基于光温效应的温室小白菜农艺指标动态模拟

蔡淑芳; 吴宝意; 廖水兰; 刘现; 雷锦桂

doi:10.19303/j.issn.1008-0384.2020.06.006

基于光温效应的温室小白菜农艺指标动态模拟

doi: 10.19303/j.issn.1008-0384.2020.06.006

福建省农业科学院数字农业研究所,　福建　福州,　350003

基金项目: 福建省自然科学基金项目（2017J01045）；福建省农业科学院项目（A2018-4，YDXM2019006，STIT2017-2-12）

详细信息

作者简介:
蔡淑芳（1985−），女，助理研究员，研究方向：数字农业（csf2019@qq.com）

通讯作者:
雷锦桂（1973−），男，研究员，研究方向：数字农业（71906244@qq.com）

中图分类号: S 634.3
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- 被引次数: 0
出版历程
- 收稿日期: 2020-04-03
- 修回日期: 2020-05-09
- 刊出日期: 2020-08-10

Light and Temperature Effects on Agronomic Indices of Brassica chinensis L. in a Simulated Greenhouse Test

Institute of Digital Agriculture, Fujian Academy of Agriculture Sciences, Fuzhou, Fujian　350003, China

摘要

摘要: 目的研究小白菜在温室环境下的农艺指标动态，揭示小白菜形态和产量形成过程。方法以耐热品种华冠小白菜为试材，在薄膜温室内开展水培试验。试验过程中，实时采集温室环境数据，并定期测定小白菜农艺指标。根据小白菜农艺指标与温度和光合有效辐射的关系，构建基于光温效应（LTF）的温室小白菜农艺指标动态模拟模型，并应用不同播期的试验数据对模型进行验证。结果结果表明，小白菜株高、叶数、叶面积、茎粗、根长、鲜重等农艺指标均随LTF的增加而增长，拟合方程可用S型生长曲线函数描述。LTF模型的预测效果优于辐热积（TEP）模型和积温（GDD）模型；其不仅改善了农艺指标的模拟精度，且拟合度较佳。各项农艺指标模拟值与实测值之间的决定系数（R²）为0.907～0.984；回归估计标准误差（RMSE）为0.540～34.393，相对误差（RE）为6.79%～12.66%，RMSE和RE分别为TEP、GDD模型的5.29%～59.98%、31.30%～96.23%。结论基于LTF的模型预测值与实测值吻合度较好，预测精度较高，可为温室小白菜生长模拟提供参考。
- 温室 /
- 小白菜 /
- 光温效应 /
- 农艺指标 /
- 模拟
Abstract: Objective By studying changes on the agronomic properties of Brassica chinensis L. in response to the light and temperature conditions in a greenhouse, morphology and yield of the plant were investigated. Method A hydroponics experiment with a heat-resistant B. chinensis in a greenhouse was carried out. The environmental data were collected in real time, and the agronomic properties of the plants monitored continuously. Relationship between the plant agronomy and the greenhouse temperature and photosynthetically active radiation (or, the light and temperature function, LTF) was used to compare with other dynamic simulation models. Result The agronomic indices including plant height, leaf number, leaf area, stem diameter, root length, and fresh weight of B. chinensis increased with increasing LTF in a fitting equation of an s-shaped function. Prediction by the LTF-based model was better than either TEP- or GDD-based model. The LTF model was not only more precise but also better fitted between the simulated and measured agronomic indices. It showed a R² of 0.907-0.984, a RMSE of 0.540-34.393, and a RE of 6.79-12.66%, which were superior to the RMSE and RE of 5.29-59.98% and 31.30-96.23% for TEP and GDD models, respectively. Conclusion The LTF-based model was found to more accurately predict the growth and yield of B. chinensis than did the other models.
- Greenhouse /
- Brassica chinensis L. /
- light and temperature function /
- agronomy /
- simulation

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图 1 小白菜单株株高（a）、叶数(b)、叶面积(c)、茎粗(d)、根长(e)、鲜重(f)与光温效应、辐热积以及积温的关系

Figure 1. Individual plant height （a）, leaf number （b）, leaf area （c）, stem diameter （d）, root length (e), and fresh weight (f) of B. chinensis in relation to LTF, TEP or GDD

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图 2 小白菜单株株高(a)、叶数(b)、叶面积(c)、茎粗(d)、根长(e)、鲜重(f)模拟值和实测值比较

Figure 2. Simulated vs. measured individual plant height(a), leaf number(b), leaf area(c), stem diameter(d), root length(e), and fresh weight(f) of B. chinensis

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表 1 试验期间环境温度和光合有效辐射情况

Table 1. Ambient temperature and photosynthetically active radiation applied for experimentation

试验期 Experiment	天数 Days/d	日平均气温 Daily average temperature/℃			日光合有效辐射 Daily photosynthetically active radiation/（mol·m⁻²·d⁻¹）
试验期 Experiment	天数 Days/d	最大值 Maximum	最小值 Minimum	均值 Mean	最大值 Maximum	最小值 Minimum	均值 Mean
1	32	35.87	27.47	33.51	16.86	3.61	10.65
2	36	36.38	31.62	34.51	19.58	0.001	8.18
3	30	34.83	31.25	33.26	19.30	7.67	13.64

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表 2 小白菜单株株高、叶数、叶面积、茎粗、根长、鲜重与光温效应、辐热积以及积温的拟合结果

Table 2. Individual plant height, leaf number, leaf area, stem diameter, root length, and fresh weight of B. chinensis as affected by LTF, TEP or GDD

指标 Index	方程 Equation	R²	RMSE	指标 Index	方程 Equation	R²	RMSE
株高 Plant height	23.539 3 EXP[−EXP （0.393 9−0.150 7 LTF）]	0.960	1.097	茎粗 Stem diameter	−16.657 9 EXP[−EXP （1.017 2−0.068 5 LTF）]	0.980	0.310
	−18.353 2/[1+（TEP/53.802 0）^{1.973 3}]+ 24.050 8	0.956	1.156		−17.041 5 EXP[−EXP （1.066 5−0.009 5 TEP）]	0.979	0.314
	−18.227 9/[1+（GDD/346.882 2）^{1.851 7}]+ 23.986 2	0.964	1.047		12.428 7 EXP[−EXP （0.950 0−0.001 7 GDD）]	0.985	0.263
叶数 Leaf number	−20.385 1/[1+（LTF/18.317 6）^{3.270 0}]+ 24.868 9	0.989	0.420	根长 Root length	−28.524 1/[1+（LTF/18.260 6）^{1.2605 9}]+ 32.544 8	0.976	0.755
	−29.309 3/[1+（TEP/154.911 0）^{2.998 7}]+ 33.748 2	0.987	0.451		−24.971 9/[1+（TEP/101.637 62）^{1.413 29}]+ 28.806 06	0.971	0.836
	−16.807 5/[1+（GDD/785.289 5）^{3.442 2}]+ 21.349 9	0.988	0.434		−24.030 76/[1+（GDD/659.621 19）^{1.338 13}]+ 27.959 84	0.973	0.802
叶面积 Leaf area	26 248 000 EXP[−EXP （2.613 8−0.014 5 LTF）]	0.978	39.761	鲜重 Fresh weight	8 347.241 8 EXP[−EXP （2.153 1−0.034 2 LTF）]	0.967	5.696
	30.496 0−1.419 1 TEP+0.054 9 TEP²	0.963	51.538		4 037 040 EXP[−EXP （2.680 0−0.002 43TEP）]	0.972	5.256
	34 100.942 0 EXP[−EXP （1.964 9−0.000 7 GDD）]	0.984	34.089		−1 006.914 6 EXP[−EXP （1.895 8−0.001 1 GDD）]	0.971	5.311

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表 3 基于光温效应、辐热积以及积温的小白菜单株株高、叶数、叶面积、茎粗、根长、鲜重模型检验结果

Table 3. Test results of LTF, TEP and GDD models on individual plant height, leaf number, leaf area, stem diameter, root length, and fresh weight of B. chinensis

指标　　 Index	拟合方法 Fitting method	R²	RMSE	RE（%）	指标　　 Index	拟合方法 Fitting method	R²	RMSE	RE（%）
株高 Plant heigh	LTF	0.946	1.106	6.79	茎粗 Stem diameter	LTF	0.936	0.540	12.66
	TEP	0.874	1.843	11.32		TEP	0.744	1.415	33.18
	GDD	0.943	1.200	7.38		GDD	0.897	0.712	16.69
叶数 Leaf number	LTF	0.966	0.697	8.24	根长 Root length	LTF	0.907	1.338	9.97
	TEP	0.346	6.586	77.89		TEP	0.763	2.494	18.59
	GDD	0.947	0.998	11.81		GDD	0.912	1.390	10.36
叶面积 Leaf area	LTF	0.981	34.393	11.21	鲜重 Fresh weight	LTF	0.984	3.733	11.83
	TEP	0.630	297.276	96.91		TEP	0.463	70.648	223.80
	GDD	0.891	109.891	35.82		GDD	0.922	10.637	33.69

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