Indica rice	RMSE (%)	籼稻种植区 Indica rice region	RMSE (%)
`NP65'	0.15	岛根Shimane	0.24	`BA'	0.14	岩手Iwate	0.12
`SK'	0.15	南京Nanjing	0.26	`TEN'	0.15	岛根Shimane	0.23
`CH86'	0.30	岩手Iwate	0.29	`NIP'	0.28	南京Nanjing	0.24
`IR72'	0.37	京都Kyoto	0.30	`WA'	0.38	京都Kyoto	0.29
`TAK'	0.40
`扬稻6号' `Yangdao 6'	0.20	金坛Jintan	0.16	`早丰9号' `Zaofeng 9'	0.14	昆山Kunshan	0.14
`丰优香占' `Fengyouxiangzhan'	0.21	丹阳Danyang	0.20	`广陵香粳' `Guanglingxiangjing'	0.18	泗洪Sihong	0.18
`泗稻10号' `Sidao 10'	0.23	泗洪Sihong	0.22	`连粳3号' `Lianjing 3'	0.25	丹阳Danyang	0.20
`常优1号' `Changyou 1'	0.24	昆山Kunshan	0.34	`武育粳3号' `Wuyujing 3'	0.29	金坛Jintan	0.36
`汕优63' `Shanyou 63'	0.41			`武育粳7号' `Wuyujing 7'	0.39
平均值 Average	0.27		0.25		0.24		0.22

图2 江苏省不同稻区籼稻品种(A)和粳稻品种(B)籽粒蛋白质含量模拟值与观测值的比较

Fig.2 Comparison between simulated and measured grain protein content of Indica rice (A) and Japonica rice (B) under different environments in Jangsu Province

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