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Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola

Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola was established on 20th October, 1969 with its head-quarter at Akola. This Agricultural University was named after the illustrious son of Vidarbha Dr. Panjabrao (alias Bhausaheb) Deshmukh, who was the Minister for Agriculture,Govt. of India. The jurisdiction of this university is spread over the eleven districts of Vidarbha. According to the University Act 1983 (of the Government of Maharashtra), the University is entrusted with the responsibility of agricultural education, research and extension education alongwith breeder and foundation seed programme. The University has its main campus at Akola. The instructional programmes at main campus are spread over in 5 Colleges namely, College of Agriculture, College of Agricultural Engineering & Technology, College of Forestry, College of Horticulture and Post Graduate Institute. At this campus 4 degree programmes namely B.Sc.(Agri.) B.Sc. (Hort.), B.Sc. (Forestry) and B.Tech. (Ag. Engg.) , two Master’s Degree Programmes viz. M.Sc.(Agri.) and M.Tech. (Agri.Engg.) and Doctoral Degree Programmes in the faculties of Agriculture and Agril. Engineering are offered. The University has its sub-campus at Nagpur with constituent College, College of Agriculture which offers B.Sc.(Agri.) and M.Sc.(Agri.) degree programmes. The Nagpur Campus is accomplished with a garden, surrounded by its natural beauty and a well established Zoo which attract the general public and visitors to the city. A separate botanic Garden is being maintained on 22 hectares with a green house for the benefit of research workers. In addition there are 2 affiliated grant-in-aid colleges and 14 private non-grant-in-aid colleges under the umbrella of this University A Central Research Station is situated at the main Campus which caters to the need of research projects undertaken by Crop Scientists of the principle crops of the region are Cotton, Sorghum, Oilseeds and Pulses.

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End date: 2023 × Start date: 2020 × Type: Thesis × Thesis Type: M.Tech. ×
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    ThesisItemOpen Access
    ESTIMATION OF EVAPOTRANSPIRATION OF CHICKPEA USING VEGETATION INDICES BASED CROP COEFFICIENTS.
    (Dr. Panjabrao Deshmukh Krishi Vidyapeeth Akola, Maharashtra, 2022-11-28) AKKARA, MONCY S.; Pimpale, Dr. A. R.
    Ever growing water demand of world along with the severe reduction in water availability- quantitatively and qualitatively, necessitates monitoring and management of existing water resources in the best possible way. Agriculture being major shareholder of fresh water consumption calls for an immediate action to adopt proper irrigation methods and develop technology to make judicious use of water. Better estimation of irrigation water requirements is essential for water conservation aspects as well as better yield and economic aspects. Evapotranspiration being the major consumptive use of irrigation water, crop evapotranspiration represents crop water requirement and is calculated by FAO-56 procedures based on literature derived crop coefficients. Irrigation scheduling based on literature derived crop coefficients often leads to over irrigation due to the non optimal actual field conditions and spatial and temporal variations in Kc. Remotely sensed multispectral vegetation indices (VIs) have similar pattern as that of crop coefficients (Kc). Hence, Kc can be modelled using VIs. The Kc derived from VI responds to actual field conditions and captures spatial variability. Thus, VI based approach can be used for crop identification, acreage estimation and precision irrigation management. Furthermore, yield and quality of moisture sensitive chickpea crop can be considerably increased by applying precise irrigation in critical stages though it is a rabi crop. The present investigation entitled ‘Estimation of Evapotranspiration of Chickpea using Vegetation Indices Based Crop Coefficients’ was undertaken with major objective of identifying the most appropriate VI having highest correlation with crop coefficients of rabi chickpea crop in order to estimate the water demand. The study was conducted in Akola district located in Maharashtra. Multidate Sentinel 2 A (MSI sensor) satellite images were used to extract most commonly used vegetation indices RVI, NDVI, NDWI and SAVI. The spectral behaviour of the chickpea crop suggested that the VIs follow a similar pattern to crop coefficients. The two stage hybrid classification technique of remote sensing was employed to compute the crop acreage. The results showed an overestimation of 3.12% than the crop statistics published by the Department of Agriculture, Government of Maharashtra. The values of multi-date vegetation indices RVI, NDVI, NDWI and SAVI were distributed according to the age of the crop on each day of satellite data acquisition. Simple linear regression analysis was applied to derive the relationship between the mean weekly VI values and the week-wise crop coefficients (Kc) recommended by MPKV Rahuri and the relationships were established in the form of prediction models. All the vegetation indices exhibited good correlation with crop coefficients (Kc) with high R² values. However, NDWI-Kc model outperformed all other regression models. NDWI-Kc model showed highest R² and D values of 0.9550 and 0.9884 respectively with lowest values of SE, RMSE and PD of 0.0743, 0.0698 and 4.1016 respectively. Hence, NDWI was identified as the most superior remote sensing indicator for estimation of chickpea crop coefficients. The weekly crop coefficients were derived from the best performing NDWI-Kc model and the crop water requirement was estimated as 248.23 mm for chickpea crop. Crop water demand of rabi chickpea in Akola district was determined as 213.4138 Mm3. The outcomes of this study show the potential of multispectral vegetation indices for estimating spatial crop coefficients, leading to the determination of site-specific crop water demand and thus ultimately helping in precise irrigation water management, by providing irrigation with high water use efficiency and saving significant amount of water.
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    ThesisItemOpen Access
    ESTIMATION OF EVAPOTRANSPIRATION OF CHICKPEA USING VEGETATION INDICES BASED CROP COEFFICIENTS.
    (Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-11-28) AKKARA, MONCY S.; Pimpale, Dr. A. R.
    Ever growing water demand of world along with the severe reduction in water availability- quantitatively and qualitatively, necessitates monitoring and management of existing water resources in the best possible way. Agriculture being major shareholder of fresh water consumption calls for an immediate action to adopt proper irrigation methods and develop technology to make judicious use of water. Better estimation of irrigation water requirements is essential for water conservation aspects as well as better yield and economic aspects. Evapotranspiration being the major consumptive use of irrigation water, crop evapotranspiration represents crop water requirement and is calculated by FAO-56 procedures based on literature derived crop coefficients. Irrigation scheduling based on literature derived crop coefficients often leads to over irrigation due to the non optimal actual field conditions and spatial and temporal variations in Kc. Remotely sensed multispectral vegetation indices (VIs) have similar pattern as that of crop coefficients (Kc). Hence, Kc can be modelled using VIs. The Kc derived from VI responds to actual field conditions and captures spatial variability. Thus, VI based approach can be used for crop identification, acreage estimation and precision irrigation management. Furthermore, yield and quality of moisture sensitive chickpea crop can be considerably increased by applying precise irrigation in critical stages though it is a rabi crop. The present investigation entitled ‘Estimation of Evapotranspiration of Chickpea using Vegetation Indices Based Crop Coefficients’ was undertaken with major objective of identifying the most appropriate VI having highest correlation with crop coefficients of rabi chickpea crop in order to estimate the water demand. The study was conducted in Akola district located in Maharashtra. Multidate Sentinel 2 A (MSI sensor) satellite images were used to extract most commonly used vegetation indices RVI, NDVI, NDWI and SAVI. The spectral behaviour of the chickpea crop suggested that the VIs follow a similar pattern to crop coefficients. The two stage hybrid classification technique of remote sensing was employed to compute the crop acreage. The results showed an overestimation of 3.12% than the crop statistics published by the Department of Agriculture, Government of Maharashtra. The values of multi-date vegetation indices RVI, NDVI, NDWI and SAVI were distributed according to the age of the crop on each day of satellite data acquisition. Simple linear regression analysis was applied to derive the relationship between the mean weekly VI values and the week-wise crop coefficients (Kc) recommended by MPKV Rahuri and the relationships were established in the form of prediction models. All the vegetation indices exhibited good correlation with crop coefficients (Kc) with high R² values. However, NDWI-Kc model outperformed all other regression models. NDWI-Kc model showed highest R² and D values of 0.9550 and 0.9884 respectively with lowest values of SE, RMSE and PD of 0.0743, 0.0698 and 4.1016 respectively. Hence, NDWI was identified as the most superior remote sensing indicator for estimation of chickpea crop coefficients. The weekly crop coefficients were derived from the best performing NDWI-Kc model and the crop water requirement was estimated as 248.23 mm for chickpea crop. Crop water demand of rabi chickpea in Akola district was determined as 213.4138 Mm3. The outcomes of this study show the potential of multispectral vegetation indices for estimating spatial crop coefficients, leading to the determination of site-specific crop water demand and thus ultimately helping in precise irrigation water management, by providing irrigation with high water use efficiency and saving significant amount of water.
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    ThesisItemOpen Access
    Title : DESIGN AND DEVELOPMENT OF SUBSOILER ATTACHMENT TO ROTAVATOR
    (Publisher : Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-11-24) Authors : KHARAD, SAGAR DNYANDEV.; Advisor : Thakare, Dr. S. H.
    Abstract : The project entitled “Design and Development of Subsoiler attachment to Rotavator”. Farm mechanization increasing in the most parts of the world is an effort to increase the crop production. This trend is viewed with concern in most countries due to soil degradation caused by compaction, which occurs when heavy agricultural machinery is used for primary and secondary tillage operations. Compaction of soil reduces hydraulic conductivity while increasing bulk density and soil strength, affecting the soil workability, crop growth, yield and quality. Deep tillage equipment such as the subsoiler, which loosen the soil by generating cracks and fissures beneath the compacted layer, used to remove the soil compaction. Therefore, subsoiler attachment to rotavator was developed to solve the problem of soil compaction. The field performance of implement was conducted at subsoiling depth of 250 mm, 350 mm and 450 mm and at forward speed of operation of 2.5 km/h, 3.0 km/h and 3.5 km/h. The soil strength, forward speed of operation, draft requirement, Power requirement, theoretical field capacity, effective field capacity, field efficiency, wheel slippage and fuel consumption are evaluated at different subsoiling depths and forward speed of operation. The cone index values before performing operations shows more soil resistance and the cone index values after performing operation of implement shows less soil resistance. The depth of operation of 450 mm and forward speed of 2.5 km/h was found suitable for operation. The draft requirement, Power requirement, theoretical field capacity, effective field capacity, field efficiency, wheel slippage and fuel consumption were found to be 1198.8 kgf, 11.09 kW, 0.375 ha/h, 0.255 ha/h, 68 per cent, 9.45 per cent and 5.78 l/h respectively. Cost of operation per hectare of rotavator without subsoiler attachment was found to be Rs. 1867.5 and for rotavator with subsoiler attachment was found to be Rs. 2670.26.
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    ThesisItemOpen Access
    Title: DESIGN AND DEVELOPMENT OF PEELER CUM CUTTER FOR MEDICINAL PLANTS (ROOTS).
    (Publisher : Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-10-21) Authors: JADHAV, PRIYANKA DATTATRAY.; Advisor: Patil, Dr. B. N.
    Abstract: Shatavari (Asparagus racemosus) is climbing Ayurvedic plant with tuberous roots. It belongs to family “Asparagaceae”. It is traditionally used herb for its benefits like antidepressant, antioxidant, diuretic, antiepileptic, anti-HIV, antiplasmoidal etc. The process of peeling and cutting of medicinal roots like Shatavari is labour-intensive and time consuming operation done manually mostly by women labour. Hence, to reduce labour, human contamination and time requirement a power operated peeling cum cutting machine was developed. The physical properties of Shatavari roots were studied. The length, top diameter and bottom diameter of Shatavari root was found out to be 193.47 mm, 10 mm and 7.15 mm, respectively. The geometric mean diameter was 23.81 mm while sphericity and aspect ratio were 0.127 and 19.67. True density and bulk density of Shatavari roots were 0.66 g/cc and 0.36 g/cc. Moisture content was 73.80% (wb) for Shatavari roots while static coefficient of friction and angle of repose 0.38 and 33.25o, respectively. The peeling cum cutting machine was designed and developed, then the performance was evaluated. The main component of machine includes main frame, feeding unit, peeling unit, cutting unit, driving mechanism and 0.5 hp electric motor with stabilizer. The trials were performed by varying motor speed (200 to 300 rpm), feed rate (1 to 3 kg/batch) and two types of peeling sheets (metal sheet and emery paper sheet) to determine different responses viz. washing efficiency (%), peeling efficiency (%), cutting efficiency (%), peel ratio, throughput capacity (kg/h) and overall efficiency (%). Optimal custom design of response surface methodology in Design Expert Software was used to optimize machine parameter for better overall efficiency and lower peel ratio. Optimum machine performance with maximum peeling efficiency (94.93%) and minimum peel ratio (0.069) obtains at motor speed of 250 rpm and feed rate of 3 kg/ batch for metal sheet.
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    ThesisItemOpen Access
    Description : The present investigation was conducted at Department of Irrigation and Drainage Engineering, College of Agriculture Engineering and Technology, Akola, Dr. PDKV, Akola during the year 2020-2021 for calibration and validation of AquaCrop model for irrigated okra crop.
    (Publisher : Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-10-04) Authors : SIRSAT, LAXMAN GOVINDRAO.; Advisor : Wadatkar, S. B.
    Abstract : The present study entitled “calibration and validation of AquaCrop model for irrigated okra crop” was conducted at Department of Irrigation and Drainage Engineering, Dr. PDKV, Akola. Predicting attainable yield under water limiting condition is an important goal in rainfed agriculture. Proper irrigation planning is not only essential for water saving, but also for yield enhancement and it is only possible when an accurate and reliable decision-making tool has been adopted. AquaCrop is one of the model extensively used for irrigation plaining purposes. To evaluate the performance of the model, entitled study “Calibration and Validation of AquaCrop model for irrigated okra crop” was undertaken, with objective to calibrate and validate this AquaCrop model. AquaCrop model was calibrated using okra production data for the period 3rd December 2016 to 14th March 2017. The harvest index was observed as 86% for the okra. Thus, validation was carried out without any further adjustment to the calibrated parameters. The model validated for the period 20th November 2017 to 1st March 2018. Using irrigation treatment T1 and T2. Two statistical parameters i.e. root mean square error (RMSE) and Nash Sutcliffe coefficient of efficiency (R2Ns) were used as performance indicator. Results indicated that both statical parameters were in acceptable limit for both calibration and validation period. Testing of two formulated Irrigation Schedules was carried out for period of 3rd November 2018 to 12th February 2019. AquaCrop model was tested for two different irrigation schedules formulated during 2018-19 and it was observed that Iirrigation schedule S0 (80 % ETc with PM) was best fitted in terms of water saving and yield obtained as compared to S1 (60 % ETc with PM) irrigation schedules.
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    ThesisItemOpen Access
    Title : CALIBRATION AND VALIDATION OF AQUACROP MODEL FOR IRRIGATED WHEAT CROP.
    (Publisher : Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-10-04) Authors : ASOLKAR, SURAJ DNYANDEO.; Advisor : Mankar, A. N.
    Abstract : Predicting attainable yield under water limiting conditions is an important goal in rainfed agriculture. Proper irrigation planning is not only essential for water saving, but also for yield enhancement and it is possible only when an accurate and reliable decision-making tool has been adopted. AquaCrop is one of the model, extensively used for irrigation planning purposes. To evaluate the performance of the model entitled study “Calibration and Validation of Aquacrop model for Irrigated Wheat Crop” was undertaken with objectives to calibrate and validate the AquaCrop model. AquaCrop model was calibrated using Wheat production data for the period 13th December 2010 to 30th March 2011. The harvest index was observed as 32 % for Wheat. Thus, validation was carried out without any further adjustment to calibrated parameter. The model validated for the period 8th December 2011 to 15th March 2012. Using irrigation level I1 to I4. Two statistical parameters i.e. root mean square error (RMSE) and Nash Sutcliff coefficient of efficiency (R2NS) were used as performance indicator. Results indicated that both statistical parameters were in acceptable limit for both calibration and validation period. Verification of four formulated Irrigation schedules was carried out for the period of 11th December 2012 to 18th March 2013. Simulations were carried out using calibrated model for the formulated schedules. The R2NS value 0.9702 was obtained in the perfect fit limit and RMSE value was observed as 0.8998 q for yield. Highest water use efficiency was recorded for schedule S0 (0.6 IW/CPE) followed by S1 (0.8 IW/CPE) S2 (1.0 IW/CPE) S3 (1.2 IW/CPE) which may be due to lowest water use. Schedule S2 (1.0 IW/CPE) recorded second highest yield with water use efficiency of 0.79, with slightly decrease in water use efficiency i.e. 0.77 for schedule S3 (1.2 IW/CPE) yield was obtained to be highest which is 41.14 q/ha. Therefore S3 (1.2 IW/CPE) should be used for wheat production.
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    ThesisItemOpen Access
    Title : VEGETATION INDICES BASED CROP COEFFICIENTS TO ESTIMATE EVAPOTRANSPIRATION OF WHEAT.
    (Publisher : Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-10-12) Authors : KOSLE, ABHA ANIE.; Advisor : Pimpale, A. R.
    Abstract : Water is regarded as "Blue Gold," and is considered to be the most critical issue of the current century. Water scarcity is continuously becoming the most prominent environmental constraint limiting plant growth in many arid and semi-arid regions and can adversely affect food security worldwide Precise irrigation water management is needed in order to utilize scare water resources effectively. The water requirements of crops are generally estimated by guidelines provided in FAO-56 bulletin in which tabulated values of crop coefficients (Kc) are used. These crop coefficients are point based and actual crop evapotranspiration (ETc) is crucially dependent on crop coefficient curves. Remote Sensing derived multispectral vegetation indices (VIs) have similar pattern as that of crop coefficients (Kc). Therefore, VIs can be used to model crop coefficients and utilized as proxy Kc. The use of VI can give spatial dimension to Kc and thus spatial variability of water requirement can be well captured. Therefore, the present investigation entitled ‘Multispectral Vegetation Indices-based Crop coefficients for Irrigation Water Management’ was undertaken with major objective of finding the most appropriate VI showing close relationship with crop coefficients of rabi sorghum and wheat crops. The study was carried out in Pratapgarh district situated in Uttar Pradesh. Images of Sentinel 2 A, MSI sensor were used to generate multi temporal commonly used vegetation indices RVI, NDVI, NDWI and SAVI. Spectral behavior of wheat crop indicated that the VIs follows the similar pattern as that of crop coefficients. The crop acreages were computed by utilizing two stage hybrid classification of remote sensing. These estimates showed deviation of 4.43 % from the estimates of Department of Agriculture, for wheat crop. The values of multi-date vegetation indices RVI, NDVI, NDWI and SAVI were arranged according to the age in terms of weeks. The week-wise crop coefficients (Kc) recommended by MPKV Rahuri were used to form the relationship with VIs. Linear regression analysis was applied and the relationships were established in the form of prediction models. It was found that all the vegetation indices (VIs) have reasonably good correlation with crop coefficients (Kc) with higher R² values. However, NDWI-Kc model and showed best performance in case of wheat crop. For wheat crop, NDWI-Kc model showed highest R² and D values of 0.9485 and 0.991, respectively with lowest values of SE, RMSE and PD of 0.0841, 0.079 and 2.08, respectively. Therefore, NDWI was found most preferred remote sensing indicators for estimation of wheat crop coefficients. These best performing models were utilized to estimate week-wise crop coefficients. The crop water requirements were estimated and found 405.74 mm for wheat crop. Water demands for wheat crop were estimated. For wheat crop Water demand of Pratapgarh district was found 63.21 Mm3. Results of this study demonstrate the potential of multispectral vegetation indices for estimating spatial crop coefficients leading to correct site-specific crop water demand resulting in precise irrigation water
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    ThesisItemOpen Access
    Title : PROTECTIVE IRRIGATION PLANNING FOR RAINFED CROPPING AT AKOLA STATION FOR CLIMATE RESILIENT AGRICULTURE
    (Publisher : Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-10-04) Authors : TALOLE, RUSHIKESH SURESH; Advisor : Kale, M. U.
    Abstract : The present study entitled “Protective Irrigation Planning for Rainfed Cropping at Akola Station for Climate Resilient Agriculture” was conducted at Department of Irrigation and Drainage Engineering, Dr. PDKV, Akola. Annual and weekly climate variability in terms of rainfall, minimum and maximum temperature were analysed for the period from 1998 to 2019. The increase in average annual maximum and minimum temperature for all stations in Akola was found as 0.8% and 1.5%, respectively. The average reduction in annual rainfall for Akola district was 99.02 mm (11.76%). The variation in average weekly rainfall, average weekly maximum temperature and average weekly minimum temperature was accessed for SMW 23 to SMW 39 in Akola district. The maximum and minimum weekly reference evapotranspiration during monsoon season was observed in SMW-23 (June) and SMW-31 (August), respectively. The high values were may be due to high and low temperature during June and August. The reference evapotranspiration varies from 6.39 mm day-1 to 3.75 mm day-1. The maximum monthly rainfall and effective rainfall was observed during the month of July, followed by August, June and September. The highest effective rainfall was found in Patur taluka followed by Barshitakali, Murtizapur, Akola, Akot, Telhara and Balapur. Crop water requirement for Cotton, Pigeon Pea and Soybean was estimated using CropWat 8.0 using crop coefficient approach for all stations of Akola. The Cotton and Pigeon pea crop requires at least 37.3 mm/month, 120.9 mm/month, 121.4 mm/month, 114.7 mm/month, and 18.9 mm/month irrigation water during September, October, November, December and January respectively. Peak irrigation requirement of cotton and pigeon pea was found in the month of November. The protective irrigation schedule was generated using CropWat 8.0 for Cotton, Pigeon Pea and Soybean for all stations of Akola. There is no need of protective irrigation for soybean crop due to low irrigation requirement during Kharif season. The amount of protective irrigation for Cotton and pigeon pea requires protective irrigation in the month of October (>130mm) followed by December (>128mm), November (>65mm). The protective irrigation planned for the study area will help to increase the crop production.
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    ThesisItemOpen Access
    Title : CALIBRATION AND VALIDATION OF AQUACROP MODEL FOR IRRIGATED CHILLI CROP.
    (Publisher : Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra., 2022-10-04) Authors : GARDE, VAIBHAV ,BABASAHEB.; Advisor : Deshmukh., M. M.
    Abstract : Predicting attainable yield under water limiting condition is an important goal in rainfed agriculture. Proper irrigation planning is not only essential for water saving, but also for yield enhancement and it is only possible when an accurate and reliable decision-making tool has been adopted. AquaCrop is one of the models extensively used for irrigation plaining purposes. To evaluate its performance, a study entitled ‘Calibration and Validation of AquaCrop model for irrigated chilli crop’ was undertaken, with objective to calibrate and validate this AquaCrop model and also to verify the field results with the simulated outputs. Experimental study on chilli crop was carried out during 2014-15, 2015-16 and 2016-17. AquaCrop model was calibrated using chilli production data for the period 21st July 2014 to 19th January 2015. The harvest index was observed as 77 % for the chilli whereas, water productivity were 18 g/m2. Thus, validation was carried out without any further adjustment to the calibrated parameters. The model validated for the period 21st July 2015 to 19th January 2016. Two statistical parameters i.e. root mean square error (RMSE) and Nash Sutcliffe coefficient of efficiency (R2Ns) were used as performance indicator. Results indicated that both statistical parameters were in acceptable limit for both calibration and validation period. Using calibrated model different irrigation schedules were tested for the year 2016-17 and it was found that S1 (80 % ET with PM) irrigation schedule was best as compare to other irrigation schedule in terms of yield and water saving.