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 Water is the major constraint to crop production in many parts of the world.  To sustain crop production in water scarce environments, deficit irrigation.

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Presentation on theme: " Water is the major constraint to crop production in many parts of the world.  To sustain crop production in water scarce environments, deficit irrigation."— Presentation transcript:

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2  Water is the major constraint to crop production in many parts of the world.  To sustain crop production in water scarce environments, deficit irrigation (DI) is a suggestable irrigation practice.  DI is an irrigation strategy in which water is applied less than the full water requirement of the crop.  Citrus, the third important fruit crop in India, has low productivity and it varies widely from year to year depending upon climate and water availability in different regions of the country.  In changing climate scenario, it is utmost essential to optimize water management and prediction of yield of the crop.

3 DI 50 : Irrigation at 50% ETc DI 75 : Irrigation at 75% ETc PRD 50 : Irrigation at 50% ETc through PRD PRD 75 : Irrigation at 75% ETc through PRD FI : Irrigation at 100% ETc throughout the crop period Treatment details of sustained deficit irrigation (DI) and Partial root zone drying (PRD) irrigation Scheduling Replication: 4; Plants per replication: 2; Design: RBD

4 1.2 m 1.0 m 0.9 m Tree stem Lateral pipe Drip emitter Wetted zone of emitter Micro tube Layout of drip emitters in tree basin and their wetted zone under PRD

5 The water application for fully-irrigated trees was computed as: ETc = Kp x Kc x Ep The volume of water applied under 100% ETc was estimated based on the formula (Germanà et al., 1992): V id = π (D 2 / 4)  (ET c – R e ) / E i Irrigation water quantity estimation

6 Measurements and analysis Soil water measurement Leaf and stem water potential measurement For Relative leaf water contentLeaf physiological parameters

7 Canopy reflectance Root sampling and analysis

8 Mature Kinnow fruits on trees Harvested Kinnow fruits Juice of Kinnow Analysis of Juice

9 1.The water stress integral (S ψ ) for each treatment was calculated using the midday leaf and xylem water potential data, according to the equation defined by Myers (1988): S ψ = where S ψ is water stress integral (MPa day), ψ i, i+1 is average midday leaf/stem water potential for any interval i and i+1 (MPa), c is maximum leaf/stem water potential measured during the study and n is number of days in the interval. 2. a. Relative leaf water content (RLWC )was determined by the formula (Bowman, 1989): RLWC (%) = {(FW - DW) / (TW - DW)} x 100 b. Leaf water concentration (LWC) was determined using the formula (Peñuelas et al., 1997): LWC = {(FW−DW) / (FW)} x 100 Indices

10 3. The spectral reflectance indices related to water deficit conditions are calculated as: Water band index (WBI) = (R 900 ) / (R 970 ) (Penuelas et al., 1995); Normalized Difference water index (NDWI) = (R 857 – R 1241 ) / (R 857 + R 1241 ) (Gao, 1995); Moisture stress index (MSI) = (R 1599 ) / (R 819 ) (Hunt et al., 1989); Normalised difference infrared index (NDII) = (R 819 -R 1649 ) / (R 819 +R 1649 ) (Jackson et al., 2004), Simple ratio (proposed) = (R 1360 ) / (R 2250 ) where R and the subscript numbers indicate the light reflectance at the specific wavelength (in nm).

11 Treatments20102011 NPKNPK DI 50 2.31a0.15a1.42a2.43a0.16a1.44a DI 75 2.46a0.19a1.54b2.46b0.19a1.56c PRD 50 2.35a0.18a1.48c2.45b0.18a1.49d PRD 75 2.47b0.21a1.59a2.49c0.19a1.61b FI 100 2.69c0.22a1.64c2.72d0.20a1.66d Total N, P and K in leaf (%, dry weight basis) of ‘Kinnow’ mandarin as affected by various irrigation treatments Optimum range of leaf-N (2.28–2.53%), P (0.10–0.13% ), and K (1.28–1.63% ) for Kinnow (Hundal and Arora, 2001; Srivastava, 2011).

12 Treatments20102011 FeMnCuZnFeMnCuZn DI 50 54.0a48.6a7.3a24.7a56.8a50.3a7.8a24.9a DI 75 58.4a57.8a7.9a25.6a58.7a58.2a8.2a24.1a PRD 50 55.6a51.2a7.3a25.2a56.7a51.8a7.9a25.5a PRD 75 59.9a58.4a8.2a25.8a61.4a58.9a8.4a26.9a FI 100 62.6b61.5b8.2a26.9b62.8b61.6a8.9a27.2b Total Fe, Mn, Cu and Zn in leafs (ppm, dry weight basis of ‘Kinnow’ mandarin as affected by various irrigation treatments Optimum values (62.3–89.4 ppm Fe, 58.7 – 76.3 ppm Mn, 8.1 – 10.3 ppm Cu and 26.3 – 28.5 ppm Zn) of Kinnow mandarin (Hundal and Arora, 2001; Srivastava, 2011).

13 Leaf/stem water potential and leaf /stem water stress integral during 2010 and 2011

14 RLWC and LWC in 2010 1nd 2011

15 Treatments20102011 PngsTrLWUEPngsTrLWUE DI 50 2.89a21.07b1.66b1.74c2.94a20.50b1.53b1.92a DI 75 2.92a24.80d1.84d1.58a3.41b23.48d1.60d2.13b PRD 50 2.90a20.13a1.43a2.02e3.38b20.04a1.31a2.58d PRD 75 2.95b23.13c1.79c1.65b3.45b22.83c1.57c2.17b FI 100 3.88c37.78e2.081.86d4.37c31.07e1.74e2.51c Leaf physiological parameters under different irrigation treatments in 2010 and 2011

16 Treatments20102011 THSDCDCVTHSDCDCV DI 50 33.4a20.4a25.8a0.81a21.7a19.2a20.1a0.64a DI 75 36.2b22.5b31.3b0.83a26.7b20.9b27.5b0.77a PRD 50 32.5a19.7a25.3a0.79a21.0a19.0a18.8a0.60a PRD 75 35.9b22.0b30.9b0.80a26.5b20.9b26.9b0.74a FI 100 40.7c26.2c48.7c0.86b36.0c25.6c32.3c0.98b Tree growth under various irrigation treatment

17 Treat ments Hyperspectral Indices 20102011 WBINDWIMSINDIISRWBINDWIMSINDIISR DI 50 1.0560.0420.5610.2663.0020.9920.0810.4620.2192.937 DI 75 0.9660.0350.4720.2432.8020.9810.0640.4170.2062.811 PRD 50 1.0060.0370.4810.2512.8620.9840.0760.4310.2072.828 PRD 75 0.9320.0340.4710.2412.8470.9520.0570.4060.2052.796 FI 100 0.9170.0330.4690.2392.7110.8150.0310.3840.2032.629 Mean water band index (WBI), normalised difference water index (NDWI), moisture stress index (MSI) and Normalised difference infrared index (NDII) of Kinnow mandarin under various irrigation treatments. Parameters are significantly different from each other

18 Treatments2010 No. fruits dropped/tree No. fruits harvested /tree Average fruit weight (g) Fruit yield (t ha -1 ) IWUE (t ha -1 mm -1 ) WUE (t ha -1 mm -1 ) DI 50 170d (96 *, 52 **, 22 *** ) 671a152.7a51.23a0.108c0.056c DI 75 135c (77, 40, 18) 718b161.6b58.01c0.081b0.051b PRD 50 148b (80, 48, 20) 703b160.7b 56.48b (8.7%) 0.119d (83%) 0.062c PRD 75 100a (61, 28, 11) 755c163.0b58.73c0.082b0.053b FI 100 92a (64, 15, 13) 763c162.3b61.91d0.065a0.047a Fruit yield, IWUE, and WUE in 2010

19 Treatments2011 No. fruits dropped/tree No. fruits harvested/ tree Average fruit weight (g) Fruit yield (t ha -1 ) IWUE (t ha -1 mm -1 ) WUE (t ha -1 mm -1 ) DI 50 151e (82 *, 50 **, 19) 682a154.7a52.75a0.150c0.071c DI 75 109c (66, 32, 11) 739c163.1b60.26c0.114b0.067b PRD 50 126d (70, 46, 10)711b161.0b 57.23b (9.4%) 0.163d (81%) 0.077d PRD 75 89b (52, 27, 10)751c165.2b62.03c0.118b0.070c FI 100 79a (51, 20, 8)776d162.8b63.20c0.090a0.061a Fruit yield, IWUE, and WUE in 2011

20 Treatments2010 Juice content (%) TSS ( 0 Brix) TA (%) Ascorbic acid (mg/l) Reducing Sugar (mg/l) Total Sugar (mg/l) DI 50 43.7a11.41.02f120.4a50.4c73.8c DI 75 46.7b10.9c0.82b112.1a42.9b61.7a PRD 50 45.5b11.2b0.84b119.8a59.3d67.4b PRD 75 48.2b10.8b0.82b109.0c47.1c60.1a FI 100 49.6c10.8c0.81b116.3b37.2a66.4b Fruit quality parameters of Kinnow fruits in 2010

21 Treatments2011 Juice content (%) TSS ( 0 Brix) TA (%) Ascorbic acid (mg/l) Reducible sugar (mg/l) Total sugar (mg/l) DI 50 43.1a11.7 a0.96f128.7a54.7c75.4c DI 75 45.9b11.2c0.80d114.7a45.9b64.7a PRD 50 44.3b11.4b0.83e123.6a61.7d69.3b PRD 75 47.9b11.1b0.80b111.9c49.2b63.2a FI 100 49.5c10.9c0.79b119.1b38.7a68.7b Fruit quality parameters of Kinnow fruits in 2011

22 Parameters Fruit Yield SDCV Leaf- N Leaf- K Leaf- Fe Leaf - Zn SΨ l SΨ s RL WC LW C PnTrgs LW UE WBI ND WI MSI SD0.25 * CV0.33 * 0.69 * Leaf-N0.57 + NS0.29 * Leaf-K0.61 + NS0.41 * 0.43 * Leaf- FeNS Leaf-Zn0.58 * NS 0.41 * SΨ l 0.59 + 0.21 * 0.29 * 0.43 * 0.47 * NS SΨ s 0.62 + 0.26 * 0.32 * 0.52 * 0.49 * NS 0.93 + RLWC0.55 + 0.20 * 0.17 * 0.320.32 * NS 0.74 + 0.79 + LWC0.53 + NS 0.300.25 * NS 0.59 + 0.69 + 0.74 + Pn0.55 + NS0.23 * 0.85 + 0.44 * 0.78 + 0.360.62 + 0.53 + 0.66 + 0.55 + Tr0.51 + NS 0.69 * 0.51 + 0.43 * 0.290.78 + 0.83 + 0.71 + 0.69 + 0.61 + gs0.61 + NS 0.58 * 0.55 + 0.45 * 0.380.79 + 0.76 + 0.75 + 0.66 + 0.58 + 0.61 + LWUE0.60 + NS 0.47 * 0.36 * 0.42 * 0.210.73 + 0.69 + 0.59 + 0.48 + 0.39 + 0.69 + 0.57 * WBI0.57 + 0.29 * 0.59 + 0.47 * 0.44 * NS0.65 + 0.67 + 0.69 + 0.52 + 0.47 * 0.55 * 0.51 * 0.30 + NDWI0.53 * NS 0.53 * NS 0.38 * 0.48 * 0.57 * 0.40 * 0.33 * 0.49 * 0.40 * 0.21 * 0.59 + MSI0.79 + 0.22 * 0.23 * 0.51 + 0.40 * NS 0.44 * 0.41 + 0.52 + 0.47 + 0.42 + 0.43 + 0.45 * 0.17 + 0.59 * 0.54 * NDII0.49 * NS 0.43 * 0.36 * 0.27 * NS0.26 * 0.32 * 0.47 * 0.49 * 0.39 * 0.37 + 0.39 * 0.26 * 0.55 * 0.48 * 0.51 * SR0.61 + NS 0.54 + 0.36 * NS 0.57 + 0.62 + 0.63 + 0.58 + 0.47 + 0.50 + 0.44 * 0.20 * 0.84 + 0.59 * 0.60 * Correlation matrix (Pearson’s) for plant-based observations during 2010 and 2011 under DI

23 Paramete rs Fruit Yield SDCV Leaf- N Leaf- K Leaf- Fe Leaf - Zn SΨ l SΨ s RL WC LW C PnTrgs LW UE WBI ND WI MSI SD0.19 * CV0.27 * 0.59 * Leaf-N0.59 + NS0.23 * Leaf-K0.62 + NS0.30 * 0.21 * Leaf- FeNS Leaf-Zn0.58 * NS 0.33 * SΨ l 0.63 + 0.27 * 0.19 * 0.38 * 0.40 * NS SΨ s 0.69 + 0.29 * 0.22 * 0.42 * 0.49 * NS 0.91 + RLWC0.55 + 0.20 * 0.16 * 0.220.33 * NS 0.70 + 0.87 + LWC0.51 + NS 0.290.24 * NS 0.63 + 0.65 + 0.87 + Pn0.59 + NS0.20 * 0.84 + 0.40 * 0.74 + 0.310.54 + 0.55 + 0.60 + 0.50 + Tr0.57 + NS 0.61 * 0.48 + 0.38 * 0.270.80 + 0.77 + 0.66 + 0.59 + gs0.44 + NS 0.52 * 0.50 + 0.40 * 0.330.82 + 0.68 + 0.60 + 0.75 + LWUE0.60 + NS 0.38 * 0.33 * 0.40 * 0.280.74 + 0.67 + 0.50 + 0.49 + 0.37 + 0.64 + 0.59 * WBI0.50 # 0.21 * 0.27 * 0.58 + 0.42 * NS0.69 + 0.65 + 0.66 + 0.52 + 0.44 * 0.55 * 0.50 * 0.32 + NDWI0.49 * NS 0.50 * NS 0.37 * 0.44 * 0.59 * 0.40 * 0.34 * 0.44 * 0.43 * 0.17 * 0.55 + MSI0.59 + 0.15 * 0.11 * 0.51 + 0.41 * NS 0.46 * 0.35 + 0.38 + 0.47 + 0.42 + 0.47 * 0.19 + 0.73 * 0.50 * NDII0.40 * NS 0.43 * 0.39 * 0.21 * NS0.28 * 0.33 * 0.42 * 0.46 * 0.30 * 0.32 + 0.30 * 0.29 * 0.57 * 0.61 * 0.49 * SR0.64 + NS 0.54 + 0.37 * NS 0.59 + 0.64 + 0.59 + 0.44 + 0.51 + 0.40 * 0.22 * 0.81 + 0.74 * 0.63 * Correlation matrix (Pearson’s) for plant-based observations during 2010 and 2011 under PRD

24 PCDIPRD Variables Eigen value % variance Cumulative % of variance Variables Eigen value % variance Cumulative % of variance 1 SΨ s, Leaf- N, Leaf-K, SΨ l, RLWC 6.96440.20 SΨ s, Leaf-N, Leaf-K, SΨ l, RLWC 5.74438.46 2gs, Pn3.71633.5473.74gs, Pn2.89932.1170.57 3WBI, SR2.44915.2889.02WBI, SR2.21913.7784.34 Principal components with Eigen values and variances

25 Yield prediction under DI and PRD For DI (2011)

26 Conclusions  PRD at 50% FI produced 9% less fruit yield, with marginally lower vegetative growth of the plants in comparison to that under FI. However, 50% water saving under PRD 50 boosted the irrigation water use efficiency up to 83% higher than that under FI.  Yield prediction using PC-regression with leaf-N, leaf-K, stem water potential stress index, stomatal conductance and water band index gives satisfactory result. Therefore, this technique can be used for yield forecasting of citrus orchards under differential water stress condition and such methodology may be tried for other crops also.

27 THANK YOU


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