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CN112858240A - Rapid field diagnosis method for drought stress of sugarcane - Google Patents

Rapid field diagnosis method for drought stress of sugarcane Download PDF

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CN112858240A
CN112858240A CN202110145055.1A CN202110145055A CN112858240A CN 112858240 A CN112858240 A CN 112858240A CN 202110145055 A CN202110145055 A CN 202110145055A CN 112858240 A CN112858240 A CN 112858240A
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sugarcane
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drought stress
drought
light
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CN112858240B (en
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安东升
严程明
徐磊
孔冉
苏俊波
窦美安
徐志军
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Zhanjiang Experimental Station Chinese Academy of Tropical Agricultural Sciences
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    • G01N21/62Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
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    • GPHYSICS
    • G01MEASURING; TESTING
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    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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Abstract

The invention discloses a field rapid diagnosis method for drought stress of sugarcane, which comprises the following steps of firstly carrying out material, determination index and test design in the production of the sugarcane, wherein the material, the determination index and the test design are divided into the following tests: test one: barrel test 1; and (2) test II: a barrel planting test 2; and (3) test III: planting in a field; the load test 1 is to select plants which are processed without stress in different planting periods and grow uniformly and consistently, and to determine the light quantum efficiency and Fv/Fm under three light intensity gradients (PAR285 mu mol-2 s-1, PAR625 mu mol-2 s-1 and PAR1150 mu mol-2 s-1) by adopting an artificial light source; the specification of the cultivation barrel is that the diameter of the barrel opening is 40cm, the diameter of the barrel bottom is 32cm, and the barrel height is 40 cm. According to the field rapid diagnosis method for the sugarcane drought stress, the response rule of the sugarcane leaf photon efficiency and the drought stress under the field condition is described through a multipoint measurement and fitting modeling method, and the rapid diagnosis of the drought stress in sugarcane production is realized.

Description

Rapid field diagnosis method for drought stress of sugarcane
Technical Field
The invention relates to the technical field related to sugarcane cultivation, in particular to a field rapid diagnosis method for sugarcane drought stress.
Background
As an important sugar crop, 80% of sugarcane is planted in a dry farmland in subtropical regions, seasonal drought becomes the second major factor limiting sugarcane production, seasonal drought in southwest south China, which mainly comprises autumn drought and winter-spring continuous drought, greatly influences seedling growth and yield formation, the traditional physiological index detection method is complicated in steps and long in time, and serves as a probe for rapidly and nondestructively detecting photosynthesis and photoprotection, and the light quantum efficiency indirectly reflects the response of a photosynthetic system channel determining yield and transpiration to drought stress.
Disclosure of Invention
The invention aims to provide a field rapid diagnosis method for sugarcane drought stress, which aims to solve the problem that the traditional detection method takes too long time to affect the growth and yield formation of seedlings in seasonal drought, which is proposed by the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a rapid diagnosis method for drought stress of sugarcane in the field comprises the following steps of firstly carrying out material, determination index and test design, wherein the material, the determination index and the test design are divided into the following tests:
test one: the method comprises the following steps of (1) carrying out a barreled test, wherein the barreled test 1 is to select plants which are subjected to non-stress treatment in different planting periods and grow uniformly and consistently, and determine the light quantum efficiency and Fv/Fm under three light intensity gradients (PAR285 mu mol-2 s-1, PAR625 mu mol-2 s-1 and PAR1150 mu mol-2 s-1) by adopting an artificial light source;
and (2) test II: a barrel planting test 2;
and (3) test III: and (5) planting in a field.
Preferably, the specification of the cultivation barrel is that the diameter of a barrel opening is 40cm, the diameter of a barrel bottom is 32cm, the height of the barrel is 40cm, the cultivation barrel is placed with reference to the planting distance of the field sugarcane, the placing density is 6 barrels/m 2, 3 segments of seed stems are planted in each barrel, 1 bud is planted in each segment, and 10 barrels are planted in each variety; selecting the sugarcane in normal growth, measuring the rated light intensity and the light quantum efficiency at different temperatures, and establishing a light-temperature correction model through curve fitting.
Preferably, the planting mode of the barrel planting test 2 is the same as that of the barrel loading test 1, a natural drought stress test is carried out, the light quantum efficiency and the relative water content of soil under different water gradients are measured, a drought stress response model is established by using the temperature correction value of the light quantum efficiency and the photosynthetic active radiation, and a drought stress index is fitted.
Preferably, the field planting is natural drought treatment, water covering treatment is carried out according to different drought degrees, each treatment is repeated for 3 times, and each community is 12m2Measuring the light quantum efficiency of the sugarcane leaves and the relative water content of soil at the roots of the plants under different light temperature backgrounds, and analyzing the 1:1 linear conformity and accuracy of the calculated value and the measured value of the light quantum efficiency.
Preferably, the rapid diagnosis method comprises the following steps of establishing a standard model after the materials, the measured indexes and the test design, wherein the standard model is established by the following steps:
the method comprises the following steps: a light-temperature correction model of the light quantum efficiency of the sugarcane leaves;
step two: a drought stress response model of the sugarcane leaf photon efficiency;
step three: verifying the model;
step four: and (5) field operation.
Preferably, the relationship between the photon efficiency and the temperature and illumination under different light temperature conditions in the first step is described as follows:
Figure RE-GDA0003023469070000031
in the formula (1), T is the actual air temperature (DEG C); phi is the photon efficiency at air temperature T; phi b and phi a are respectively basic and variable phi, and the relation is phi b + phi a To phi To; tmin, To and Tmax are three base point temperatures for sugarcane growth, and are respectively determined as 12 ℃, 28 ℃ and 43 ℃ through curve parameter fitting;
Figure RE-GDA0003023469070000032
Figure RE-GDA0003023469070000033
due to the existence of multiple electron transfer paths, even if the photosynthetic rate of the leaves is reduced to zero, the electron transfer is still carried out in the leaves, so that the phi isbLAnd phibHThe fundamental photon efficiencies at low and high temperatures, respectively; aL, bL、 aHAnd bHThe fitting values of the four empirical coefficients are 0.678 and 7.6 multiplied by 10 respectively-40.672 and 5.6X 10-4
Preferably, the curve is established between the light quantum efficiency and the photosynthetically active radiation under different moisture gradients after the temperature correction in the two steps, so that the change rule of the light quantum efficiency under different temperature, light and water combinations can be reflected,
Figure RE-GDA0003023469070000034
wherein the fitting parameter epsilon is a drought stress index, and the formula of the drought stress index with the change of the moisture gradient is as follows:
Figure RE-GDA0003023469070000035
wherein rSWC is the relative water content of soil, rSWCc is the relative water content of the critical lower limit soil, the rSWCc values of the new table sugar No. 22 and the new table sugar No. 16 are respectively determined to be 30% and 20% according to tests, epsilon (0) is an initial value without drought stress, the epsilon (0) values of the new table sugar No. 22 and the new table sugar No. 16 are respectively determined to be 6.395 and 5.785 according to the tests, and the fitting values of empirical coefficients c and d of the new table sugar No. 22 and the new table sugar No. 16 are respectively 14.25 and 9.68, 34.82 and 21.77.
Preferably, the third step is to substitute the environmental parameters of the second test into the calculation phi (PAR, T), the determination coefficients (r2) between phi (PAR, T) of the new table sugar No. 22 and the new table sugar No. 16 and the measured values based on the 1:1 line are respectively 0.98 and 0.96, and the relative regression estimation standard errors (rRMSE) are respectively 3.66% and 5.74%, which indicates that the model can better predict the actual light quantum efficiency in the field, and select the new table sugar No. 22 for yield verification in production, when the relative water content of soil is reduced to T1 (35-45%), T1 (20-30%), T1 (10-20%) and T1 (3-10%), the water is supplemented to the normal level, the production is tested when the product is to be received, and if the emergence rate is greatly influenced by spring drought, the yield is respectively reduced by 1.3%, 13.9%, 25.9% and 48.3% compared with the yield of full irrigation; if the autumn drought occurs, the jointing and the maturity of the sugarcane are influenced, and the yield is respectively reduced by 4.9%, 10.1%, 14.8% and 21.8% compared with the full irrigation; if 7< epsilon > is less than or equal to 9, the light drought is, 9< epsilon > is less than or equal to 13, the medium drought is, and the heavy drought is, epsilon > 13.
Preferably, the fourth step is that 10 plants are randomly selected in each field, a portable fluorescence instrument is used for measuring the light quantum efficiency phi (PAR, T) of natural stable light adaptation under sunlight in the morning, a black adhesive tape is used for wrapping the photoreaction measuring site, and F is measured after 30minv/FmAnd reversely deducing the drought stress index epsilon according to the environmental light temperature data, judging the drought occurrence degree, and performing preliminary disaster damage estimation.
Compared with the prior art, the invention has the beneficial effects that: according to the field rapid diagnosis method for the sugarcane drought stress, the response rule of the sugarcane leaf photon efficiency and the drought stress under the field condition is described by a multipoint measurement and fitting modeling method, and the rapid diagnosis of the drought stress in sugarcane production is realized.
Detailed Description
The following will clearly and completely describe the technical solutions in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that: a method for quickly diagnosing drought stress of sugarcane in field includes such steps as preparing raw materials, measuring indexes and test design, which are divided into the following tests:
test one: the method comprises the following steps of (1) carrying out a barreled test, wherein the barreled test 1 is to select plants which are subjected to non-stress treatment in different planting periods and grow uniformly and consistently, and determine the light quantum efficiency and Fv/Fm under three light intensity gradients (PAR285 mu mol-2 s-1, PAR625 mu mol-2 s-1 and PAR1150 mu mol-2 s-1) by adopting an artificial light source;
and (2) test II: a barrel planting test 2;
and (3) test III: and (5) planting in a field.
The specification of the cultivation barrel is that the diameter of the barrel opening is 40cm, the diameter of the barrel bottom is 32cm, the barrel height is 40cm, the cultivation barrel is placed with reference to the planting distance of the field sugarcane, the placing density is 6 barrels/m 2, 3 sections of seed stems are planted in each barrel, 1 bud is planted in each section, and 10 barrels are planted in each variety; selecting the sugarcane in normal growth, measuring the rated light intensity and the light quantum efficiency at different temperatures, and establishing a light-temperature correction model through curve fitting.
The planting mode of the barrel planting test 2 is the same as that of the barrel loading test 1, a natural drought stress test is carried out, the light quantum efficiency and the relative water content of soil under different water gradients are measured, a drought stress response model is established by using the temperature correction value of the light quantum efficiency and the photosynthetic active radiation, and a drought stress index is fitted.
The field planting is natural drought treatment, water covering treatment is carried out according to different drought degrees, each treatment is repeated for 3 times, and each cell is 12m2Measuring the light quantum efficiency of the sugarcane leaves and the relative water content of soil at the roots of the plants under different light temperature backgrounds, and analyzing the 1:1 linear conformity and accuracy of the calculated value and the measured value of the light quantum efficiency.
The rapid diagnosis method comprises the following steps of establishing a standard model after materials, measured indexes and test design, wherein the standard model is established by the following steps:
the method comprises the following steps: a light-temperature correction model of the light quantum efficiency of the sugarcane leaves;
step two: a drought stress response model of the sugarcane leaf photon efficiency;
step three: verifying the model;
step four: and (5) field operation.
The relation between the light quantum efficiency and the temperature and illumination under different light temperature conditions is described as follows:
Figure RE-GDA0003023469070000061
in the formula (1), T is the actual air temperature (DEG C); phi is the photon efficiency at air temperature T; phi b and phi a are respectively basic and variable phi, and the relation is phi b + phi a To phi To; tmin, To and Tmax are three base point temperatures for sugarcane growth, and are respectively determined as 12 ℃, 28 ℃ and 43 ℃ through curve parameter fitting;
Figure RE-GDA0003023469070000062
Figure RE-GDA0003023469070000063
due to the existence of multiple electron transfer paths, even if the photosynthetic rate of the leaves is reduced to zero, the electron transfer is still carried out in the leaves, so that the phi isbLAnd phibHThe fundamental photon efficiencies at low and high temperatures, respectively; aL, bL、 aHAnd bHThe fitting values of the four empirical coefficients are 0.678 and 7.6 multiplied by 10 respectively-40.672 and 5.6X 10-4
The curve is established between the light quantum efficiency and the photosynthetically active radiation under different moisture gradients after temperature correction for two steps, so that the change rule of the light quantum efficiency under different temperature, light and water combinations can be reflected,
Figure RE-GDA0003023469070000064
wherein the fitting parameter epsilon is a drought stress index, and the formula of the drought stress index with the change of the moisture gradient is as follows:
Figure RE-GDA0003023469070000071
wherein rSWC is the relative water content of soil, rSWCc is the relative water content of the critical lower limit soil, the rSWCc values of the new table sugar No. 22 and the new table sugar No. 16 are respectively determined to be 30% and 20% according to tests, epsilon (0) is an initial value without drought stress, the epsilon (0) values of the new table sugar No. 22 and the new table sugar No. 16 are respectively determined to be 6.395 and 5.785 according to the tests, and the fitting values of empirical coefficients c and d of the new table sugar No. 22 and the new table sugar No. 16 are respectively 14.25 and 9.68, 34.82 and 21.77.
Step three, substituting environmental parameters of the test two into the calculation phi (PAR, T), wherein the determination coefficients (r2) between phi (PAR, T) of the new table sugar No. 22 and the new table sugar No. 16 and the measured values based on a 1:1 line are 0.98 and 0.96 respectively, and the relative regression estimation standard errors (rRMSE) are 3.66 percent and 5.74 percent respectively, so that the model can better predict the actual field light quantum efficiency, selecting the new table sugar No. 22 in production to verify the yield, supplementing water to a normal level when the relative water content of soil is reduced to T1 (35-45 percent), T1 (20-30 percent), T1 (10-20 percent) and T1 (3-10 percent), testing the yield when the product is to be received, and if spring drought greatly affects the emergence rate, respectively reducing the yield by 1.3 percent, 13.9 percent, 25.9 percent, 48.3 percent compared with full irrigation; if the autumn drought occurs, the jointing and the maturity of the sugarcane are influenced, and the yield is respectively reduced by 4.9%, 10.1%, 14.8% and 21.8% compared with the full irrigation; if 7< epsilon > is less than or equal to 9, the light drought is, 9< epsilon > is less than or equal to 13, the medium drought is, and the heavy drought is, epsilon > 13.
Selecting 10 plants at random in each field, measuring the light quantum efficiency phi (PAR, T) of natural stable light adaptation under sunlight in the morning by using a portable fluorometer, wrapping the photoreaction measuring site by using a black adhesive tape, and measuring F after 30minv/FmAccording to the ambient light temperatureAnd (5) reversely deducing the drought stress index epsilon from the data, judging the drought occurrence degree, and performing primary disaster damage estimation.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk. It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and all the changes or substitutions should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (9)

1. A field rapid diagnosis method for sugarcane drought stress is characterized by comprising the following steps: the rapid diagnosis method for drought in sugarcane production comprises the following steps of firstly carrying out material, determination index and test design, wherein the material, the determination index and the test design are divided into the following tests:
test one: the method comprises the following steps of (1) carrying out a barreled test, wherein the barreled test 1 is to select plants which are subjected to non-stress treatment in different planting periods and grow uniformly and consistently, and determine the light quantum efficiency and Fv/Fm under three light intensity gradients (PAR285 mu mol-2 s-1, PAR625 mu mol-2 s-1 and PAR1150 mu mol-2 s-1) by adopting an artificial light source;
and (2) test II: a barrel planting test 2;
and (3) test III: and (5) planting in a field.
2. The field rapid diagnosis method for drought stress of sugarcane according to claim 1, characterized in that: the specification of the cultivation barrel is that the diameter of the barrel opening is 40cm, the diameter of the barrel bottom is 32cm, the barrel height is 40cm, the cultivation barrel is placed with reference to the planting distance of the field sugarcane, the placing density is 6 barrels/m 2, 3 sections of seed stems are planted in each barrel, 1 bud is planted in each section, and 10 barrels are planted in each variety; selecting the sugarcane in normal growth, measuring the rated light intensity and the light quantum efficiency at different temperatures, and establishing a light-temperature correction model through curve fitting.
3. The field rapid diagnosis method for drought stress of sugarcane according to claim 1, characterized in that: the planting mode of the barrel planting test 2 is the same as that of the barrel loading test 1, a natural drought stress test is carried out, the light quantum efficiency and the relative water content of soil under different water gradients are measured, a drought stress response model is established by using the temperature correction value of the light quantum efficiency and photosynthetic active radiation, and a drought stress index is fitted.
4. A sugarcane drought stress field speed as claimed in claim 1A rapid diagnostic method characterized by: the field planting is natural drought treatment, water covering treatment is carried out according to different drought degrees, each treatment is repeated for 3 times, and each district is 12m2Measuring the light quantum efficiency of the sugarcane leaves and the relative water content of soil at the roots of the plants under different light temperature backgrounds, and analyzing the 1:1 linear conformity and accuracy of the calculated value and the measured value of the light quantum efficiency.
5. The field rapid diagnosis method for drought stress of sugarcane according to claim 1, characterized in that: the rapid diagnosis method comprises the following steps of establishing a standard model after materials, measuring indexes and test design, wherein the standard model is established by the following steps:
the method comprises the following steps: a light-temperature correction model of the light quantum efficiency of the sugarcane leaves;
step two: a drought stress response model of the sugarcane leaf photon efficiency;
step three: verifying the model;
step four: and (5) field operation.
6. The field rapid diagnosis method for drought stress of sugarcane according to claim 5, characterized in that: the relation between the light quantum efficiency and the temperature and illumination under different light temperature conditions is described as follows:
Figure RE-FDA0003023469060000021
in the formula (1), T is the actual air temperature (DEG C); phi is the photon efficiency at air temperature T; phi b and phi a are respectively basic and variable phi, and the relation is phi b + phi a To phi To; tmin, To and Tmax are three base point temperatures for sugarcane growth, and are respectively determined as 12 ℃, 28 ℃ and 43 ℃ through curve parameter fitting;
Figure RE-FDA0003023469060000022
Figure RE-FDA0003023469060000023
due to the existence of multiple electron transfer paths, even if the photosynthetic rate of the leaves is reduced to zero, the electron transfer is still carried out in the leaves, so that the phi isbLAnd phibHThe fundamental photon efficiencies at low and high temperatures, respectively; a isL、bL、aHAnd bHThe fitting values of the four empirical coefficients are 0.678 and 7.6 multiplied by 10 respectively-40.672 and 5.6X 10-4
7. The field rapid diagnosis method for drought stress of sugarcane according to claim 5, characterized in that: the step establishes a curve of the light quantum efficiency and the photosynthetically active radiation under different moisture gradients after the temperature correction, can reflect the change rule of the light quantum efficiency under different temperature, light and water combinations,
Figure RE-FDA0003023469060000031
wherein the fitting parameter epsilon is a drought stress index, and the formula of the drought stress index with the change of the moisture gradient is as follows:
Figure RE-FDA0003023469060000032
wherein rSWC is the relative water content of soil, rSWCc is the relative water content of the critical lower limit soil, the rSWCc values of the new table sugar No. 22 and the new table sugar No. 16 are respectively determined to be 30% and 20% according to tests, epsilon (0) is an initial value without drought stress, the epsilon (0) values of the new table sugar No. 22 and the new table sugar No. 16 are respectively determined to be 6.395 and 5.785 according to the tests, and the fitting values of empirical coefficients c and d of the new table sugar No. 22 and the new table sugar No. 16 are respectively 14.25 and 9.68, 34.82 and 21.77.
8. The field rapid diagnosis method for drought stress of sugarcane according to claim 5, characterized in that: step three, substituting environmental parameters of the test two into the calculation phi (PAR, T), wherein the determination coefficients (r2) between phi (PAR, T) of the new table sugar No. 22 and the new table sugar No. 16 and the measured values based on a 1:1 line are 0.98 and 0.96 respectively, and the relative regression estimation standard errors (rRMSE) are 3.66 percent and 5.74 percent respectively, so that the model can better predict the actual field light quantum efficiency, the new table sugar No. 22 is selected in production for yield verification, water is supplemented to a normal level when the relative water content of soil is reduced to T1 (35-45 percent), T1 (20-30 percent), T1 (10-20 percent) and T1 (3-10 percent), the production is measured when goods are received, and if spring drought greatly influences the emergence rate, the yield is reduced by 1.3 percent, 13.9 percent, 25.9 percent and 48.3 percent compared with full irrigation respectively; if the autumn drought occurs, the jointing and the maturity of the sugarcane are influenced, and the yield is respectively reduced by 4.9%, 10.1%, 14.8% and 21.8% compared with the full irrigation; if 7< epsilon > is less than or equal to 9, the light drought is, 9< epsilon > is less than or equal to 13, the medium drought is, and the heavy drought is, epsilon > 13.
9. The field rapid diagnosis method for drought stress of sugarcane according to claim 5, characterized in that: selecting 10 plants at random in each field, measuring the light quantum efficiency phi (PAR, T) of natural stable light adaptation under sunlight in the morning by using a portable fluorometer, wrapping the photoreaction measuring site by using a black adhesive tape, and measuring F after 30minv/FmAnd reversely deducing the drought stress index epsilon according to the environmental light temperature data, judging the drought occurrence degree, and performing preliminary disaster damage estimation.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102301878A (en) * 2011-07-09 2012-01-04 云南省农业科学院甘蔗研究所 Method for evaluating drought resistance/drought tolerance of sugarcane seedlings at seedling stage
CN102598987A (en) * 2012-03-26 2012-07-25 天津师范大学 Method for using cerium to improve chlorophyll fluorescence dynamic of ryegrass in arid environments
CN106105753A (en) * 2016-08-08 2016-11-16 云南省农业科学院甘蔗研究所 A kind of Caulis Sacchari sinensis barrel plant drought stress test method
CN106546567A (en) * 2016-10-31 2017-03-29 浙江大学 Plant drouhgt stress diagnostic method and device based on imaging-PAM technology
CN110622811A (en) * 2019-10-23 2019-12-31 广西壮族自治区农业科学院 Single-plant and combined drought-resisting screening method for sugarcane seedlings

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102301878A (en) * 2011-07-09 2012-01-04 云南省农业科学院甘蔗研究所 Method for evaluating drought resistance/drought tolerance of sugarcane seedlings at seedling stage
CN102598987A (en) * 2012-03-26 2012-07-25 天津师范大学 Method for using cerium to improve chlorophyll fluorescence dynamic of ryegrass in arid environments
CN106105753A (en) * 2016-08-08 2016-11-16 云南省农业科学院甘蔗研究所 A kind of Caulis Sacchari sinensis barrel plant drought stress test method
CN106546567A (en) * 2016-10-31 2017-03-29 浙江大学 Plant drouhgt stress diagnostic method and device based on imaging-PAM technology
CN110622811A (en) * 2019-10-23 2019-12-31 广西壮族自治区农业科学院 Single-plant and combined drought-resisting screening method for sugarcane seedlings

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
安东升 等: "基于Lake模型的叶绿素荧光参数在甘蔗苗期抗旱性研究中的应用", 《植物生态学报》 *
安东升: "温室切花百合对干旱胁迫响应的叶绿素荧光诊断研究", 《中国优秀博硕士学位论文全文数据库(硕士) 农科科技辑》 *

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