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Remote sensing estimators of potential and actual crop yield
REMOTE SENSING OF ENVIRONMENT 13:301-311 (1983)
301
Remote Sensing Estimators of Potential and Actual Crop Yield*
j. L. HATFIELD Land, Air and Water Resources, University of California, Davis, California 95616
Spectral-reflectance patterns, vegetative indices of infrared/red, were utilized to signal the beginning and ending times for a stress-degree-day summation. The maximum vegetative index (MSS 7/5) corresponded to the beginning of head-emergence in grain sorghum and the boot-stage in wheat. When the vegetative index declined to 0.5 of the maximum, 90% of the reproductive dry matter had been accumulated, delineating the reproductive portion of the growth cycle. In both grain sorghum and wheat, a linear relationship was found between yield and stress-degree-days over the reproductive period defined by the vegetative index. However, in all years, the grain sorghum data did not fit the same linear relationship because of differences in cultttral practices. It was found that the maximum vegetative index could be used to define the potential harvestable yield that was encountered during the reproductive stage. A linear relationship was then found between the yield harvested relative to this potential harvestable yield and the summation of the stress-degree-days. In these experiments, there was a wide range in ground covers and yield providing a rigorous test of the relationship. This technique provides a method for defining the interval of the stress-degree-day accumulation and has applicability as a generalized yield model.
Introduction In recent years, considerable attention has been given to the development of yield models which could be driven with remote sensing inputs. These have ranged from spectral models as typified by Tucker et al. [1,2]; albedo models (Idso et al. [3]) to complete thermal models (Idso et al. [4] and Walker and Hatfield [5]). Each of these groups have developed relationships for data from a particular crop within a limited geographic region. Aase and Siddoway [6] related spectral reflectance to the yield of spring wheat but cautioned that this method was developed on normal" grain filling processes. Water or other stresses may not be detectable in this model. Idso et al. [7] found that the yield of wheat could be "'
*Contribution from the California Experiment Station Project No. 3963-H. Partial support supplied by USDA Broadform Agreement 12-14-5001-37BF. ©Elsevier Science Publishing Co., Inc., 1983 52 Vanderbilt Ave., New York, NY 10017
estimated by an evaluation of the rate of senescence as measured by the vegetative index (MSS 7/5) following heading. They found that the faster the rate of senescence, the larger the yield because stressed plants would begin to senesce sooner. This type of approach is, in reality, a measure of the duration of the green leaf area index. Fischer and HilleRislambers [8] found that yield of wheat was decreased when the duration of green leaf area was reduced. Crop yield has also been found to be a function of the leaf area at the onset of the reproductive stage (Fischer [9]). Hatfield [10] found that the vegetative indices (MSS 7/5) during the reproductive stage for 82 different varieties of wheat in a yield nursery were not related to final yield, suggesting that previously developed vegetative indices may be variety-specific. Tucker et al. [1] showed that the normalized-difference method was linearly related to yield in wheat. However, in their study, hallground cover was not obtained during the 0034-4257/83/$3.00
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302
season, suggesting that this relationship may not be valid over a wide range of ground covers. Pinter et al. [11] related yield of wheat and barley to an accumulated index derived from the normalized difference vegetative index [MSS ( 7 - 5)/(7 + 5)]. They postulated that this method was similar to a measure of the duration of green leaf area and was applicable over a wide range of soil cover. Daughtry et al. [12] postulated that a calculation of greenness from the reflectance of all MSS wavebands could be used to approximate interception of solar radiation by the canopy. The summation of solar radiation interception was related to grain yield in corn. Idso et al. [4] first proposed and showed that midday canopy-air temperature differences (stress-degree-day) were related to yield when summed from heading to maturity. Walker and Hatfield [5] found that planting date on kidney beans did not influence the relationship between accumulated stress-degree-days over the reproductive stage and yield. Later, Walker [13] showed that the period of accumulation of stress-degree-days was critical to the goodness of fit between the stress-degree-days and yield. In the work of Idso et al. [4], the summation periods were related to observable phenological stages which limits the technique from a remote-sensing platform because of the need to identify these stages. From the research which has been conducted, it would appear that spectral reflectance and thermal infrared measurements could be combined to develop a yield model. It is the objective of these studies to evaluate the usefulness of the spectral reflectance measurements to define critical development stages in wheat and grain sorghum and to utilize the
L. HATFIELD
canopy-air temperature summation over this period as a measure of the level of stress and hence the final yield.
Methods and Materials A field study was conducted at Davis, California on a Yolo-clay loam (Typic Xerorthent) using grain sorghum (Sorghum bicolor L. Moench, cultivar Dekalb A28 +) during 1978, 1979, and 1981, and winter wheat (Triticum aestivum, eultivar Anza) in 1981. For the grain sorghum, the irrigation treatments ineluded: 1. ample water supply throughout the growing season (irrigation when the available water in the upper meter was 65% removed); 2. no irrigation throughout the season; 3. irrigation as an amply watered treatment during the vegetative stage with no water during the reproductive stage; and 4. ample water treatment during the reproductive stage following no irrigation during the vegetative stage. In all years, the profile was filled to capacity at planting. The wheat was not irrigated because the normal rainfall amounts during the growing season provided adequate water. The Yolo clay loam soft profile at Davis is 300 cm deep. A crop can be grown to maturity without irrigation if the soft profile is at capacity at the beginning of the season. In the spring of 1979, a series of controlled-rooting depth plots were installed to create conditions of reducedwater availability. These plots were created by excavating the soft to 50, 100, or 150 cm, laying in plastic, and refilling. Each of these plots were 5 × 15 m. These plots were used for the 1979 grain sorghum with the four irrigation treatments imposed on each rooting depth and on a natural soft profile. The 1981 wheat
REMOTE SENSING ESTIMATORS OF CROP YIELDS
303
experiments were also conducted on this experimental site. Due to the small size of the experimental area, the irrigation treatments were not replicated in a rooting depth for the wheat or grain sorghum studies. However, the mean of each parameter is a result of four measurements. In the field plots of 1978 and 1981, each treatment was replicated four times. The grain sorghum experiments were planted in mid-June at a population of 15,000 plants ha - t in 76 cm rows. The row direction was east-west in 1978 and north-south in 1979 and 1981. Weekly measurements were made of plant growth, i.e., height, leaf area, ground cover, and phenological stage on 10 randomlyselected plants from each replicate. In the 1979 experiments, destructive sampling was not possible so weekly measurements were made of plant height, ground cover, and phenological stage. Destructive samples to determine dry weight and leaf area were made at the 5-leaf, boot, earlygrain tilling, and mature stages on 10 randomly selected plants from each treatment. Grain yield was measured at maturity from two 1-m row lengths from each treatment. Grain yield was measured at the end of the season from 10 1-m2 sample area, from each replicate in 1978 and 1981. Daily measurements were made of canopy and air temperature at 1300-1400 PST with a Barnes PRT-5* or Telatemp AG-42* with a 20 ° and 4 ° fov, respectively. Both infrared thermometers were calibrated at the beginning and end of the experiment and checked throughout the season to ensure calibration stability. Canopy temperature measurements were
made in each replicate from each cardinal direction at an angle of 60 ° from nadir and averaged. In the rooting depth plots, only north-south readings were made on two adjacent rows with four readings in each direction because of the small plot size. Dry-bulb air temperature was measured at 1 m above the canopy with an aspirated Assman psychrometer. The winter wheat experiment was planted on 2 December 1980 at a population of 135,000 plants ha -~ in northsouth, 20 cm rows. No irrigation treatments were imposed on the wheat, with the rooting depth being the treatment variable creating a difference in water availability. During the 1980-81 season, rainfall was 330 m m - - 9 0 mm below normal. The last significant rainfall was on 25 March 1981. Thus, water needs of the crop were sufficient until the beginning of grain fill. Weekly measurements were made of the growth parameters and ground cover with yield measured at harvest. Growth parameters were measured on five randomly-selected plants from an area in the center of the plot and ground cover was estimated visually in four locations under the area for canopy temperature and reflectance measurements. Weekly photographs of vertical and angular ground cover were also obtained for each rooting depth. Yield was measured as the mean of 8 1-m~ samples from the reflectance and canopy temperature measurement sites in each plot. Canopy temperatures were monitored throughout the season with a Teletemp AG-42 with eight temperature readings for each rooting depth. Dry-bulb air temperatures were measured at 1 m above the canopy with an aspirated Assman psychrometer during the time of the canopy temperature measurements.
*No endorsement intended.
304
j. L. HATFIELD
In both the grain sorghum and wheat experiments, spectral reflectance measurements were made on clear days throughout the growing season. In the grain sorghum an Exotech Model 100A* radiometer with four bands simulating the MSS 4, 5, 6, and 7 bands, 0.5-0.6, 0.6-0.7, 0.7-0.8, and 0.8-1.1 /xm, respectively. For reflectance calibration, a bariumsulfate plate suspended above the crop surface was measured prior to and during the measurement period. For the wheat, a 3-band radiometer with bands at 0.640.70, 0.75-0.89, and 1.55-1.75 /~m was used (Landsat Thematic Mapper (TM) bands 3, 4, and 5, respectively). The readings were taken at solar noon and completed within 15 to 20 min. The radiometer was held at about 1 m above the canopy, with 10-15 measurements taken per plot. Results and Discussion Development of Spectral Reflectance Patterns Temporal plots of the near-infrared/red reflectance ratios (MSS 7/5) for the four irrigation treatments of grain sorghum in 1978 are shown in Figure 1. These data indicate differences between treatments particularly after heading. If we are to develop a yield model as proposed by Idso et al. (1977), then we should relate a spectral vegetative index such as the infrared/red ratio to the growth and development patterns of the crop. Examination of the dry-matter accumulation curves for the four irrigation treatments shows that the vegetative index reaches its maximum at approximately head emergence, the beginning of the reproductive stage, then
*No endorsement intended.
declines, until maturity. We then had to evaluate the value of the vegetative index which would describe the time at which the crop had accumulated a large portion of its dry matter, hence its yield. The dry-matter accumulation curves for these irrigation treatments assume the familiar sigmoidal growth curve for both vegetative and reproductive growth and about 90% of the total dry matter in the head is accumulated during the linear phase of reproductive growth (Figure 2). It should be noted that in this study the nonirrigated treatment accumulated the largest amount of dry matter due to differences in pretreatment growing conditions and large, initial soft moisture ditferences between treatments. Using the vegetative index values from Figure 1 over this same period, we find that the vegetative index at the time of 90% accumulation of reproductive dry matter is 0.5 of the maximum value at the time of head emergence. The maximum leaf area index occurred at heading, which would be typical of determinant crops such as sorghum, and corresponded to the maximum vegetative index. It is not the purpose of this paper to estimate phenological stages but rather use change in spectral estimators as indicators of the initiation and cessation times for the stress-degree-day method and to evaluate these changes relative to some physiological characteristic of the plant. One exception to this is Treatment 2 which was well-watered during the reproductive stage and did not decline as rapidly in the vegetative index because of pronounced secondary growth of tillers. The slow senescence rate of the crop in this case is due to renewed growth and could cause a minor problem in evaluating the period over which stress-degree-days should be summed.
REMOTE SENSING ESTIMATORS OF CROP YIELDS
305
GRAIN SORGHUM 1978 ~ " ~, " XHeading 8-(/3 Or)
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Dry-matter accumulation curves for four irrigation treatments in grain sorghum
306
J.L. HATFIELD
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~ STRESS- DEGREE- DAY FIGURE 3. Yield as a function o| accumulated stress-degree-days over the period from maximum to 0.5 maximum vegetative index for grain sorghum in 1978 and 1979.
The computed rate of senescence as suggested by Idso et al. [7], revealed a rather poor relationship between yield and the rates of senescence. Inclusion of a model such as the stress-degree-day may lead to improved results. Stress-Degree-Day Model For the 1978 and 1979 grain sorghum yield data, the daily stress-degree-day values were summed over the period indicated by the spectral reflectance measurements (Figure 3). The data fit a linear relationship with some noticeable scatter. The scatter is to be expected for the type of experiment conducted in 1979, where plants were grown without water until near death and then rewatered, with the yield coming from only secondary tiller growth. It is encouraging that the 1978 and 1979 data have the same linear relationship. While the 1981 data exhibited a linear relationship, it was different than the results from previous years, suggesting that this approach needs to include a
better description of crop development and yield to incorporate year-to-year growth variation. A possible cause of the difference between years was the date of planting and the resultant effects on growth. Concept of Potential Yield Fischer [9] discussed that yield is a function of the leaf area at the beginning of the reproductive stage and that the final yield would be determined by the duration of the leaf area index. Pinter et al. [11] suggested that final yield is determined by the duration of green leaf area index as evidenced by the different summations of the normalized difference. It appeared that this concept of green leaf area duration would provide a measure of the plants' ability to produce a final yield. From the treatments for 1978, 1979, and 1981, a few plots were maintained in a nonstress condition following heading, e.g., well-watered and well-irrigated fol-
REMOTE SENSING ESTIMATORS OF CROP YIELDS
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L A T AT H E A D I N G FIGURE 4. Grain yield o[ grain sorghum as related to the lea( area index at heading with no significant stress imposed during the reproductive stage.
lowing a vegetative water stress. These were chosen to develop the relationship between yield and leaf area index (LA1) under nonlimiting conditions. This relationship shows that as the LAI at the onset of the reproductive stage increases, the final yield increases if no htrther stress is imposed (Figure 4). The rationale for the approach is that yield in determinant crops would be a function of the leaf area available to intercept radiation and convert the radiation into photosynthate for the grain-filling process. A remote-sensing approach of this type has been proposed by Daughtry et al. [12]. If there is no stress imposed during the reproductive stage, then the available leaf area should be able to work at maximum efficiency. Thus, we have a potential harvestable yield line for this crop. In order to relate this to our objective of using only spectral and thermal data for a yield estimation,
the yield of these treatments and the vegetative index at heading were plotted (Figure 5). This relationship between yield and the vegetative index then defines the potential harvestable yield by substituting the vegetative index for the leaf area index at heading. Relative yields for each treatment were determined from the potential harvestable yield relationship, in Figure 5, by calculating the ratio between the actual and potential harvestable yield. These relative yields were then plotted against the summation of the stress-degree-days for the period from maximum to 0.5 maximum vegetative index. The relationship between the relative yields and the summed stress-degree-days were linear and exhibit only minor scatter (Figure 6). Utilizing this approach, all of the grain sorghum data fall into one population. This is encouraging for this study since
j. L. HATFIELD
308
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VEGETATIVE INDEX (MSS 7/5) AT HEADING FIGURE 5. Grain yield of grain sorghum as effected by the vegetative index (MSS 7/5) at heading with no significant stress imposed during the reproductive stage.
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FIGURE 6. Relative yield (actual to potential yield) as defined by the potential yield from the vegetative index as effeeted by the accumulation of the stress-degree-days during the reproductive stage.
REMOTE SENSING ESTIMATORS OF CROP YIELDS
309
the range of actual yields were from 0 to 9600 kg ha -1 with a range of ground covers at heading from 40% to 100%.
by half almost 90% of the reproductive dry matter had been accumulated in the head. This suggests that this approach may have applicability to a wide range of grain producing crops. In this experiment, it was not possible to evaluate the concept of potential yield because of a lack of range of LAI at heading. It does, however, suggest that such an approach would be valid since, in all plots, the potential was the same at heading and the resultant moisture stress prevented each plot from achieving its potential. The stress-degree-days over this interval were summed and expressed as a function of the final yield. The equation relating yield to stress-degree-days (SDD) is
Application to Wheat Yield Prediction
To evaluate if this approach could be used for other species, the same methodology was applied to wheat, i.e., using the maximum vegetative index as the starting point and 0.5 vegetative index as the ending point of the stress-degree-day summation. Values of the vegetative index throughout the season are given in Figure 7. No difference in the vegetative index was evident until day of year 105 (full-head emergence). The maximum values of the vegetative index corresponded to the boot stage, which was also when the maximum leaf area index occurred. The differences in rooting depths caused a range in water available to the crop and this created a differential water stress during the grain-filling period, resulting in a significant change in the date of maturity and yield. Again, as in the grain sorghum when the vegetative index was reduced
30
,
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Yield = 4024.75 - 54.2 (ESDD). The r 2 for these data is 0.98; however, with only four data points, these results must be considered preliminary. Differences in LAI at heading between years
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CALENDAR FIGURE 7.
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130
140
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DATE
Vegetative index (TM 4/3) patterns for four dif|erent rooting depths in wheat during 1981.
J.L.
310
HATFIELD
TABLE 1 Yield and Summed Stress-Degree-Days for the Interval trom Maximum to 0.5 Maximum Vegetative Index for Anza Wheat in 1981 Rooting Depth
Yield
(em)
(kgha- 1)
Stress-Degree-Days
50 100 150 300
1912 3209 4863 6386
40 10 - 10 - 45
could alter these relationships substantially, thus necessitating the incorporation of the potential harvestable yield.
Conclusions A spectral vegetative index was found to provide a method of defining the beginning and ending points of a stressdegree-day summation which is related to yield. The maximum value corresponded to the beginning of grain fill and a decline to 0.5 maximum signaled the point at which 90% of the reproductive dry weight had been accumulated or roughly the end of the linear phase of reproductive growth. A potential harvestable yield determined from the vegetative index described the upper limit of yield assuming nonlimiting conditions for the remainder of the growth cycle. The potential yield was reduced by the accumulation of stress-degree-days over the period defined by the vegetative index in a linear relationship. Inclusion of data over a number of years and a wide range of yields suggests its applicability to a wide region. Previous research has shown that the relationships between remotely-sensed parameters and crops may be specific. These data suggest that this generalized approach could be utilized for a wide
range of varieties if one knew the yield potential of the crop, an aspect that needs refinement and further research over a wide range of geographic locations. The combination of spectral and thermal remotely-sensed data may provide the basis for a general yield model. The' approach suggested in this paper would appear to be usehd in remote sensing of yield for many different agricultural crops. Acknowledgments The helpful comments and discussions o f Dr. R. D. Jackson and Dr. R. I. Reginato are gratefully appreciated.
References 1. Tucker, C. J., Holben, B. N., Elgin, J. H., Jr., and McMurtrey, J. E., IlL (1980), Relationships of spectral data to grainyield variation, Photogram. Eng. and Remote Sens. 46:657-666. 2. Tucker, C. J., Holben, B. N., Elgin, J. H., Jr., and McMurtrey, J. E., III. (1981), Remote sensing of total dry-matter accumulation of winter wheat, Remote Sens. Environ. 11:171-189. 3. Idso, S. B., Hatfield, J. L., Reginato, R. J., and Jackson, R. D. (1978), Wheat yield estimation by albedo measurement, Remote Sens. Environ. 7:273-276. 4. Idso, S. B., Jackson, R. D., and Reginato,
REMOTESENSINGESTIMATORSOF CROP YIELDS R. J. (1977), Remote sensing of crop yields, Science 196:19-25. 5. Walker, G. K., and Hat.field, J. L. (1979), Test of the stress-degree-day concept using multiple-planting data of red kidney beans. Agron. J. 71:967-971. 6. Aase, J. K., and Siddoway, F. H. (1981), Spring wheat yield estimates from spectral reflectances measurements. IEEE Trans. Geoscience and Remote Sensing, GE-19:78-84. 7. Idso, S. B., Pinter, P. J., Jr., Jackson, R. D., and Reginato, R. J. (1980), Estimation of grain yields by remote-sensing of crop senescence rates, Remote Sens. Environ. 9:87-91. 8. Fischer, R. A. and HilleRislambers, D. (1978), Effect of environment and cultivar on source limitation to grain weight in wheat. Aust. J. Agric. Res. 29:443-448. 9. Fischer, R. A. (1975), Yield potential in a dwarf spring wheat and the effect of
311 shading. Crop Sci. 15:607-613. 10. Hatatield, J. L. (1981), Spectral behavior of wheat yield variety trials. Photogram. Eng. and Remote Sens. 47:1487-1491. 11. Pinter, P. J., Jr., Jackson, R. D., Idso, S. B., and Reginato, R. D. (1981), Multidate spectral reflectance as predictors of yield in water-stressed wheat and barley. Int. J. Remote Sens. 2:43-48. 12. Daughtry, C. S. T., Gallo, K. P., and Bauer, M. E. (1982), Spectral estimates of solar radiation intercepted by corn canopies. Agristars Technical Report SR-PZ04236. Purdue University, West Lafayette, IN, 14 pp. 13. Walker, G. K. (1980), Relations between crop tempera~tre and the growth and yield of kidney beans (Phaseolus vulgaris L.). Ph.D. Dissertation, University of California, Davis. 201 pp. Received Apri116, 1982;acceptedOctober22, 1982.
301
Remote Sensing Estimators of Potential and Actual Crop Yield*
j. L. HATFIELD Land, Air and Water Resources, University of California, Davis, California 95616
Spectral-reflectance patterns, vegetative indices of infrared/red, were utilized to signal the beginning and ending times for a stress-degree-day summation. The maximum vegetative index (MSS 7/5) corresponded to the beginning of head-emergence in grain sorghum and the boot-stage in wheat. When the vegetative index declined to 0.5 of the maximum, 90% of the reproductive dry matter had been accumulated, delineating the reproductive portion of the growth cycle. In both grain sorghum and wheat, a linear relationship was found between yield and stress-degree-days over the reproductive period defined by the vegetative index. However, in all years, the grain sorghum data did not fit the same linear relationship because of differences in cultttral practices. It was found that the maximum vegetative index could be used to define the potential harvestable yield that was encountered during the reproductive stage. A linear relationship was then found between the yield harvested relative to this potential harvestable yield and the summation of the stress-degree-days. In these experiments, there was a wide range in ground covers and yield providing a rigorous test of the relationship. This technique provides a method for defining the interval of the stress-degree-day accumulation and has applicability as a generalized yield model.
Introduction In recent years, considerable attention has been given to the development of yield models which could be driven with remote sensing inputs. These have ranged from spectral models as typified by Tucker et al. [1,2]; albedo models (Idso et al. [3]) to complete thermal models (Idso et al. [4] and Walker and Hatfield [5]). Each of these groups have developed relationships for data from a particular crop within a limited geographic region. Aase and Siddoway [6] related spectral reflectance to the yield of spring wheat but cautioned that this method was developed on normal" grain filling processes. Water or other stresses may not be detectable in this model. Idso et al. [7] found that the yield of wheat could be "'
*Contribution from the California Experiment Station Project No. 3963-H. Partial support supplied by USDA Broadform Agreement 12-14-5001-37BF. ©Elsevier Science Publishing Co., Inc., 1983 52 Vanderbilt Ave., New York, NY 10017
estimated by an evaluation of the rate of senescence as measured by the vegetative index (MSS 7/5) following heading. They found that the faster the rate of senescence, the larger the yield because stressed plants would begin to senesce sooner. This type of approach is, in reality, a measure of the duration of the green leaf area index. Fischer and HilleRislambers [8] found that yield of wheat was decreased when the duration of green leaf area was reduced. Crop yield has also been found to be a function of the leaf area at the onset of the reproductive stage (Fischer [9]). Hatfield [10] found that the vegetative indices (MSS 7/5) during the reproductive stage for 82 different varieties of wheat in a yield nursery were not related to final yield, suggesting that previously developed vegetative indices may be variety-specific. Tucker et al. [1] showed that the normalized-difference method was linearly related to yield in wheat. However, in their study, hallground cover was not obtained during the 0034-4257/83/$3.00
J.
302
season, suggesting that this relationship may not be valid over a wide range of ground covers. Pinter et al. [11] related yield of wheat and barley to an accumulated index derived from the normalized difference vegetative index [MSS ( 7 - 5)/(7 + 5)]. They postulated that this method was similar to a measure of the duration of green leaf area and was applicable over a wide range of soil cover. Daughtry et al. [12] postulated that a calculation of greenness from the reflectance of all MSS wavebands could be used to approximate interception of solar radiation by the canopy. The summation of solar radiation interception was related to grain yield in corn. Idso et al. [4] first proposed and showed that midday canopy-air temperature differences (stress-degree-day) were related to yield when summed from heading to maturity. Walker and Hatfield [5] found that planting date on kidney beans did not influence the relationship between accumulated stress-degree-days over the reproductive stage and yield. Later, Walker [13] showed that the period of accumulation of stress-degree-days was critical to the goodness of fit between the stress-degree-days and yield. In the work of Idso et al. [4], the summation periods were related to observable phenological stages which limits the technique from a remote-sensing platform because of the need to identify these stages. From the research which has been conducted, it would appear that spectral reflectance and thermal infrared measurements could be combined to develop a yield model. It is the objective of these studies to evaluate the usefulness of the spectral reflectance measurements to define critical development stages in wheat and grain sorghum and to utilize the
L. HATFIELD
canopy-air temperature summation over this period as a measure of the level of stress and hence the final yield.
Methods and Materials A field study was conducted at Davis, California on a Yolo-clay loam (Typic Xerorthent) using grain sorghum (Sorghum bicolor L. Moench, cultivar Dekalb A28 +) during 1978, 1979, and 1981, and winter wheat (Triticum aestivum, eultivar Anza) in 1981. For the grain sorghum, the irrigation treatments ineluded: 1. ample water supply throughout the growing season (irrigation when the available water in the upper meter was 65% removed); 2. no irrigation throughout the season; 3. irrigation as an amply watered treatment during the vegetative stage with no water during the reproductive stage; and 4. ample water treatment during the reproductive stage following no irrigation during the vegetative stage. In all years, the profile was filled to capacity at planting. The wheat was not irrigated because the normal rainfall amounts during the growing season provided adequate water. The Yolo clay loam soft profile at Davis is 300 cm deep. A crop can be grown to maturity without irrigation if the soft profile is at capacity at the beginning of the season. In the spring of 1979, a series of controlled-rooting depth plots were installed to create conditions of reducedwater availability. These plots were created by excavating the soft to 50, 100, or 150 cm, laying in plastic, and refilling. Each of these plots were 5 × 15 m. These plots were used for the 1979 grain sorghum with the four irrigation treatments imposed on each rooting depth and on a natural soft profile. The 1981 wheat
REMOTE SENSING ESTIMATORS OF CROP YIELDS
303
experiments were also conducted on this experimental site. Due to the small size of the experimental area, the irrigation treatments were not replicated in a rooting depth for the wheat or grain sorghum studies. However, the mean of each parameter is a result of four measurements. In the field plots of 1978 and 1981, each treatment was replicated four times. The grain sorghum experiments were planted in mid-June at a population of 15,000 plants ha - t in 76 cm rows. The row direction was east-west in 1978 and north-south in 1979 and 1981. Weekly measurements were made of plant growth, i.e., height, leaf area, ground cover, and phenological stage on 10 randomlyselected plants from each replicate. In the 1979 experiments, destructive sampling was not possible so weekly measurements were made of plant height, ground cover, and phenological stage. Destructive samples to determine dry weight and leaf area were made at the 5-leaf, boot, earlygrain tilling, and mature stages on 10 randomly selected plants from each treatment. Grain yield was measured at maturity from two 1-m row lengths from each treatment. Grain yield was measured at the end of the season from 10 1-m2 sample area, from each replicate in 1978 and 1981. Daily measurements were made of canopy and air temperature at 1300-1400 PST with a Barnes PRT-5* or Telatemp AG-42* with a 20 ° and 4 ° fov, respectively. Both infrared thermometers were calibrated at the beginning and end of the experiment and checked throughout the season to ensure calibration stability. Canopy temperature measurements were
made in each replicate from each cardinal direction at an angle of 60 ° from nadir and averaged. In the rooting depth plots, only north-south readings were made on two adjacent rows with four readings in each direction because of the small plot size. Dry-bulb air temperature was measured at 1 m above the canopy with an aspirated Assman psychrometer. The winter wheat experiment was planted on 2 December 1980 at a population of 135,000 plants ha -~ in northsouth, 20 cm rows. No irrigation treatments were imposed on the wheat, with the rooting depth being the treatment variable creating a difference in water availability. During the 1980-81 season, rainfall was 330 m m - - 9 0 mm below normal. The last significant rainfall was on 25 March 1981. Thus, water needs of the crop were sufficient until the beginning of grain fill. Weekly measurements were made of the growth parameters and ground cover with yield measured at harvest. Growth parameters were measured on five randomly-selected plants from an area in the center of the plot and ground cover was estimated visually in four locations under the area for canopy temperature and reflectance measurements. Weekly photographs of vertical and angular ground cover were also obtained for each rooting depth. Yield was measured as the mean of 8 1-m~ samples from the reflectance and canopy temperature measurement sites in each plot. Canopy temperatures were monitored throughout the season with a Teletemp AG-42 with eight temperature readings for each rooting depth. Dry-bulb air temperatures were measured at 1 m above the canopy with an aspirated Assman psychrometer during the time of the canopy temperature measurements.
*No endorsement intended.
304
j. L. HATFIELD
In both the grain sorghum and wheat experiments, spectral reflectance measurements were made on clear days throughout the growing season. In the grain sorghum an Exotech Model 100A* radiometer with four bands simulating the MSS 4, 5, 6, and 7 bands, 0.5-0.6, 0.6-0.7, 0.7-0.8, and 0.8-1.1 /xm, respectively. For reflectance calibration, a bariumsulfate plate suspended above the crop surface was measured prior to and during the measurement period. For the wheat, a 3-band radiometer with bands at 0.640.70, 0.75-0.89, and 1.55-1.75 /~m was used (Landsat Thematic Mapper (TM) bands 3, 4, and 5, respectively). The readings were taken at solar noon and completed within 15 to 20 min. The radiometer was held at about 1 m above the canopy, with 10-15 measurements taken per plot. Results and Discussion Development of Spectral Reflectance Patterns Temporal plots of the near-infrared/red reflectance ratios (MSS 7/5) for the four irrigation treatments of grain sorghum in 1978 are shown in Figure 1. These data indicate differences between treatments particularly after heading. If we are to develop a yield model as proposed by Idso et al. (1977), then we should relate a spectral vegetative index such as the infrared/red ratio to the growth and development patterns of the crop. Examination of the dry-matter accumulation curves for the four irrigation treatments shows that the vegetative index reaches its maximum at approximately head emergence, the beginning of the reproductive stage, then
*No endorsement intended.
declines, until maturity. We then had to evaluate the value of the vegetative index which would describe the time at which the crop had accumulated a large portion of its dry matter, hence its yield. The dry-matter accumulation curves for these irrigation treatments assume the familiar sigmoidal growth curve for both vegetative and reproductive growth and about 90% of the total dry matter in the head is accumulated during the linear phase of reproductive growth (Figure 2). It should be noted that in this study the nonirrigated treatment accumulated the largest amount of dry matter due to differences in pretreatment growing conditions and large, initial soft moisture ditferences between treatments. Using the vegetative index values from Figure 1 over this same period, we find that the vegetative index at the time of 90% accumulation of reproductive dry matter is 0.5 of the maximum value at the time of head emergence. The maximum leaf area index occurred at heading, which would be typical of determinant crops such as sorghum, and corresponded to the maximum vegetative index. It is not the purpose of this paper to estimate phenological stages but rather use change in spectral estimators as indicators of the initiation and cessation times for the stress-degree-day method and to evaluate these changes relative to some physiological characteristic of the plant. One exception to this is Treatment 2 which was well-watered during the reproductive stage and did not decline as rapidly in the vegetative index because of pronounced secondary growth of tillers. The slow senescence rate of the crop in this case is due to renewed growth and could cause a minor problem in evaluating the period over which stress-degree-days should be summed.
REMOTE SENSING ESTIMATORS OF CROP YIELDS
305
GRAIN SORGHUM 1978 ~ " ~, " XHeading 8-(/3 Or)
Physiological " ~ ' Maturity ~ "
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Days After Planting FIGURE 1. Vegetative index (MSS 7/5) for four irrigation treatments in grain sorghum in 1978.
I0,000
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ARROWS DENOTE 9 0 % OF FINAL GRAIN WEIGHT
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DAYS FIGURE 2. in 1978.
60
AFTER
80
100
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PLANTING
Dry-matter accumulation curves for four irrigation treatments in grain sorghum
306
J.L. HATFIELD
8,000
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.---- 6,000 T 0 ¢..
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30
60
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~ STRESS- DEGREE- DAY FIGURE 3. Yield as a function o| accumulated stress-degree-days over the period from maximum to 0.5 maximum vegetative index for grain sorghum in 1978 and 1979.
The computed rate of senescence as suggested by Idso et al. [7], revealed a rather poor relationship between yield and the rates of senescence. Inclusion of a model such as the stress-degree-day may lead to improved results. Stress-Degree-Day Model For the 1978 and 1979 grain sorghum yield data, the daily stress-degree-day values were summed over the period indicated by the spectral reflectance measurements (Figure 3). The data fit a linear relationship with some noticeable scatter. The scatter is to be expected for the type of experiment conducted in 1979, where plants were grown without water until near death and then rewatered, with the yield coming from only secondary tiller growth. It is encouraging that the 1978 and 1979 data have the same linear relationship. While the 1981 data exhibited a linear relationship, it was different than the results from previous years, suggesting that this approach needs to include a
better description of crop development and yield to incorporate year-to-year growth variation. A possible cause of the difference between years was the date of planting and the resultant effects on growth. Concept of Potential Yield Fischer [9] discussed that yield is a function of the leaf area at the beginning of the reproductive stage and that the final yield would be determined by the duration of the leaf area index. Pinter et al. [11] suggested that final yield is determined by the duration of green leaf area index as evidenced by the different summations of the normalized difference. It appeared that this concept of green leaf area duration would provide a measure of the plants' ability to produce a final yield. From the treatments for 1978, 1979, and 1981, a few plots were maintained in a nonstress condition following heading, e.g., well-watered and well-irrigated fol-
REMOTE SENSING ESTIMATORS OF CROP YIELDS
_,.-I
I0,000
--
8,000
--
307
GRAIN SORGH
0 ,,,,,
6,000 -y
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-
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I
2
3
4
5
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L A T AT H E A D I N G FIGURE 4. Grain yield o[ grain sorghum as related to the lea( area index at heading with no significant stress imposed during the reproductive stage.
lowing a vegetative water stress. These were chosen to develop the relationship between yield and leaf area index (LA1) under nonlimiting conditions. This relationship shows that as the LAI at the onset of the reproductive stage increases, the final yield increases if no htrther stress is imposed (Figure 4). The rationale for the approach is that yield in determinant crops would be a function of the leaf area available to intercept radiation and convert the radiation into photosynthate for the grain-filling process. A remote-sensing approach of this type has been proposed by Daughtry et al. [12]. If there is no stress imposed during the reproductive stage, then the available leaf area should be able to work at maximum efficiency. Thus, we have a potential harvestable yield line for this crop. In order to relate this to our objective of using only spectral and thermal data for a yield estimation,
the yield of these treatments and the vegetative index at heading were plotted (Figure 5). This relationship between yield and the vegetative index then defines the potential harvestable yield by substituting the vegetative index for the leaf area index at heading. Relative yields for each treatment were determined from the potential harvestable yield relationship, in Figure 5, by calculating the ratio between the actual and potential harvestable yield. These relative yields were then plotted against the summation of the stress-degree-days for the period from maximum to 0.5 maximum vegetative index. The relationship between the relative yields and the summed stress-degree-days were linear and exhibit only minor scatter (Figure 6). Utilizing this approach, all of the grain sorghum data fall into one population. This is encouraging for this study since
j. L. HATFIELD
308
I0,000
-
-
GRAIN SORGHUM
/e
./
r2 = 0.93 8000
--
Y = - 2 7 4 3 . 4 + 1537.6 (VI) s.e. = 744.5
I o e,-
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--
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VEGETATIVE INDEX (MSS 7/5) AT HEADING FIGURE 5. Grain yield of grain sorghum as effected by the vegetative index (MSS 7/5) at heading with no significant stress imposed during the reproductive stage.
1.0
GRAIN SORGHUM
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60
90
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STRESS-DEGREE-DAY
FIGURE 6. Relative yield (actual to potential yield) as defined by the potential yield from the vegetative index as effeeted by the accumulation of the stress-degree-days during the reproductive stage.
REMOTE SENSING ESTIMATORS OF CROP YIELDS
309
the range of actual yields were from 0 to 9600 kg ha -1 with a range of ground covers at heading from 40% to 100%.
by half almost 90% of the reproductive dry matter had been accumulated in the head. This suggests that this approach may have applicability to a wide range of grain producing crops. In this experiment, it was not possible to evaluate the concept of potential yield because of a lack of range of LAI at heading. It does, however, suggest that such an approach would be valid since, in all plots, the potential was the same at heading and the resultant moisture stress prevented each plot from achieving its potential. The stress-degree-days over this interval were summed and expressed as a function of the final yield. The equation relating yield to stress-degree-days (SDD) is
Application to Wheat Yield Prediction
To evaluate if this approach could be used for other species, the same methodology was applied to wheat, i.e., using the maximum vegetative index as the starting point and 0.5 vegetative index as the ending point of the stress-degree-day summation. Values of the vegetative index throughout the season are given in Figure 7. No difference in the vegetative index was evident until day of year 105 (full-head emergence). The maximum values of the vegetative index corresponded to the boot stage, which was also when the maximum leaf area index occurred. The differences in rooting depths caused a range in water available to the crop and this created a differential water stress during the grain-filling period, resulting in a significant change in the date of maturity and yield. Again, as in the grain sorghum when the vegetative index was reduced
30
,
I'
X bJ Q Z
I'
I'
I'
WHEAT
~'
I'
Yield = 4024.75 - 54.2 (ESDD). The r 2 for these data is 0.98; however, with only four data points, these results must be considered preliminary. Differences in LAI at heading between years
dointing
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40
50
60
70
80
90
CALENDAR FIGURE 7.
I00
I10
120
130
140
150
DATE
Vegetative index (TM 4/3) patterns for four dif|erent rooting depths in wheat during 1981.
J.L.
310
HATFIELD
TABLE 1 Yield and Summed Stress-Degree-Days for the Interval trom Maximum to 0.5 Maximum Vegetative Index for Anza Wheat in 1981 Rooting Depth
Yield
(em)
(kgha- 1)
Stress-Degree-Days
50 100 150 300
1912 3209 4863 6386
40 10 - 10 - 45
could alter these relationships substantially, thus necessitating the incorporation of the potential harvestable yield.
Conclusions A spectral vegetative index was found to provide a method of defining the beginning and ending points of a stressdegree-day summation which is related to yield. The maximum value corresponded to the beginning of grain fill and a decline to 0.5 maximum signaled the point at which 90% of the reproductive dry weight had been accumulated or roughly the end of the linear phase of reproductive growth. A potential harvestable yield determined from the vegetative index described the upper limit of yield assuming nonlimiting conditions for the remainder of the growth cycle. The potential yield was reduced by the accumulation of stress-degree-days over the period defined by the vegetative index in a linear relationship. Inclusion of data over a number of years and a wide range of yields suggests its applicability to a wide region. Previous research has shown that the relationships between remotely-sensed parameters and crops may be specific. These data suggest that this generalized approach could be utilized for a wide
range of varieties if one knew the yield potential of the crop, an aspect that needs refinement and further research over a wide range of geographic locations. The combination of spectral and thermal remotely-sensed data may provide the basis for a general yield model. The' approach suggested in this paper would appear to be usehd in remote sensing of yield for many different agricultural crops. Acknowledgments The helpful comments and discussions o f Dr. R. D. Jackson and Dr. R. I. Reginato are gratefully appreciated.
References 1. Tucker, C. J., Holben, B. N., Elgin, J. H., Jr., and McMurtrey, J. E., IlL (1980), Relationships of spectral data to grainyield variation, Photogram. Eng. and Remote Sens. 46:657-666. 2. Tucker, C. J., Holben, B. N., Elgin, J. H., Jr., and McMurtrey, J. E., III. (1981), Remote sensing of total dry-matter accumulation of winter wheat, Remote Sens. Environ. 11:171-189. 3. Idso, S. B., Hatfield, J. L., Reginato, R. J., and Jackson, R. D. (1978), Wheat yield estimation by albedo measurement, Remote Sens. Environ. 7:273-276. 4. Idso, S. B., Jackson, R. D., and Reginato,
REMOTESENSINGESTIMATORSOF CROP YIELDS R. J. (1977), Remote sensing of crop yields, Science 196:19-25. 5. Walker, G. K., and Hat.field, J. L. (1979), Test of the stress-degree-day concept using multiple-planting data of red kidney beans. Agron. J. 71:967-971. 6. Aase, J. K., and Siddoway, F. H. (1981), Spring wheat yield estimates from spectral reflectances measurements. IEEE Trans. Geoscience and Remote Sensing, GE-19:78-84. 7. Idso, S. B., Pinter, P. J., Jr., Jackson, R. D., and Reginato, R. J. (1980), Estimation of grain yields by remote-sensing of crop senescence rates, Remote Sens. Environ. 9:87-91. 8. Fischer, R. A. and HilleRislambers, D. (1978), Effect of environment and cultivar on source limitation to grain weight in wheat. Aust. J. Agric. Res. 29:443-448. 9. Fischer, R. A. (1975), Yield potential in a dwarf spring wheat and the effect of
311 shading. Crop Sci. 15:607-613. 10. Hatatield, J. L. (1981), Spectral behavior of wheat yield variety trials. Photogram. Eng. and Remote Sens. 47:1487-1491. 11. Pinter, P. J., Jr., Jackson, R. D., Idso, S. B., and Reginato, R. D. (1981), Multidate spectral reflectance as predictors of yield in water-stressed wheat and barley. Int. J. Remote Sens. 2:43-48. 12. Daughtry, C. S. T., Gallo, K. P., and Bauer, M. E. (1982), Spectral estimates of solar radiation intercepted by corn canopies. Agristars Technical Report SR-PZ04236. Purdue University, West Lafayette, IN, 14 pp. 13. Walker, G. K. (1980), Relations between crop tempera~tre and the growth and yield of kidney beans (Phaseolus vulgaris L.). Ph.D. Dissertation, University of California, Davis. 201 pp. Received Apri116, 1982;acceptedOctober22, 1982.