WO2022142432A1 - 一种利用生菜叶绿素荧光参数预测光合气体交换参数方法 - Google Patents
一种利用生菜叶绿素荧光参数预测光合气体交换参数方法 Download PDFInfo
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- lettuce
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- gas exchange
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- 235000003228 Lactuca sativa Nutrition 0.000 title claims abstract description 36
- 241000208822 Lactuca Species 0.000 title claims abstract description 35
- 229930002875 chlorophyll Natural products 0.000 title claims abstract description 20
- 235000019804 chlorophyll Nutrition 0.000 title claims abstract description 20
- ATNHDLDRLWWWCB-AENOIHSZSA-M chlorophyll a Chemical compound C1([C@@H](C(=O)OC)C(=O)C2=C3C)=C2N2C3=CC(C(CC)=C3C)=[N+]4C3=CC3=C(C=C)C(C)=C5N3[Mg-2]42[N+]2=C1[C@@H](CCC(=O)OC\C=C(/C)CCC[C@H](C)CCC[C@H](C)CCCC(C)C)[C@H](C)C2=C5 ATNHDLDRLWWWCB-AENOIHSZSA-M 0.000 title claims abstract description 20
- 230000029553 photosynthesis Effects 0.000 title claims abstract description 20
- 238000010672 photosynthesis Methods 0.000 title claims abstract description 20
- 238000000034 method Methods 0.000 title claims abstract description 16
- 230000027756 respiratory electron transport chain Effects 0.000 claims abstract description 24
- 230000001419 dependent effect Effects 0.000 claims abstract description 7
- 230000000243 photosynthetic effect Effects 0.000 claims description 59
- 230000004044 response Effects 0.000 claims description 15
- 238000005259 measurement Methods 0.000 claims description 10
- 238000000611 regression analysis Methods 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 3
- 238000000746 purification Methods 0.000 claims 1
- 241000196324 Embryophyta Species 0.000 abstract description 10
- 238000011160 research Methods 0.000 abstract description 8
- 230000000875 corresponding effect Effects 0.000 description 18
- 238000004364 calculation method Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 239000000523 sample Substances 0.000 description 3
- 238000011282 treatment Methods 0.000 description 3
- 230000035479 physiological effects, processes and functions Effects 0.000 description 2
- 240000008415 Lactuca sativa Species 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 238000000799 fluorescence microscopy Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000004298 light response Effects 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 235000013311 vegetables Nutrition 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0098—Plants or trees
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N2021/635—Photosynthetic material analysis, e.g. chrorophyll
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
Definitions
- This technology discloses a method for predicting photosynthetic gas exchange parameters by using lettuce chlorophyll fluorescence parameters to reveal the intrinsic relationship between chlorophyll fluorescence parameters and photosynthetic gas exchange parameters, which can both characterize the photosynthetic capacity of plants.
- Lettuce has become one of the most commonly grown vegetables in the world because of its convenient consumption, rich nutrition, and certain medical and health functions. Therefore, research on high-yield cultivation of lettuce has been ongoing. In view of the fact that photosynthesis is the basis for constructing the yield of all crops, the research on the photosynthetic characteristics of lettuce has also become the focus of high-yield cultivation research of lettuce.
- the chlorophyll fluorescence parameter and the photosynthetic gas exchange parameter are two important different index systems that reflect the photosynthetic characteristics of plants, and they need to be calculated separately during research.
- the maximum net photosynthetic rate and its corresponding light intensity in the photosynthetic gas exchange parameters that is, the light saturation point, not only reflect the photosynthetic potential of the plant, but also reflect the plant's utilization range of light energy, which is particularly important in the research of photosynthetic physiology.
- the two are mainly tested by the Li-6400 photosynthesis measurement system for the light response (response of the net photosynthetic rate Pn to the light intensity PAR, PAR-Pn) curve test, and then the maximum net photosynthetic rate and the corresponding light intensity, that is, the light saturation point, are determined according to The fitted PAR-Pn response curve equation (where PAR is the independent variable and Pn is the dependent variable) is obtained.
- Chlorophyll fluorescence technology is known as a fast and non-invasive probe to study plant photosynthetic function, and is widely used in the study of plant photosynthetic physiology.
- the test system uses chlorophyll in the body as a natural probe to study and detect the photosynthetic physiological status of plants, and the measurement time is short, and multiple samples can be measured in a short time.
- the test system is usually a German-made modulated fluorescence imaging system (Imaging-PAM system), which includes the response curve of the apparent combined electron transfer rate ETR to the light intensity PAR and the curve equation fitting (PAR-ETR), wherein the apparent optical
- the combined electron transfer rate represents the speed of electron transfer in the photosynthetic electron transfer chain per unit time, which directly affects the size of the net photosynthetic rate, and the two are highly correlated.
- the maximum apparent combined electron transfer rate and the corresponding light intensity, that is, the light saturation point, were obtained according to the fitted PAR-ETR response curve equation (where PAR is the independent variable and ETR is the dependent variable). Then, can the maximum electron transfer rate ETR and the corresponding light intensity, that is, the light saturation point, in the simple and easy-to-measure chlorophyll fluorescence parameters be used to accurately characterize the maximum net photosynthetic rate and the corresponding light intensity, that is, the light saturation point, in the photosynthetic gas exchange parameters, so as to overcome the While the above photosynthetic gas exchange parameters are inconvenient to measure, they also reveal the intrinsic relationship between the two different index systems.
- This technology uses lettuce as the research object, and calculates the maximum net photosynthetic rate and the corresponding light saturation point, the maximum apparent photosynthetic electron transfer rate and the corresponding light saturation point of the same lettuce by fitting the PAR-Pn and ETR-ETR response curve equations, respectively. , and then, using the appropriate fitting equations, the relationship between the maximum net photosynthetic rate-maximum apparent photosynthetic electron transfer rate, the maximum net photosynthetic rate time saturation point-maximum apparent photosynthetic electron transfer rate time saturation point was respectively constructed, thereby revealing The intrinsic link between two different indicator systems.
- the purpose of the present technology is to provide a method for predicting the maximum electron transfer rate and the corresponding light saturation point in the photosynthetic gas exchange parameters respectively by using the maximum electron transfer rate and the corresponding light saturation point in the chlorophyll fluorescence parameters.
- the present invention mainly adopts the following technical solutions, a method for predicting the photosynthetic gas exchange parameters by utilizing the lettuce chlorophyll fluorescence parameter, which is carried out according to the following steps:
- this method selects the slow growth stage of lettuce in the early stage and the fast growth stage in the middle stage respectively for testing.
- the leaf ages of lettuce in the slow growth stage and the fast growth stage were 5-7 pieces and 11-13 pieces, respectively.
- step (2) the light intensity gradient set by the LI-6400XT portable photosynthesis instrument is 0, 50, 100, 150, 200, 400, 600, 800, 1000, 1200 ⁇ mol ⁇ m -2 ⁇ s -1 , each time The interval is 2-3min. Subsequently, the response curve of the apparent combined electron transfer rate of the same leaves to the light intensity was determined by using the chlorophyll fluorometer IMAGING-PAM.
- the light intensity gradient set by the Imaging-PAM system is 0, 42, 77, 135, 206, 250, 299, 372, 457, 582, 727 ⁇ mol ⁇ m -2 ⁇ s -1 , and each time The interval is 20s.
- the maximum apparent photosynthetic electron transfer rate and the corresponding light saturation point of lettuce which are easy to measure, can be used to predict the maximum net photosynthetic rate and the corresponding light saturation point that require higher calculation conditions.
- the invention selects the maximum apparent photosynthetic electron transfer rate and its light saturation point among the chlorophyll fluorescence parameters that are extremely related to it, the measurement time is short, and the measurement is less restricted by external conditions, and the maximum apparent photosynthetic electron transfer rate and its light saturation point are selected by constructing the maximum photosynthetic rate and its light saturation point.
- the point fitting equation predicts the maximum photosynthetic rate and its light saturation point of lettuce, which not only overcomes the inconvenience of measuring the above photosynthetic gas exchange parameters, but also reveals the intrinsic relationship between the two different index systems.
- Fig. 4 Fitted curve and equation for prediction of light saturation point corresponding to maximum net photosynthetic rate.
- the experimental site was in a greenhouse in Zhenjiang, and the cultivated lettuce was a year-round Italian bolting-resistant variety.
- the lettuce leaf age is about 6.5
- a calculation is made to represent the lettuce in the slow growth stage. 13 normal leaves with different sizes and growth were selected, and the PAR-Pn and PAR-ETR response curves were measured respectively, and the maximum apparent combined electron transfer rate ETR max , the light saturation point LSP' and the maximum net electron transfer rate were obtained by fitting the hyperbolic correction model.
- the regression coefficients a 1 , b 1 and a 2 , b 2 are 0.3178, 0.8361 and 0.3178, respectively.
- Table 1 Parameters of lettuce in slow growth stage
- the coefficient a 2 in b2 is very similar, and so is b 2 , which indicates that the corresponding light saturation point of the maximum net photosynthetic rate of lettuce at different growth stages can also be predicted by the same equation.
Abstract
一种利用生菜叶绿素荧光参数预测光合气体交换参数方法，属植物生理研究领域，其中，叶绿素荧光参数与光合气体交换参数均为表征植物光合能力的独立指标体系。通过同期分别测算生菜叶绿素荧光参数中最大表观光合电子传递速率及其光饱和点和光合气体交换参数中的最大净光合速率及其光饱和点，以叶绿素荧光参数为自变量X，光合气体交换参数为因变量Y，按Y＝aXb方程分别构建最大表观光合电子传递速率-最大净光合速率和最大表观光合电子传递速率时光饱和点-最大净光合速率时光饱和点的拟合方程，求出各自回归系数a和b，从而得到基于叶绿素荧光的部分参数预测光合气体交换的部分参数的方程，揭示两指标体系间的内在统一。
Description
本技术公布一种利用生菜叶绿素荧光参数预测光合气体交换参数方法，以揭示叶绿素荧光参数和光合气体交换参数这两个均可表征植物光合能力大小的不同指标体系间的内在联系，属于探究植物生理特征内在统一性的技术领域。
生菜因其食用方便、营养丰富，且具一定的医疗和保健功能，现已成为世界上最为普遍种植的蔬菜之一。因此，关于生菜高产栽培的研究一直在持续进行。鉴于光合作用是构建一切作物产量的基础，生菜光合特性的研究因而也成为生菜高产栽培研究的重点。目前，叶绿素荧光参数和光合气体交换参数分别是反映植物光合特性的两个重要的不同指标体系，在研究时需分别测算。其中，光合气体交换参数中的最大净光合速率及其相应光强即光饱和点既反映植物的光合潜力，又反映植物对光能的利用范围，在光合生理研究中尤为重要。目前，二者主要是通过Li-6400光合测定系统进行光响应(净光合速率Pn对光强PAR的响应，PAR-Pn)曲线测试，进而最大净光合速率及相应光强即光饱和点则根据拟合的PAR-Pn响应曲线方程(其中PAR为自变量，Pn为因变量)求得。因该方法测算精确，它已几乎成为当前近乎唯一的测算方法。但是，该方法对环境条件和测量时间要求较严，通常需在晴朗天气下的上午9：00-10：00进行，而每测量一个样本则需近25-30分钟，这样每天最多仅能测量3个样本。然而，很多研究常需设计多个处理，且每个处理还需设有3个以上重复，因此，不同处理的样本难以在短期内进行测定，即平行测定，最终影响研究结果的准确性。叶绿素荧光技术被称为研究植物光合功能的快速、无损伤探针，广泛应用在植物光合生理的研究中。它以体内叶绿素作为天然探针，研究和探测植物的光合生理状况，测量时间短，可在短时间内测定多个样本。该测试系统通常为德国产的调制荧光成像系统(Imaging-PAM系统)，它包括表观光合电子传递速率ETR对光强PAR的响应曲线及曲线方程拟合(PAR-ETR)，其中，表观光合电子传递速率表示单位时间内光合电子传递链中电子传递的速度，直接影响净光合速率的大小，二者相关性极强。而最大表观光合电子传递速率及相应光强即光饱和点则是根据拟合的PAR-ETR响应曲线方程(其中PAR为自变量，ETR为因变量)求得。那么，是否可以用简单易测的叶绿素荧光参数中的最大电子传递速率ETR及对应光强即光饱和点精确表征光合气体交换参数中最大净光合速率及对应光强即光饱和点，从而在克服以上光合气 体交换参数不便测量的同时，也揭示两个不同指标体系间的内在联系。
本技术利用生菜作为研究对象，通过拟合的PAR-Pn和ETR-ETR响应曲线方程，分别测算同一生菜的最大净光合速率及相应光饱和点和最大表观光合电子传递速率及相应光饱和点，然后，利用选用适宜的拟合方程，分别构建最大净光合速率-最大表观光合电子传递速率、最大净光合速率时光饱和点-最大表观光合电子传递速率时光饱和点间的关系，从而揭示两个不同指标体系间的内在联系。
发明内容
本技术目的是提供一种方法，利用叶绿素荧光参数中的最大电子传递速率及相应光饱和点分别预测光合气体交换参数中的最大电子传递速率及相应光饱和点。
为实现以上目标，本发明主要采用以下技术方案，一种利用生菜叶绿素荧光参数预测光合气体交换参数方法，按照下述步骤进行：
(1)为更全面地构建两个不同指标体系的内在联系，本方法分别选择了生菜前期慢速生长阶段和中期快速生长阶段进行测试。其中，慢速生长阶段和快速生长阶段生菜的叶龄数分别为5-7片和11-13片。
(2)在生菜的两个不同生长阶段，在晴朗天气的上午9：00-10：00，分别选取一定数量(n≥10)正常生长的叶片，利用LI-6400XT便携式光合仪，进行净光合速率对光照强度的响应曲线的测定。再利用Imaging-PAM系统，进行相对电子传递速率对光照强度的响应曲线的测定。
(3)将得到的不同叶片PAR-Pn响应曲线和不同叶片PAR-ETR响应曲线分别用双曲线修正模型进行拟合，从而求得一组最大净光合速率(Pn
max)及一组光饱和点(LSP)，以及另一组最大表观光合电子传递速率(ETR
max)及一组光饱和点(LSP’)。
(4)选用幂函数方程Y＝a
1X
b1，以ETR
max为自变量，Pn
max为因变量，将测算得到的两组值，按照相同叶片一一对应地回归分析，求出回归系数a
1和b
1。
选用幂函数方程Y＝a
2X
b2，以LSP’为自变量，LSP为因变量，将两组值也按照相同叶片一一对应地进行回归分析，求出回归系数a
2和b
2。
其中步骤(2)中，LI-6400XT便携式光合仪设置的光强梯度为0、50、100、150、200、400、600、800、1000、1200μmol·m
-2·s
-1，每次时间间隔为2-3min。随后利用叶绿素荧光仪IMAGING-PAM进行相同叶片的表观光合电子传递速率对光照强度的响应曲线的测定。
其中步骤(2)中，Imaging-PAM系统设置的光强梯度为0、42、77、135、206、250、 299、372、457、582、727μmol·m
-2·s
-1，每次时间间隔为20s。
这样，便可利用易于测算的生菜最大表观光合电子传递速率及相应光饱和点预测测算条件要求较高的最大净光合速率及相应光饱和点。
本发明的优点
目前,光合气体交换参数中的最大光合速率及其光饱和点的测算通常十分耗时，测定时受限条件也多。本发明选择与其极相关且测量耗时短、测定时受外界条件限制较少的叶绿素荧光参数中的最大表观光合电子传递速率及其光饱和点，通过构建其与最大光合速率及其光饱和点拟合方程，预测生菜的最大光合速率及其光饱和点，在克服以上光合气体交换参数不便测量的同时，也揭示两个不同指标体系间的内在联系。
图1最大净光合速率预测的拟合曲线及方程；
图2最大净光合速率对应的光饱和点预测的拟合曲线及方程；
图3最大净光合速率预测的拟合曲线和方程；
图4最大净光合速率对应的光饱和点预测的拟合曲线和方程。
实验地点在镇江的某温室大棚内，栽培的生菜为全年意大利耐抽苔品种。在生菜叶龄为6.5左右时，进行一次代表生菜处于慢速生长阶段的测算。选取13片大小不同、生长的正常的叶片，分别测定PAR-Pn和PAR-ETR响应曲线，利用双曲线修正模型拟合得到最大表观光合电子传递速率ETR
max及光饱和点LSP’和最大净光合速率Pn
max及光饱和点LSP(表1)。分别按照幂函数方程Pn
max＝a
1ETR
max
b1和LSP＝a
2LSP’
b2进行拟合(图1)，求得回归系数a
1、b
1和a
2、b
2分别为0.3178、0.8361和0.2159、1.2847，系数代入后得到预测最大净光合速率的公式：Pn
max＝0.3178*ETR
max
0.8361(图1)及其预测最大净光合速率对应的光饱和点的公式LSP＝0.2159*LSP’
1.2847(图2)。
表1：生菜处于慢速生长阶段的各参数
在生菜叶龄为12.0左右时，进行一次代表生菜处于快速生长阶段的测算。选取13片大小不同、生长的正常的叶片，分别按照慢速生长阶段的测算方法，获取相关数据(表2)后，得到预测最大净光合速率的公式：Pn
max＝0.3174*ETR
max
0.8368(图3)及其预测最大净光合速率对应的光饱和点的公式LSP＝0.2144*LSP’
1.2836(图4)。
表2生菜处于快速生长阶段的各参数
图1和图3显示，生菜处于两个不同生长阶段时，最大净光合速率预测方程Pn
max ＝a
1*ETRmax
b1中的系数a
1极其相近，b
1也是如此，这表明不同生长阶段生菜的最大净光合速率可用同一方程预测，因此，本技术方法则分别以两个不同生长阶段a
1和b
1的均值，作为生菜整个生长阶段预测方程的系数a
1和b
1，即a
1＝0.3176，b
1＝0.8365，因而最大净光合速率的预测方程公式为Pn
max＝0.3176*ETRmax
0.8365；生菜处于两个不同生长阶段时，最大净光合速率相应光饱和点的预测方程LSP＝a
2*LSP
b2中的系数a
2极其相近，b
2也是如此，这表明不同生长阶段生菜的最大净光合速率相应光饱和点也可用同一方程预测，因此，本技术方法则分别以两个不同生长阶段a
2和b
2的均值，作为生菜整个生长阶段预测方程的系数a
2和b
2，即a
2＝0.2152，b
2＝1.2844，因而最大净光合速率相应光饱和点的预测方程为LSP＝0.2152*LSP’
1.2844。因此，可利用生菜叶绿素荧光参数中部分参数预测光合气体参数中的部分参数，这一方法应同样适用于其他植物的预测。
Claims (3)
- 一种利用生菜叶绿素荧光参数预测光合气体交换参数方法，其特征在于按照下述步骤进行：(1)为更全面地构建两个不同指标体系的内在联系，本方法分别选择了生菜前期慢速生长阶段和中期快速生长阶段进行测试；其中，慢速生长阶段和快速生长阶段生菜的叶龄数分别为5-7片和11-13片；(2)在生菜的两个不同生长阶段，在晴朗天气的上午9：00-10：00，分别选取一定数量(n≥10)正常生长的叶片，利用LI-6400XT便携式光合仪，分别进行净光合速率对光照强度的响应曲线的测定；再利用Imaging-PAM系统，进行相对电子传递速率对光照强度的响应曲线的测定；(3)将得到的不同叶片PAR-Pn响应曲线和不同叶片PAR-ETR响应曲线分别用双曲线修正模型进行拟合，从而求得一组最大净光合速率(Pn max)及一组光饱和点(LSP)，以及另一组最大表观光合电子传递速率(ETR max)及一组光饱和点(LSP’)；(4)选用幂函数方程Y＝a 1X b1，以ETR max为自变量，Pn max为因变量，将测算得到的两组值，按照相同叶片一一对应地回归分析，求出回归系数a 1和b 1；选用幂函数方程Y＝a 2X b2，以LSP’为自变量，LSP为因变量，将两组值也按照相同叶片一一对应地进行回归分析，求出回归系数a 2和b 2。
- 根据权利要求1所述的一种利用生菜叶绿素荧光参数预测光合气体交换参数方法，其特征在于其中步骤(2)中，LI-6400XT便携式光合仪设置的光强梯度为0、50、100、150、200、400、600、800、1000、1200μmol·m -2·s -1，每次时间间隔为2-3min。
- 根据权利要求1所述的一种利用生菜叶绿素荧光参数预测光合气体交换参数方法，其特征在于其中步骤(2)中，Imaging-PAM系统设置的光强梯度为0、42、77、135、206、250、299、372、457、582、727μmol·m -2·s -1，每次时间间隔为20s。
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