Multi-factor photosynthetic rate prediction model by fusion of photosynthetic response model and theory-guided neural network

doi:10.17521/cjpe.2024.0288

Abstract

Abstract:

Aims In recent years, the ever increasing greenhouse gas (GHG) emissions and extreme weather events had significantly impacted plant photosynthesis. Photosynthesis is closely related to plant growth and development, with photosynthetic rate is a key indicator of plant health, which has been widely used in predicting global carbon cycle dynamics. The net photosynthesis rate is also an important parameter in calibrating agriculture facility. Therefore, accurate prediction of plant photosynthesis rate is important to agriculture, forestry and grassland research.

Methods We used photosynthesis meter to obtain photosynthetic data of common reed (Phragmites australis) and smooth cordgrass (Spartina alterniflora) under different environmental conditions, we then fitted seven single-factor photosynthetic response models, and developed multifactorial photosynthetic rate prediction model using theory-guided neural network (TgNN).

Important findings All existing single-factor photosynthetic response models show good performances in fitting photosynthetic data but lack theoretical research value; whereas the multifactor photosynthetic model based on TgNN shows good predictability and generality. Our contribution provides a new avenue for calibrating more accurate and reliable models for predicting plant photosynthetic rate.

Key words: photosynthetic prediction model, neural network, photosynthetic response model, grey box model

SU Chen-Fei, TIAN Wei, ZHANG Nan, TANG Long, ZHAO Yu-Wei, WANG Yao. Multi-factor photosynthetic rate prediction model by fusion of photosynthetic response model and theory-guided neural network[J]. Chin J Plant Ecol, 2026, 50(1): 173-187.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2024.0288

https://www.plant-ecology.com/EN/Y2026/V50/I1/173

Figures/Tables 18

References 20

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模型 Model	叶片温度 T_leaf (℃)	初始斜率 α	最大净光合速率 A_max (µmol·m^-2·s^-1)	光补偿点 I_c (µmol·m^-2·s^-1)	暗呼吸速率 R_d (µmol·m^-2·s^-1)	模型拟合的决定系数 R²
直角双曲线模型 Rectangular hyperbola model	20	0.055 4	76.109 1	108.260 3	5.561 6	0.983 7
	25	0.049 4	81.143 2	62.736 8	2.985 4	0.989 0
	30	0.059 2	78.160 6	97.101 2	5.355 6	0.975 6
	35	0.059 5	77.629 1	100.994 0	5.574 3	0.976 0
	40	0.054 0	76.456 4	98.070 3	4.952 9	0.983 6
非直角双曲线模型 Non-rectangular hyperbolic model	20	0.033 0	43.819 3	70.154 9	2.314 6	0.989 6
	25	0.035 7	52.939 4	29.800 2	1.060 3	0.990 2
	30	0.031 0	39.988 4	33.141 6	1.028 4	0.992 7
	35	0.031 9	41.794 3	45.647 5	1.460 1	0.990 5
	40	0.036 4	53.005 1	59.875 5	2.174 3	0.985 1
直角双曲线修正模型 Modified model of rectangular hyperbola	20	0.040 2	37.973 3	91.036 5	3.584 2	0.988 6
	25	0.040 5	42.891 8	43.780 7	1.747 9	0.989 8
	30	0.043 6	39.648 7	86.064 3	3.670 5	0.986 9
	35	0.043 5	39.269 2	88.745 7	3.775 4	0.985 7
	40	0.039 5	38.420 6	77.286 2	2.992 2	0.987 6
指数模型 Exponential Model	20	0.044 2	47.011 6	25.302 6	1.103 9	0.985 8
	25	0.042 2	51.911 4	25.027 3	1.045 1	0.989 6
	30	0.047 7	48.645 4	23.276 0	1.098 4	0.979 4
	35	0.047 5	48.226 8	23.476 4	1.102 8	0.979 6
	40	0.043 6	47.714 3	25.250 0	1.089 4	0.985 4

模型 Model	叶片温度 T_leaf (℃)	初始斜率 α	最大净光合速率 A_max (µmol·m^-2·s^-1)	光补偿点 I_c (µmol·m^-2·s^-1)	暗呼吸速率 R_d (µmol·m^-2·s^-1)	模型拟合的决定系数 R²
直角双曲线模型 Rectangular hyperbola model	20	0.055 4	76.109 1	108.260 3	5.561 6	0.983 7
	25	0.049 4	81.143 2	62.736 8	2.985 4	0.989 0
	30	0.059 2	78.160 6	97.101 2	5.355 6	0.975 6
	35	0.059 5	77.629 1	100.994 0	5.574 3	0.976 0
	40	0.054 0	76.456 4	98.070 3	4.952 9	0.983 6
非直角双曲线模型 Non-rectangular hyperbolic model	20	0.033 0	43.819 3	70.154 9	2.314 6	0.989 6
	25	0.035 7	52.939 4	29.800 2	1.060 3	0.990 2
	30	0.031 0	39.988 4	33.141 6	1.028 4	0.992 7
	35	0.031 9	41.794 3	45.647 5	1.460 1	0.990 5
	40	0.036 4	53.005 1	59.875 5	2.174 3	0.985 1
直角双曲线修正模型 Modified model of rectangular hyperbola	20	0.040 2	37.973 3	91.036 5	3.584 2	0.988 6
	25	0.040 5	42.891 8	43.780 7	1.747 9	0.989 8
	30	0.043 6	39.648 7	86.064 3	3.670 5	0.986 9
	35	0.043 5	39.269 2	88.745 7	3.775 4	0.985 7
	40	0.039 5	38.420 6	77.286 2	2.992 2	0.987 6
指数模型 Exponential Model	20	0.044 2	47.011 6	25.302 6	1.103 9	0.985 8
	25	0.042 2	51.911 4	25.027 3	1.045 1	0.989 6
	30	0.047 7	48.645 4	23.276 0	1.098 4	0.979 4
	35	0.047 5	48.226 8	23.476 4	1.102 8	0.979 6
	40	0.043 6	47.714 3	25.250 0	1.089 4	0.985 4

模型 Model	叶片温度 T_leaf (℃)	初始斜率 α	最大净光合速率 A_max (µmol·m^-2·s^-1)	光补偿点 I_c (µmol·m^-2·s^-1)		暗呼吸速率 R_d (µmol·m^-2·s^-1)	模型拟合的决定系数 R²
直角双曲线模型 Rectangular hyperbola model	20	0.094 3	61.488 0	107.877 6		8.732 0	0.962 2
	25	0.089 3	68.372 4	120.464 5		9.298 3	0.966 2
	30	0.102 7	66.953 5	107.877 5		9.508 1	0.961 5
	35	0.104 8	68.320 1	107.877 6		9.702 2	0.960 3
	40	0.096 4	62.854 3	107.877 5		8.926 0	0.961 1
非直角双曲线模型 Non-rectangular hyperbolic model	20	0.092 9	61.667 2	107.155 9		8.568 8	0.962 2
	25	0.042 4	39.048 8	103.921 2		4.400 1	0.992 7
	30	0.045 6	39.765 2	84.978 2		3.864 5	0.989 3
	35	0.046 5	40.576 8	84.978 5		3.943 4	0.989 4
	40	0.042 8	37.330 6	84.978 1		3.627 9	0.988 9
直角双曲线修正模型 Modified model of rectangular hyperbola	20	0.055 4	32.908 7	97.673 4		5.216 4	0.980 8
	25	0.058 1	34.590 9	120.743 9		6.720 5	0.984 6
	30	0.060 3	35.833 9	97.673 3		5.680 0	0.981 1
	35	0.061 6	36.565 2	97.673 5		5.796 0	0.981 3
	40	0.056 6	33.640 0	97.673 3		5.332 3	0.980 2
指数模型 Exponential model	20	0.063 4	37.039 3	19.380 2		1.207 8	0.971 5
	25	0.062 3	40.246 5	19.741 8		1.212 0	0.974 2
	30	0.069 0	40.331 7	17.773 8		1.207 8	0.972 3
	35	0.061 6	36.565 2	97.673 5		5.796 0	0.980 8
	40	0.064 8	37.862 4	18.952 0		1.207 8	0.978 8
	40	0.043 6	47.714 3	25.250 0	1.089 4		0.985 4

模型 Model	叶片温度 T_leaf (℃)	初始斜率 α	最大净光合速率 A_max (µmol·m^-2·s^-1)	光补偿点 I_c (µmol·m^-2·s^-1)		暗呼吸速率 R_d (µmol·m^-2·s^-1)	模型拟合的决定系数 R²
直角双曲线模型 Rectangular hyperbola model	20	0.094 3	61.488 0	107.877 6		8.732 0	0.962 2
	25	0.089 3	68.372 4	120.464 5		9.298 3	0.966 2
	30	0.102 7	66.953 5	107.877 5		9.508 1	0.961 5
	35	0.104 8	68.320 1	107.877 6		9.702 2	0.960 3
	40	0.096 4	62.854 3	107.877 5		8.926 0	0.961 1
非直角双曲线模型 Non-rectangular hyperbolic model	20	0.092 9	61.667 2	107.155 9		8.568 8	0.962 2
	25	0.042 4	39.048 8	103.921 2		4.400 1	0.992 7
	30	0.045 6	39.765 2	84.978 2		3.864 5	0.989 3
	35	0.046 5	40.576 8	84.978 5		3.943 4	0.989 4
	40	0.042 8	37.330 6	84.978 1		3.627 9	0.988 9
直角双曲线修正模型 Modified model of rectangular hyperbola	20	0.055 4	32.908 7	97.673 4		5.216 4	0.980 8
	25	0.058 1	34.590 9	120.743 9		6.720 5	0.984 6
	30	0.060 3	35.833 9	97.673 3		5.680 0	0.981 1
	35	0.061 6	36.565 2	97.673 5		5.796 0	0.981 3
	40	0.056 6	33.640 0	97.673 3		5.332 3	0.980 2
指数模型 Exponential model	20	0.063 4	37.039 3	19.380 2		1.207 8	0.971 5
	25	0.062 3	40.246 5	19.741 8		1.212 0	0.974 2
	30	0.069 0	40.331 7	17.773 8		1.207 8	0.972 3
	35	0.061 6	36.565 2	97.673 5		5.796 0	0.980 8
	40	0.064 8	37.862 4	18.952 0		1.207 8	0.978 8
	40	0.043 6	47.714 3	25.250 0	1.089 4		0.985 4

模型 Model	叶片温度 T_leaf (℃)	初始斜率 α	最大净光合速率 A_max (µmol·m^-2·s^-1)	CO₂补偿点 $\Gamma *$(µmol·m^-2·s^-1)	光呼吸速率 R_p (µmol·m^-2·s^-1)	模型拟合的决定系数 R²
直角双曲线模型 Rectangular hyperbola model	20	0.183 2	119.943 6	106.343 3	16.737 4	0.998 5
	25	0.193 8	116.599 2	74.536 9	12.861 2	0.996 1
	30	0.207 5	115.981 9	77.440 0	14.119 1	0.993 7
	35	0.230 9	113.510 7	99.638 3	19.009 4	0.983 6
	40	0.202 5	111.775 0	101.130 7	17.300 0	0.998 8
Michaelis-Menten模型 Michaelis-Menten model	20	-	119.943 6	106.343 3	16.737 4	0.998 5
	25	-	116.599 2	74.536 9	12.861 2	0.996 1
	30	-	115.981 9	77.440 0	14.119 1	0.993 7
	35	-	113.510 7	99.638 3	19.009 4	0.983 6
	40	-	111.775 0	101.130 7	17.300 0	0.998 8
直角双曲线修正模型 Modified model of rectangular hyperbola	20	0.153 3	41.087 1	108.154 3	15.344 0	0.998 8
	25	0.159 7	44.594 2	74.905 0	11.331 9	0.997 2
	30	0.174 1	46.207 5	77.867 5	12.638 7	0.994 6
	35	0.179 5	40.513 9	101.701 9	16.789 8	0.986 6
	40	0.169 4	41.739 2	102.650 3	15.800 8	0.999 1