... Eyüp Selim KÖKSAL Ondokuz Mayıs Üniversitesi, Ziraat Fakültesi, Tarımsal Yapılar ve Sulama Bö... more ... Eyüp Selim KÖKSAL Ondokuz Mayıs Üniversitesi, Ziraat Fakültesi, Tarımsal Yapılar ve Sulama Bölümü, Samsun ... Başlangıcından bu güne tarım, uzaktan algılanmış verilerin başlıca kullanıcılarından birisi olarak düşünülmüştür (Jackson 1984). ...
Field experiments were carried out in the 2004 and 2005 growing seasons on drip irrigated dwarf g... more Field experiments were carried out in the 2004 and 2005 growing seasons on drip irrigated dwarf green beans (Phaseolus vulgaris, humilis). Soil water content (SWC), spectral reflectance and yield were monitored. Based on these data crop evapotranspiration (ETc), soil water deficit index (SWDI), water use efficiency (WUE) and four separate spectral indexes were calculated. In order to determine use opportunities of spectral indexes for estimation of yield, SWDI and WUE, some statistical analyzes were made. Results showed that spectral indexes could be used for monitoring of yield, SWDI and WUE. Especially, Soil Adjusted Vegetation Index (SAVI) had the highest correlations with all three of the parameters. The estimation procedure which was given in this study has a potential use either during, or at the end of the growing season. Estimated values of WUE and SWDI were 3.2 (kg m−3) and 0.12, respectively, through SAVI and the given procedure, indicates the optimal water use and yield conditions for dwarf green beans. At this situation, probably ETc was 580 mm and yield was 25.5 t ha−1.
In this study, an experiment was conducted in sub-humid condition, several observations made to d... more In this study, an experiment was conducted in sub-humid condition, several observations made to determine Tc, spectral indexes, LWP and daily ET of sweet cherry trees with different irrigation treatments (T1 and T2). The results showed that, Tc-Ta were increased from sunrise to noon and decreased from noon to sunset throughout the day on DOY 171-172 (T1-T2) and DOY 233-234 (T2). However, it was increased from sunrise to sunset on DOY 233-234 for T1 treatment. It is very close the values of ET(d) and ET(cum) which were determined based on remotely sensed data with daily ET values determined by soil water budget for Gisela 5 rootstock. The cherry trees with non-water stress condition (T2) have had also the highest spectral index values and the tree with water stress condition (T1) has had the lowest spectral index values. According to statistical analysis, most significant relationships were determined between LWP-SAVI (r = 0.88 for T1; r = 0.77 for T2), ET(i)-LWP (r = 0.89 for T1; r = 0.92 for T2), ET(i)-SAVI (r = 0.88 for T1; r = 0.70 for T2) and ET(i)-Tc-Ta (r = 0.85 for T2). Based on these findings, the canopy temperature of sweet cherry trees is more sensitive to water stress than leaf water potential and spectral indexes and daily ET for sweet cherry trees may be defined with remotely sensed data. Spectral indexes may be used efficiently to monitor vegetation growth periods and may be beneficial to determine ET of sweet cherry trees.
In this study, the relationship between water deficit index (WDI) and a number of parameters rela... more In this study, the relationship between water deficit index (WDI) and a number of parameters related to soil water status, crop monitoring and yield were investigated with regard to drip irrigated dwarf green beans (Phaseolus vulgaris, humilis) in Ankara, Turkey during the 2004 and 2005 growing seasons. Three different WDIs were calculated based on three different spectral indexes and oblique viewed surface temperature. Soil water status was quantified by soil water content (SWC) and soil water deficit index (SWDI). Crop evapotranspiration (ETc), leaf water potential (LWP), spectral indexes and crop water stress index (CWSI) were determined. Although the WDIs have statistically significant relationships with the parameters, it is hard to use WDIs based on oblique viewed surface temperature for irrigation scheduling purposes. However, total yield estimation and monitoring of seasonal crop water use status could be achieved through this kind of WDI.
The neutron moisture meter (NMM) is a widely used device for sensing soil water content (SWC). Ca... more The neutron moisture meter (NMM) is a widely used device for sensing soil water content (SWC). Calibration accuracy and precision of the NMM are critical to obtain reliable results, and linear regression analysis of SWC against NMM count data is the most common method of calibration. In this study, artificial neural network (ANN) calibration models were developed and compared with linear regression. For this purposes, training and validation data were obtained from 2 calibration and 16 testing plots, respectively. Calibration plots consist of wet and dry soil water conditions separately. Data measured in dry beans and red pepper plots that have four different water levels were used to determine validity of regression and ANN-based calibration models. Volumetric SWC and NMM count ratio measurements were taken for depth intervals of 30 cm throughout a 120-cm-deep soil profile. Several neural network architectures were explored in order to determine the optimal network architecture. Data analyses were conducted for each soil layer and for the whole profile, separately, based on both linear regression and ANN. Linear regression calibration equation coefficients of determination (r 2) for the 0–30, 30–60, 60–90 and 90–120 cm depth ranges calculated by regression models were 0.85, 0.84, 0.72 and 0.82, respectively, and r 2 values were 0.94, 0.95, 0.87 and 0.88 based on ANN models, respectively. Using the data set from the entire 120-cm soil profile for calibration by ANN, the r 2 value was raised to 0.97.
Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey d... more Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey during the 2005 growing season. Different amounts of irrigation water were applied, and various levels of water stress and vegetation occurred. Spectral reflectance, infrared canopy temperature, and some parameters related to crop evapotranspiration (ET c) were observed. Daily ET c values were calculated based on energy balance and soil water balance residual. The fraction of reference ET (ETrF), which is essentially the same with the crop coefficient (K c), was determined, and relationships between spectral vegetation indices (SVIs) were analysed. Under water stress conditions, the ET c and ETrF values estimated by means of energy balance were relatively high. In order to improve the correlation between ETrF and SVIs and for correction of ET c for water‐stressed irrigation treatments, a modification ratio was calculated based on SVIs. Although all three SVIs have a significant relationship with ETrF, the correctness of the modification with a Simple Ratio (SR) was higher. As a consequence, ETrF or crop coefficient (K c) could be estimated by SR, and this information could be used for irrigation water management of large‐scale agricultural lands.
Determination of temporal and spatial distribution of water use (WU) within agricultural land is ... more Determination of temporal and spatial distribution of water use (WU) within agricultural land is critical for irrigation management and could be achieved by remotely sensed data. The aim of this study was to estimate WU of dwarf green beans under excessive and limited irrigation water application conditions through indicators based on remotely sensed data. For this purpose, field experiments were conducted comprising of six different irrigation water levels. Soil water content, climatic parameters, canopy temperature and spectral reflectance were all monitored. Reference evapotranspiration (ET 0 ), crop coefficient K c and potential crop evapotraspiration (ET c ) were calculated by means of methods described in FAO-56. In addition, WU values were determined by using soil water balance residual and various indexes were calculated. Water use fraction (WUF), which represents both excessive and limited irrigation applications, was defined through WU, ET 0 and K c . Based on the relationships between WUF and remotely sensed indexes, WU of each irrigation treatments were then estimated. According to comparisons between estimated and measured WU, in general crop water stress index (CWSI) can be offered for monitoring of irrigated land. At the same time, under water stress, correlation between measured WU and estimated WU based on CWSI was the highest too. However, canopy-air temperature difference (T c − T a ) is more reliable than others for excessive water use conditions. Where there is no data related to canopy temperature, some of spectral vegetation indexes could be preferable in the estimation of WU.
Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey d... more Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey during the 2005 growing season. Different amounts of irrigation water were applied, and various levels of water stress and vegetation occurred. Spectral reflectance, infrared canopy temperature, and some parameters related to crop evapotranspiration (ETc) were observed. Daily ETc values were calculated based on energy balance
Management of agricultural practices such as irrigation by using remotely sensed data requires ba... more Management of agricultural practices such as irrigation by using remotely sensed data requires background data obtained from field experiments carried out under controlled conditions. In this study, spectral and agronomic data from field trials consisting of six different irrigation treatments were used to derive new spectral indicators for estimating growth level and water use status of dwarf green beans. Spectral reflectance (Ref) values were smoothed and first-order derivative spectra ( ) were calculated. Linear regression and multivariate analysis (cluster and principal component analysis) were done between agronomic indicators and both the smoothed spectral reflectance (R) and of each individual wavelength between 650 and 1100 nm. Based on those calculations, the most appropriate wavelengths were selected for each agronomic indicator and new combinations were calculated by using rationing, differencing, normalized differencing and multiple regression. The ratio between measured at 950 or 960 nm and 1020 nm wavelengths provided estimates in an error band of 2.47 bar for Leaf Water Potential (LWP) and 3.18% for Leaf Water Content (LWC). An equation based on 740 and 980 was developed to estimate Leaf Relative Water Content (LRWC). In the same manner, the at 820 and 970 nm provided a good estimate of crop water use and the values at 770 and 960 nm were critical for the calculation of Leaf Area Index (LAI) and dry biomass. It was also determined that the ratio of R930 to R670 can be applied to yield estimation.
Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey d... more Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey during the 2005 growing season. Different amounts of irrigation water were applied, and various levels of water stress and vegetation occurred. Spectral reflectance, infrared canopy temperature, and some parameters related to crop evapotranspiration (ETc) were observed. Daily ETc values were calculated based on energy balance
The response of sunflower (Helianthus annuus L.) to 14 irrigation treatments in a sub-humid envir... more The response of sunflower (Helianthus annuus L.) to 14 irrigation treatments in a sub-humid environment (Bursa, Turkey) was studied in the field for two seasons. A rainfed (non-irrigated) treatment as the control and 13 irrigation treatments with full and 12 different deficit irrigations were applied to the hybrid Sanbro (Novartis Seed Company) planted on clay soil, at three critical development stages: heading (H), flowering (F) and milk ripening (M). The yield increased with irrigation water amount, and the highest seed yield (3.95 t ha−1) and oil yield (1.78 t ha−1) were obtained from the HFM treatment (full irrigation at three stages); 82.9 and 85.4% increases, respectively, compared to the control. Evapotranspiration (ET) increased with increased amounts of irrigation water supplied. The highest seasonal ET (average of 652 mm) was estimated at the HFM treatment. Additionally, yield response factor (k y) was separately calculated for each, two and total growth stages, and k y was found to be 0.8382, 0.9159 (the highest value) and 0.7708 (the lowest value) for the total growing season, heading, and flowering-milk ripening combination stages, respectively. It is concluded that HFM irrigation is the best choice for maximum yield under the local conditions, but these irrigation schemes must be re-considered in areas where water resources are more limited. In the case of more restricted irrigation, the limitation of irrigation water at the flowering period should be avoided; as the highest water use efficiency (WUE) (7.80 kg ha−1 mm−1) and irrigation water use efficiency (IWUE) (10.19 kg ha−1 mm−1) were obtained from the F treatment.
... Eyüp Selim KÖKSAL Ondokuz Mayıs Üniversitesi, Ziraat Fakültesi, Tarımsal Yapılar ve Sulama Bö... more ... Eyüp Selim KÖKSAL Ondokuz Mayıs Üniversitesi, Ziraat Fakültesi, Tarımsal Yapılar ve Sulama Bölümü, Samsun ... Başlangıcından bu güne tarım, uzaktan algılanmış verilerin başlıca kullanıcılarından birisi olarak düşünülmüştür (Jackson 1984). ...
Field experiments were carried out in the 2004 and 2005 growing seasons on drip irrigated dwarf g... more Field experiments were carried out in the 2004 and 2005 growing seasons on drip irrigated dwarf green beans (Phaseolus vulgaris, humilis). Soil water content (SWC), spectral reflectance and yield were monitored. Based on these data crop evapotranspiration (ETc), soil water deficit index (SWDI), water use efficiency (WUE) and four separate spectral indexes were calculated. In order to determine use opportunities of spectral indexes for estimation of yield, SWDI and WUE, some statistical analyzes were made. Results showed that spectral indexes could be used for monitoring of yield, SWDI and WUE. Especially, Soil Adjusted Vegetation Index (SAVI) had the highest correlations with all three of the parameters. The estimation procedure which was given in this study has a potential use either during, or at the end of the growing season. Estimated values of WUE and SWDI were 3.2 (kg m−3) and 0.12, respectively, through SAVI and the given procedure, indicates the optimal water use and yield conditions for dwarf green beans. At this situation, probably ETc was 580 mm and yield was 25.5 t ha−1.
In this study, an experiment was conducted in sub-humid condition, several observations made to d... more In this study, an experiment was conducted in sub-humid condition, several observations made to determine Tc, spectral indexes, LWP and daily ET of sweet cherry trees with different irrigation treatments (T1 and T2). The results showed that, Tc-Ta were increased from sunrise to noon and decreased from noon to sunset throughout the day on DOY 171-172 (T1-T2) and DOY 233-234 (T2). However, it was increased from sunrise to sunset on DOY 233-234 for T1 treatment. It is very close the values of ET(d) and ET(cum) which were determined based on remotely sensed data with daily ET values determined by soil water budget for Gisela 5 rootstock. The cherry trees with non-water stress condition (T2) have had also the highest spectral index values and the tree with water stress condition (T1) has had the lowest spectral index values. According to statistical analysis, most significant relationships were determined between LWP-SAVI (r = 0.88 for T1; r = 0.77 for T2), ET(i)-LWP (r = 0.89 for T1; r = 0.92 for T2), ET(i)-SAVI (r = 0.88 for T1; r = 0.70 for T2) and ET(i)-Tc-Ta (r = 0.85 for T2). Based on these findings, the canopy temperature of sweet cherry trees is more sensitive to water stress than leaf water potential and spectral indexes and daily ET for sweet cherry trees may be defined with remotely sensed data. Spectral indexes may be used efficiently to monitor vegetation growth periods and may be beneficial to determine ET of sweet cherry trees.
In this study, the relationship between water deficit index (WDI) and a number of parameters rela... more In this study, the relationship between water deficit index (WDI) and a number of parameters related to soil water status, crop monitoring and yield were investigated with regard to drip irrigated dwarf green beans (Phaseolus vulgaris, humilis) in Ankara, Turkey during the 2004 and 2005 growing seasons. Three different WDIs were calculated based on three different spectral indexes and oblique viewed surface temperature. Soil water status was quantified by soil water content (SWC) and soil water deficit index (SWDI). Crop evapotranspiration (ETc), leaf water potential (LWP), spectral indexes and crop water stress index (CWSI) were determined. Although the WDIs have statistically significant relationships with the parameters, it is hard to use WDIs based on oblique viewed surface temperature for irrigation scheduling purposes. However, total yield estimation and monitoring of seasonal crop water use status could be achieved through this kind of WDI.
The neutron moisture meter (NMM) is a widely used device for sensing soil water content (SWC). Ca... more The neutron moisture meter (NMM) is a widely used device for sensing soil water content (SWC). Calibration accuracy and precision of the NMM are critical to obtain reliable results, and linear regression analysis of SWC against NMM count data is the most common method of calibration. In this study, artificial neural network (ANN) calibration models were developed and compared with linear regression. For this purposes, training and validation data were obtained from 2 calibration and 16 testing plots, respectively. Calibration plots consist of wet and dry soil water conditions separately. Data measured in dry beans and red pepper plots that have four different water levels were used to determine validity of regression and ANN-based calibration models. Volumetric SWC and NMM count ratio measurements were taken for depth intervals of 30 cm throughout a 120-cm-deep soil profile. Several neural network architectures were explored in order to determine the optimal network architecture. Data analyses were conducted for each soil layer and for the whole profile, separately, based on both linear regression and ANN. Linear regression calibration equation coefficients of determination (r 2) for the 0–30, 30–60, 60–90 and 90–120 cm depth ranges calculated by regression models were 0.85, 0.84, 0.72 and 0.82, respectively, and r 2 values were 0.94, 0.95, 0.87 and 0.88 based on ANN models, respectively. Using the data set from the entire 120-cm soil profile for calibration by ANN, the r 2 value was raised to 0.97.
Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey d... more Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey during the 2005 growing season. Different amounts of irrigation water were applied, and various levels of water stress and vegetation occurred. Spectral reflectance, infrared canopy temperature, and some parameters related to crop evapotranspiration (ET c) were observed. Daily ET c values were calculated based on energy balance and soil water balance residual. The fraction of reference ET (ETrF), which is essentially the same with the crop coefficient (K c), was determined, and relationships between spectral vegetation indices (SVIs) were analysed. Under water stress conditions, the ET c and ETrF values estimated by means of energy balance were relatively high. In order to improve the correlation between ETrF and SVIs and for correction of ET c for water‐stressed irrigation treatments, a modification ratio was calculated based on SVIs. Although all three SVIs have a significant relationship with ETrF, the correctness of the modification with a Simple Ratio (SR) was higher. As a consequence, ETrF or crop coefficient (K c) could be estimated by SR, and this information could be used for irrigation water management of large‐scale agricultural lands.
Determination of temporal and spatial distribution of water use (WU) within agricultural land is ... more Determination of temporal and spatial distribution of water use (WU) within agricultural land is critical for irrigation management and could be achieved by remotely sensed data. The aim of this study was to estimate WU of dwarf green beans under excessive and limited irrigation water application conditions through indicators based on remotely sensed data. For this purpose, field experiments were conducted comprising of six different irrigation water levels. Soil water content, climatic parameters, canopy temperature and spectral reflectance were all monitored. Reference evapotranspiration (ET 0 ), crop coefficient K c and potential crop evapotraspiration (ET c ) were calculated by means of methods described in FAO-56. In addition, WU values were determined by using soil water balance residual and various indexes were calculated. Water use fraction (WUF), which represents both excessive and limited irrigation applications, was defined through WU, ET 0 and K c . Based on the relationships between WUF and remotely sensed indexes, WU of each irrigation treatments were then estimated. According to comparisons between estimated and measured WU, in general crop water stress index (CWSI) can be offered for monitoring of irrigated land. At the same time, under water stress, correlation between measured WU and estimated WU based on CWSI was the highest too. However, canopy-air temperature difference (T c − T a ) is more reliable than others for excessive water use conditions. Where there is no data related to canopy temperature, some of spectral vegetation indexes could be preferable in the estimation of WU.
Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey d... more Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey during the 2005 growing season. Different amounts of irrigation water were applied, and various levels of water stress and vegetation occurred. Spectral reflectance, infrared canopy temperature, and some parameters related to crop evapotranspiration (ETc) were observed. Daily ETc values were calculated based on energy balance
Management of agricultural practices such as irrigation by using remotely sensed data requires ba... more Management of agricultural practices such as irrigation by using remotely sensed data requires background data obtained from field experiments carried out under controlled conditions. In this study, spectral and agronomic data from field trials consisting of six different irrigation treatments were used to derive new spectral indicators for estimating growth level and water use status of dwarf green beans. Spectral reflectance (Ref) values were smoothed and first-order derivative spectra ( ) were calculated. Linear regression and multivariate analysis (cluster and principal component analysis) were done between agronomic indicators and both the smoothed spectral reflectance (R) and of each individual wavelength between 650 and 1100 nm. Based on those calculations, the most appropriate wavelengths were selected for each agronomic indicator and new combinations were calculated by using rationing, differencing, normalized differencing and multiple regression. The ratio between measured at 950 or 960 nm and 1020 nm wavelengths provided estimates in an error band of 2.47 bar for Leaf Water Potential (LWP) and 3.18% for Leaf Water Content (LWC). An equation based on 740 and 980 was developed to estimate Leaf Relative Water Content (LRWC). In the same manner, the at 820 and 970 nm provided a good estimate of crop water use and the values at 770 and 960 nm were critical for the calculation of Leaf Area Index (LAI) and dry biomass. It was also determined that the ratio of R930 to R670 can be applied to yield estimation.
Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey d... more Two separate field experiments were conducted with sugar beet and green bean, at Ankara, Turkey during the 2005 growing season. Different amounts of irrigation water were applied, and various levels of water stress and vegetation occurred. Spectral reflectance, infrared canopy temperature, and some parameters related to crop evapotranspiration (ETc) were observed. Daily ETc values were calculated based on energy balance
The response of sunflower (Helianthus annuus L.) to 14 irrigation treatments in a sub-humid envir... more The response of sunflower (Helianthus annuus L.) to 14 irrigation treatments in a sub-humid environment (Bursa, Turkey) was studied in the field for two seasons. A rainfed (non-irrigated) treatment as the control and 13 irrigation treatments with full and 12 different deficit irrigations were applied to the hybrid Sanbro (Novartis Seed Company) planted on clay soil, at three critical development stages: heading (H), flowering (F) and milk ripening (M). The yield increased with irrigation water amount, and the highest seed yield (3.95 t ha−1) and oil yield (1.78 t ha−1) were obtained from the HFM treatment (full irrigation at three stages); 82.9 and 85.4% increases, respectively, compared to the control. Evapotranspiration (ET) increased with increased amounts of irrigation water supplied. The highest seasonal ET (average of 652 mm) was estimated at the HFM treatment. Additionally, yield response factor (k y) was separately calculated for each, two and total growth stages, and k y was found to be 0.8382, 0.9159 (the highest value) and 0.7708 (the lowest value) for the total growing season, heading, and flowering-milk ripening combination stages, respectively. It is concluded that HFM irrigation is the best choice for maximum yield under the local conditions, but these irrigation schemes must be re-considered in areas where water resources are more limited. In the case of more restricted irrigation, the limitation of irrigation water at the flowering period should be avoided; as the highest water use efficiency (WUE) (7.80 kg ha−1 mm−1) and irrigation water use efficiency (IWUE) (10.19 kg ha−1 mm−1) were obtained from the F treatment.
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