KR101948107B1 - Estimation method for ripening ratio of rice - Google Patents

Abstract

The present invention relates to an estimation method for a ripening ratio of rice by using a remote sensing-based vegetation index. According to the present invention, after a normalized difference vegetation index (NDVI) and a photochemical reflectance index (PRI) that are a vegetation index observed by a spectrometric sensor are individually converted into a relative value, a change in a reduction ratio for 35 to 45 days from growth duration from seeding to heading of two vegetation indexes is used to estimate a ripening ratio of rice regardless of a growth and development degree of different rice for each year to a heading date. Moreover, vegetation indexes data in the shape of an image is used to provide a ripening ratio of rice with two-dimensional space information to help to estimate scale of damage caused by a ripening error and to make compensation, and to be used as auxiliary data of an output estimation model to contribute to related industries.

Description

TECHNICAL FIELD The present invention relates to a method of estimating the ripening rate of rice,

The present invention relates to a method for estimating the ripeness rate of rice.

After the rice emerges, the rice blooms, and after about a week 's fertilization period, the grain starts to fade. The rice maturity rate means the ratio of the grain to the grain. Therefore, the lower the ripening rate, the lower the yield and the deterioration of the rice quality grade due to the increase of the defective grain and chaff. There are many reasons for this, such as when the rice is in a pinning state, when strong winds or dry winds are blown, and when fertilization is bad, and when there is no ears, the amount of sunshine is insufficient. In recent years, There is concern that the maturity rate will be lowered because the correction is not made.

Especially, high temperature phenomenon caused by global warming is reported to have a negative influence on the ripening rate. Until now, the maturity rate estimation method is mostly empirical formula using average of daily maximum air temperature or average air temperature for 40 days after heading. Generally, when the maximum temperature (average temperature) exceeds 32 degrees (26 degrees), it starts to decrease and when the temperature reaches 40 degrees (32 degrees), the maturity rate tends to be significantly lower.

In order to estimate rice ripeness rate empirically using the maximum or average temperature, each of the estimation equations is newly needed because the degree of reactivity to temperature varies according to the varieties, and an automatic meteorological observation device (AWS, Automated Weather Station), it is difficult to accurately represent the temperature where micro-volatility occurs due to vegetation density, surface wetness, .

In the present invention, a method of estimating the ripeness rate of rice using NDVI and PRI vegetation index calculated from spectroscopic data obtained by direct remote sensing of rice from the empirical estimation method using existing environmental factors (temperature, etc.) . The vegetation index can be observed at a specific point of interest by using a spectroscope, and it is also advantageous to acquire information on the rice grain maturity using an image having a spatial resolution of several centimeters to several meters when using a spectroscopic camera.

Korean Patent No. 1353125

The present invention estimates the rice seed ripening rate using the vegetation index calculated from the spectroscopic data observed by the remote sensing technique and finds that the Normalized Difference Vegetation Index (NDVI) useful for estimating rice biomass and the PRI The purpose of this paper is to provide a method for estimating the ripeness rate of rice in a large area in a non - destructive manner in a short time by focusing on the relative change characteristics of the two vegetation indexes after rice heading using the Reflectance Index.

1. Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) were measured once a day at the beginning of rice paddy by varying the ripening rate of rice in the standard rice growing area. Obtaining a PRI value of 1, measuring it once at the rice planting day + (35 to 45) days to obtain a second NDVI value and a second PRI value;

Obtaining the relative normal vegetation index (rNDVI) by substituting the NDVI values into the following equation (1);

The first scaled photorefractive index (sPRI) value and the second PRI value are obtained by substituting the first PRI value and the second PRI value into the following equation (2), and the sPRI values are substituted into the following equation (3) Obtaining a relative scaled photochemical reflectance index (relative sPRI, rsPRI) value;

Obtaining a relational expression of the maturity rate of the rice and a value represented by the following equation (4);

Obtaining rNDVI and rsPRI by measuring NDVI and PRI of the rice cultivation region to be determined once at the date of rice seeding and once at the rice seedling date + (35 to 45) days; And

And assigning rNDVI and rsPRI obtained in the rice growing area to be judged to the relational expression,

[Equation 1]

rNDVI = (second NDVI - NDVI theoretical minimum value) / (first NDVI - NDVI theoretical minimum value)

 &Quot; (2) "

sPRI = (PRI + 1) / 2

&Quot; (3) "

rsPRI = (second sPRI - sPRI theoretical minimum value) / (first sPRI - sPRI theoretical minimum value)

&Quot; (4) "

(1 - rsPRI) / (1 - rNDVI).

2. A method for estimating the ripeness rate of rice according to 1 above, wherein the ripening rate of rice is varied by varying the temperature of the reference rice growing area.

3. The method of claim 1, wherein the NDVI is a value of the following equation (5), and the PRI is a value of the following equation (6):

&Quot; (5) "

(Reflectance of light of 800 nm wavelength - reflectance of light of wavelength of 670 nm) / (reflectance of light of 800 nm wavelength + reflectance of light of wavelength of 670 nm)

 &Quot; (6) "

(Reflectance of light at a wavelength of 531 nm - reflectance of light at a wavelength of 570 nm) / (reflectance of light at a wavelength of 531 nm + reflectance of light at a wavelength of 570 nm).

4. The method according to claim 1, wherein the relational expression is the following formula (7)

&Quot; (7) "

(%) = 4.5906 + 114.0050 / (1 + e? (- ((value represented by the above equation (4) - 3.4868) / -1.3687).

The present invention can estimate the ripeness rate of rice in a wide range in a short period of time in a non-destructive manner by using the remote exploration-based vegetation index, thereby estimating the damage caused by poor rice filling, which is the main food resource in Korea Can be used as objective information to compensate. Furthermore, providing the maturity rate variable as input to the rice yield model can contribute to the accuracy of the yield prediction.

FIG. 1 is a flowchart showing a method of estimating the ripeness rate of rice using a remote exploration-based vegetation index.
FIG. 2 is a diagram illustrating different time series changes of rNDVI and rPRI vegetation indexes according to the ripening rate.
FIG. 3 is a diagram showing an example of the relationship between the average temperature and the ripeness rate (A), the vegetation index and the ripeness rate (B) for 40 days from the heading.

Hereinafter, the present invention will be described in detail with reference to the drawings.

The present invention relates to a method for estimating the ripeness rate of rice using a normal vegetation index (NDVI) and a photochemical reflectance index (PRI), which are remote exploration-based vegetation indexes. According to one embodiment of the present invention, According to the order, we can estimate the ripeness rate of rice using NDVI and PRI which are remote exploration-based vegetation index.

The method of estimating the ripeness rate of rice according to the present invention is characterized by measuring the Normalized Difference Vegetation Index (NDVI) and the Photochemical Reflectance Index (PRI) at the rice paddy day And obtaining the first NDVI value and the first PRI value, and measuring the first NDVI value and the first PRI value once per day on the day of rice seeding + (35 to 45) to obtain the second NDVI value and the second PRI value.

The reference rice growing area is a rice growing area in which the relationship between PRI and NDVI and the ripeness ratio of rice is obtained and the ripening rate can be obtained by substituting PRI and NDVI of the rice growing area to be judged into the above relation, And the relationship between the rNDVI and the ripeness rate of rice is obtained. More specifically, the relationship between the value of the following equation (4) and the ripeness rate of rice is obtained.

The rice is not limited to the variety and can be a variety known in the art, but it is preferable that the rice in the standard rice growing area and the rice in the rice growing area to be judged are the same variety.

In addition, even when the rice cultivars of the standard rice cultivation area and the target rice cultivation area are different from each other in the soil and climatic conditions, the change in rNDVI and rsPRI has already been reflected when they affects the maturity rate, It is not.

The maturity rate of the above-mentioned rice means that a few percent of the cultivated rice in the rice grown on the ears is turned into junhyunmi (精 玄 米). It is most desirable to increase the ripening rate in order to obtain high yield.

The ripening rate can be adjusted, for example, by varying the temperature of the reference rice growing area. More specifically, the temperature may be an average temperature of the rice seedling day to the day of planting + (35 to 45) days, and the ripening rate may decrease as the average temperature increases, but the present invention is not limited thereto.

The normal vegetation index (NDVI) is a technique used to emphasize the presence or absence of vegetation, which is calculated by dividing the difference between the reflectance values of light of near infrared rays and red light by the sum of reflectance values of two lights.

The near-infrared light may be, for example, a light having a wavelength of 800 nm, and the red light may be a light having a wavelength of 670 nm, but is not limited thereto.

More specifically, the NDVI may be a value of the following equation (5).

&Quot; (5) "

(Reflectance of light of 800 nm wavelength - reflectance of light of wavelength of 670 nm) / (reflectance of light of 800 nm wavelength + reflectance of light of wavelength of 670 nm)

The photochemical reflectance index (PRI) is one of the reflectance measurement methods such as NDVI, and is mainly used for the research on the productivity or stress of the crop. It can be used for evaluating general ecosystem health, And the difference between the reflectance values of the light between the green light having the low wavelength and the green light having the high wavelength can be calculated by dividing the reflectance value of the two lights by the sum of the reflectance values.

The green light of the low wavelength may be, for example, a light having a wavelength of 531 nm, and the green light of the high wavelength may be, for example, a light having a wavelength of 570 nm.

More specifically, the PRI may be a value of the following equation (6).

&Quot; (6) "

(Reflectance of light of 531 nm wavelength - reflectance of light of wavelength 570 nm) / (reflectance of light of 531 nm wavelength + reflectance of light of wavelength 570 nm)

According to an embodiment of the present invention, a point observation data using an optical spectrometer or a dron image data equipped with a spectral camera can be applied to the present invention as shown in FIG. 1 for measuring the NDVI and PRI 100). However, observation equipment should be equipped with 531 nm, 570 nm, Red wavelength (670 nm), and near-infrared wavelength (800 nm) for NDVI and PRI.

According to one embodiment of the present invention, the reflectivity information for 531 nm, 570 nm, Red wavelength (670 nm), and NIR wavelength (800 nm) are obtained at the date of heading and day of water + (35-45) (101). The reflectivity information may be obtained on a clear day at noon, but is not limited thereto.

Generally, multi-spectral cameras do not have 531 nm and 570 nm bands, so you can use custom-designed multispectral sensors by using a hyper-spectral camera or adding the required bands. .

The NDVI and PRI are measured once per day on the day of rice seeding and once per day on the day of rice emergence + (35 to 45). The NDVI and PRI are measured once on the day of rice emergence, and from 35 to 45 Measure once a day.

The day of rice planting + (35 to 45) days is the time when the ripening of rice is completed, and the weight of ear can be the maximum. It is preferable that the measuring time is a time at which the solar zenith angle is the minimum of the day.

It is essential to obtain observations on the day of watering. If the maximum value of the vegetation index is used after a lot of observations are made before or after the date of heading, the estimated rice seedling reliability can be increased. (35-45) days from the date of paddy watering (+ 35-45) days if the observations can not be performed on the day of paddy watering (+ 35-45) due to weather conditions. Interpolation can be used. The observation value of the rice seedling day + (35 to 45) days may be an observation value of preferably rice seedling days + (38 to 42) days, more preferably an observation value of rice seedling days +40 days, But is not limited thereto.

According to one embodiment of the present invention, the NDVI and PRI can be measured once per rice seedling day and once per rice seedling day + (35 to 45) days, 35 to 45 days), and can be continuously measured for one day or more from rice seedling to rice seedling + (35 to 45) days, but the present invention is not limited thereto.

The rNDVI and rsPRI values can be obtained by measuring the NDVI and PRI once at the minimum number of rice seeding days and once at the rice seedling days + (35 to 45) days, according to the following steps.

The present invention further includes obtaining a relative NDVI (rNDVI) value by substituting the NDVI values into Equation (1).

[Equation 1]

rNDVI = (second NDVI - NDVI theoretical minimum value) / (first NDVI - NDVI theoretical minimum value)

The degree of paddy up to the time of heading may vary depending on the breed, region, weather conditions, and thus the NDVI value may vary. Therefore, taking the minimum value from the theoretical range that the NDVI can have, not using the vegetation index value, and setting the value at the time of heading as the maximum value, the relative value is obtained (103).

And convert the NDVI to rNDVI according to Equation (1). Typical NDVI values are in the range of -1 to 1, but the negative values of NDVI are known to be due to the effects of water and aerosols, not the effects of soil or vegetation. The NDVI value immediately after actual planting is close to zero, and specifically, the minimum value of the theoretical NDVI may be the minimum value of the theoretical NDVI immediately after the planting, which may be more specifically zero.

The rNDVI indicates the degree to which the NDVI of day + (35 to 45) days is located between the minimum value and the maximum value of the NDVI after heading, and NDVI may vary depending on environmental conditions such as climate and soil In accordance with these environmental conditions, relational expressions with respect to the maturity rate are changed, and thus the estimated rate of maturity can be changed. Since the relative position of the NDVI is used as a variable instead of the NDVI value using the rNDVI, It is possible to estimate the ripeness rate of rice with high reliability.

Also, the present invention obtains a first scaled photorefractive index (sPRI) value and a second PRI value by substituting the first PRI value and the second PRI value into the following equation (2) (3) to obtain a relative scaled photochemical reflectance index (relative sPRI, rsPRI) value.

&Quot; (2) "

sPRI = (PRI + 1) / 2

&Quot; (3) "

rsPRI = (second sPRI - sPRI theoretical minimum value) / (first sPRI - sPRI theoretical minimum value)

The degree of rice growth up to the time of heading may vary depending on the breed, region, weather conditions, and therefore the PRI value may vary. Therefore, taking the minimum value from the theoretical range that PRI can have, rather than using the vegetation index, the relative value is obtained by setting the value at the time of heading to the maximum value (103).

The first scaled photorefractive index (sPRI) value and the second PRI value are obtained by substituting the first PRI value and the second PRI value into the following equation (2), and the sPRI values are substituted into the following equation (3) Relative scaled photochemical reflectance index (relative sPRI, rsPRI) value can be obtained.

Typical PRI values are in the range of -1 to 1, but the minimum value of the PRI observed in actual vegetation is calculated to be -0.15, for example, from the observation results of 2016-2018. In the present invention, the minimum value of the PRI calculated from the observation result is used. Accordingly, the general sPRI is a value within the range of 0 to 1, and the theoretical minimum value of sPRI obtained by substituting the PRI minimum value calculated from the observation result of 2016 to 2018 into the equation (2) is 0.425.

In Equation (2), PRI is converted into sPRI, scaled to have a value of 0 to 1 as in the NDVI, and converted into rsPRI value in Equation 3. rsPRI is the number of sPRIs of rice seeding days + (35 to 45) days The NDVI is different depending on the environmental conditions such as climate and soil. Since the relationship between the NDVI and the maturity rate varies depending on the environmental conditions, Since the relative position of sPRI is used as a variable instead of the value of PRI or sPRI using the rsPRI as described above, it is possible to prevent the variation of the roughness estimation value according to the change of the environmental condition, Can be estimated.

The present invention further includes obtaining a relational expression of the maturity rate of the rice and a value represented by the following equation (4).

&Quot; (4) "

x = (1 - rsPRI) / (1 - rNDVI)

The relational expression of the value of the equation (4) and the ripeness rate (%) of the rice can be obtained through a regression analysis (104).

&Quot; (7) "

(%) = 4.5906 + 114.0050 / (1 + e < - > - ((value represented by Equation 4) -3.4868) / -1.3687)

Equation (7) can be obtained through regression analysis, and the coefficients of Equation (7) may vary depending on the soil, climatic condition, rice variety, and the like.

The present invention further includes a step of obtaining rNDVI and rsPRI by measuring NDVI and PRI of the rice cultivation area to be determined once at the rice paddy watering day and once at the rice paddy watering day + (35 to 45) days.

The rice growing area to be determined is a rice growing area for determining the ripeness rate of rice using NDVI and PRI according to an embodiment of the present invention.

The present invention includes a step of assigning rNDVI and rsPRI obtained in the rice growing cultivation area to the relational expression.

Through the assignment to the above relation, the present invention can estimate the ripeness rate of the rice nondestructively and simply by measuring NDVI and PRI once at the date of planting and once at the date of planting + (35 to 45) days.

Further, the present invention relates to a method of estimating the ripeness rate of rice, wherein the NDVI is a value of the following equation (5), and the PRI is a value of the following equation (6).

&Quot; (5) "

(Reflectance of light of 800 nm wavelength - reflectance of light of wavelength of 670 nm) / (reflectance of light of 800 nm wavelength + reflectance of light of wavelength of 670 nm)

&Quot; (6) "

(Reflectance of light of 531 nm wavelength - reflectance of light of wavelength 570 nm) / (reflectance of light of 531 nm wavelength + reflectance of light of wavelength 570 nm)

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, the present invention will be described in detail with reference to examples.

Example

1. Measuring the maturity rate according to the average temperature through the climate change simulation facility

Climate change simulation facility is a facility that assumes the global warming situation. The entrance temperature is the same as the outside temperature, and the inside temperature is the temperature response of the rice at the high temperature of the external temperature +3. The seedlings were moved to the climate change simulation facility and samples with different rice ripeness rates were obtained at high temperature. Average temperature and maturity information for 40 days from the day of planting were measured at 20 sites in the simulated climate change facility, and the vegetation index was also measured. The ripening rate decreased when the mean temperature was above the critical temperature for 40 days from the date of planting.

2. Relationship between average temperature and rice ripeness ratio

The ripening rate of rice according to the average temperature of 40 days from the date of planting was obtained as shown in Table 1, and is shown in FIG. 3 (A). Also, the relational expression was obtained by the following equation (8) through regression analysis.

&Quot; (8) "

(Average temperature (℃, x) - 27.2634) / -0.3625 from 40 days from the date of planting)

Observation year Average temperature (℃) for 40 days from day of planting y = Ripening rate of rice (%) Accumulation rate of actual rice (%) 2016 26.12 87.47 91.48 2016 29.74 0.00 0.11 2016 25.42 90.66 90.57 2016 23.10 91.22 94.60 2016 23.10 91.22 88.60 2016 23.10 91.22 92.10 2016 23.10 91.22 93.00 2017 23.22 91.22 95.07 2017 24.12 91.20 82.27 2017 25.24 90.87 86.56 2017 23.92 91.21 95.64 2017 23.74 91.21 91.13 2018 26.82 70.42 65.43 2018 27.16 51.35 50.86 2018 27.34 40.48 47.36 2018 27.46 32.58 31.09 2018 28.08 7.71 11.36 2018 28.19 5.51 6.11 2018 28.48 2.04 2.95 2018 27.99 9.96 1.48

3. Remote sensing based optical observations and measurements of rNDVI and rsPRI

When obtaining samples having different maturity rates according to the average temperature in Example 1 using a spectrophotometer, light reflectance values of the samples were obtained.

The spectroscopic spectrometer can detect visible light and near infrared light. 9 stations in 2016, 11 stations in 2017, and 16 stations in 2018, all of which were measured at noon on every clear day.

(NDVI) for 40 days from the date of planting in the rice growing area to the value of the following equation (5), and the photochemical reflectance index (PRI) was obtained by the following equation (6).

&Quot; (5) "

(Reflectance of light of 800 nm wavelength - reflectance of light of wavelength of 670 nm) / (reflectance of light of 800 nm wavelength + reflectance of light of wavelength of 670 nm)

 &Quot; (6) "

(Reflectance of light at a wavelength of 531 nm - reflectance of light at a wavelength of 570 nm) / (reflectance of light at a wavelength of 531 nm + reflectance of light at a wavelength of 570 nm).

Also, the relative normal vegetation index (rNDVI) was obtained according to the following equation (1).

[Equation 1]

(NDVI - NDVI theoretical minimum value) / (NDVI value of paddy days) - NDVI theoretical minimum value)

Also, a scaled photochemical reflectance index (sPRI) was obtained according to the following equation (2), and a relative scaled photochemical reflectance index (rsPRI) was obtained according to the following equation (3).

&Quot; (2) "

sPRI = (PRI + 1) / 2

&Quot; (3) "

(sPRI - sPRI theoretical minimum value at the date of rice planting + (35 - 45) days) / (sPRI - sPRI theoretical minimum value at the rice planting day)

The relationship between different time series of rNDVI and rsPRI according to the ripening rate is shown in Table 2 and Fig. The values of rNDVI and rsPRI for the maturity rate of about 90%, 77%, 50%, 31% and 1% are shown in Table 2.

2, it was found that the peak reached about the day before and after the day of heading, and then decreased.

Generally, NDVI and PRI decrease when ripening progresses well after heading, and rNDVI and rsPRI decrease accordingly. This is because the distribution patterns of the photosynthetic products of this period are concentrated in the ears, and the aging of the stems and leaves proceeds rapidly. However, when the ripening rate is low, the aging process is slow in the stem and leaf, and the decrease of NDVI and PRI is less than that of the general case.

4. Derivation of the relation between rNDVI and rsPRI for estimating the ripeness rate of rice

(1 - rsPRI) / (1 - rNDVI) / (1 - rNDPRI) and rsPRI obtained from the above Example 3 were used to estimate the ripeness rate of the rice through the optical observation data. ) Was represented by x, the results are shown in Table 3. In addition, a relational expression of y and x can be obtained, and the graph and the relational expression are shown in Fig. 3 (B). In addition, the relational expression can be confirmed as shown in Equation (7) through regression analysis.

Similar to the general pattern of decreasing the ripening rate when the temperature exceeds the critical temperature, a similar relationship is found in the relationship between vegetation index and maturity.

&Quot; (7) "

(%) = 4.5906 + 114.0050 / (1 + e < - > - ((value represented by Equation 4) -3.4868) / -1.3687)

Observation year x = (1 - rsPRI)
/ (1 - rNDVI) y = Ripening rate of rice (%) Accumulation rate of actual rice (%) 2016 2.13 87.80 91.48 2016 11.20 5.00 0.11 2016 2.02 89.49 90.57 2016 1.69 94.49 94.60 2016 1.56 96.19 88.60 2016 1.58 95.97 92.10 2016 1.65 94.92 93.00 2017 1.04 89.18 95.07 2017 1.01 85.66 82.27 2017 1.05 80.08 86.56 2017 1.05 80.70 95.64 2017 1.07 80.95 91.13 2018 2.56 80.15 65.43 2018 2.94 72.74 50.86 2018 4.25 46.06 47.36 2018 5.54 25.33 31.09 2018 15.31 4.61 11.36 2018 22.14 4.59 6.11 2018 15.99 4.60 2.95 2018 29.63 4.59 1.48

5. Estimation of ripeness rate of rice using NDVI and PRI

In order to verify the validity of the method of estimating the ripeness rate of the rice of the present invention, NDVI and PRI were measured once every day of rice paddy and once every 40 days of rice day.

Then, rNDVI and rsPRI were obtained by substituting the respective values into the above Equations (1) to (3), and each value was substituted into Equation (4) to obtain (1 - rsPRI) / (1 - rNDVI).

The maturity rate (%, y) of the rice was calculated by substituting the value of the above equation (4) into x in the above equation (7) and the rice maturity rate was estimated by repeating this procedure 21 times.

Observation year x = (1 - rsPRI)
/ (1 - rNDVI) y = Ripening rate of rice (%) Accumulation rate of actual rice (%) 2016 6.00 20.24 14.02 2016 3.77 55.62 50.56 2017 1.07 79.70 79.28 2017 1.02 93.28 89.63 2017 1.04 82.61 84.66 2017 1.04 81.28 88.65 2017 1.07 87.21 91.97 2017 1.05 66.72 91.59 2018 1.78 93.20 88.78 2018 1.80 92.89 84.65 2018 1.93 90.86 84.43 2018 2.32 84.58 82.11 2018 2.23 86.02 77.53 2018 9.10 6.45 18.00 2018 21.88 4.59 5.08 2018 16.87 4.60 1.08

6. Validation of Maturity Rate Estimation According to the Present Invention

The actual cultivated rice was harvested in order to determine whether the estimated rice seed ripening rate according to the present invention (Table 4) was reasonably estimated and the ripeness rate was measured (16 replicates). The root mean square error (RMSE) was about 8.40%, which was similar to the RMSE of 9.54% (Table 5) when the maturity rate was estimated using mean temperature. It can be confirmed that the maturity rate estimation of rice according to the present invention is valid.

Observation year Average temperature (℃) for 40 days from day of planting y = Ripening rate of rice (%) Accumulation rate of actual rice (%) 2016 27.75 18.07 14.02 2016 26.36 84.08 50.56 2017 22.92 91.27 79.28 2017 23.59 91.21 89.63 2017 24.46 91.18 84.66 2017 26.14 87.18 88.65 2017 23.56 91.21 91.97 2017 24.09 91.20 91.59 2018 25.45 90.60 88.78 2018 25.51 90.50 84.65 2018 26.32 84.88 84.43 2018 26.40 83.33 82.11 2018 26.50 81.13 77.53 2018 27.57 26.41 18.00 2018 28.32 3.72 5.08 2018 28.48 2.05 1.08

100: Remote sensing based optical observation
101: Heading, heading + (35 to 45) days observation
102: NDVI, PRI calculation 103: rNDVI, rsPRI calculation
104: Maturity rate estimation 105: Maturity rate Display of video information
200: Cultivation experiment in climate change simulation facility
201: Relationship between rNDVI and rsPRI

Claims (4)

Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) were measured once a day at the paddy watering day by varying the ripening rate of the rice in the reference rice growing area, and the first NDVI value and the first PRI Obtaining a second NDVI value and a second PRI value by measuring once at a rice planting day + (35 to 45) days;
Obtaining the relative normal vegetation index (rNDVI) by substituting the NDVI values into the following equation (1);
The first scaled photorefractive index (sPRI) value and the second PRI value are obtained by substituting the first PRI value and the second PRI value into the following equation (2), and the sPRI values are substituted into the following equation (3) Obtaining a relative scaled photochemical reflectance index (relative sPRI, rsPRI) value;
Obtaining a relational expression of the maturity rate of the rice and a value represented by the following equation (4);
Obtaining the rNDVI and rsPRI by measuring NDVI and PRI of the rice cultivation area to be determined once at the rice paddy watering day and once at the rice paddy watering day + (35 to 45) days; And
And assigning rNDVI and rsPRI obtained in the rice growing area to be judged to the relational expression,
[Equation 1]
rNDVI = (second NDVI - NDVI theoretical minimum value) / (first NDVI - NDVI theoretical minimum value)
&Quot; (2) "
sPRI = (PRI + 1) / 2
&Quot; (3) "
rsPRI = (second sPRI - sPRI theoretical minimum value) / (first sPRI - sPRI theoretical minimum value)
&Quot; (4) "
(1 - rsPRI) / (1 - rNDVI).
The method according to claim 1, wherein rice seed ripeness is varied by varying the temperature of the reference rice growing area.
The method according to claim 1, wherein the NDVI is a value of the following equation (5), and the PRI is a value of the following equation (6)
&Quot; (5) "
(Reflectance of light of 800 nm wavelength - reflectance of light of wavelength of 670 nm) / (reflectance of light of 800 nm wavelength + reflectance of light of wavelength of 670 nm)
&Quot; (6) "
(Reflectance of light at a wavelength of 531 nm - reflectance of light at a wavelength of 570 nm) / (reflectance of light at a wavelength of 531 nm + reflectance of light at a wavelength of 570 nm).
The method according to claim 1, wherein the relational expression is the following formula (7)
&Quot; (7) "
(%) = 4.5906 + 114.0050 / (1 + e? (- ((value represented by the above equation (4) - 3.4868) / -1.3687).

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