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Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 2 (2017) pp. 909-921 Journal homepage: http://www.ijcmas.com Original Research Article http://dx.doi.org/10.20546/ijcmas.2017.602.102 Dynamics of Nitrogen Uptake under Alternate Wetting and Drying Method of Water Management in Low Land Rice (Oryza sativa) Kishor Mote1*, V. Praveen Rao2, K. Avil Kumar2, V. Ramulu2 and M. Uma Devi2 1 Central Coffee Research Institute, Chikmagaluru-577117, Karnataka, India Water Technology Centre, Professor Jaysankar Telangana State Agriculture University, Hyderabad-500030, India 3 Department of Crop Physiology, Professor Jaysankar Telangana State Agriculture University, Hyderabad-500030, India 2 *Corresponding author: ABSTRACT Keywords SCMR readings, LCC ratings, Nitrogen uptake, Alternate wetting and drying, Lowland rice, Field water tube. Article Info Accepted: 20 January 2017 Available Online: 10 February 2017 A field study was conducted entitled with “Standardization of Alternate Wetting and Drying (AWD) method of water management in low land rice (Oryza sativa (L.) for up scaling in command outlets”. The treatments consisted of continuous submergence throughout the crop growing season besides AWD irrigation regimes with two pond water depths of 3 and 5 cm and drop in pond water levels in field water tube below ground level to 5, 10 and 15 cm depth. The eight treatments were laid out in randomized block design with three replications. Continuous Submergence (CS) registered higher nitrogen uptake 20.78, 45.52, 64.05 and 85.36 kg ha -1 at 30, 60, 90 DAT and at harvest, respectively which resulted it recorded significantly higher SPAD chlorophyll meter (SCMR) readings (42.74, 42.78) and Leaf Color Chart (LCC) ratings (3.83, 3.94) over rest of the irrigation regimes except that it was on par with Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 5-cm Below ground level (BGL) in field water tube (39.40, 39.59), (3.59, 3.51), Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube (41.21, 41.78), (3.73, 3.74) and Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 10-cm BGL in field water tube (40.04, 40.83), (3.69, 3.52). Introduction Rice (Oryza sativa L.) is one of the world‟s major food crops and as well as for India. The area under rice in India is 45 million ha with production of 106.19 million tonnes (Department of Agriculture, India, 2014). A tremendous amount of water is used for the rice irrigation under the conventional water management in lowland rice termed as „„continuous deep flooding irrigation‟‟ consuming about 70 to 80 per cent of the total irrigated fresh water resources in the major part of the rice growing regions in Asia including India (Bouman and Tuong, 2001; Bouman et al., 2007). However, irrigation water in India is becoming increasingly scarce and costly (Rijsberman, 2006). Rapid population growth, urbanization and multiple competing demands for water (i.e., drinking, 909 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 industrial uses) have contributed to irrigation water scarcity (Pingali et al., 1997; Tabbal et al., 2002). Tuong and Bouman (2003) estimate that, by 2025, about 2 million ha of Asia‟s irrigated dry-season rice and 13 million ha of its irrigated wet-season rice will experience physical water scarcity. The occurrence of water scarcity prompted researchers to find ways to optimize water use under water saving systems in irrigated rice fields in the tropics where high yield is critical to ensure food security (Rosegrant and Ringler, 1998). than that under continuous flooding (about 40%). Increasing N-use efficiency in AWD will help farmers reduce the amount of fertilizer inputs, increase their income, and facilitate their adoption of AWD to cope with water scarcity. Materials and Methods The experiment was laid out in a randomized block design with eight irrigation regimes comprising of two submergence levels above the ground (3 and 5 -cm) and three falling levels below ground surface (5, 10 and 15 -cm drop of water in field water tube) and farmers practice of continous standing water which were randomly allotted in three replications. The experimental soil was sandy clay in texture, moderately alkaline in reaction, nonsaline, low in organic carbon content, low in available nitrogen (N), medium in available phosphorous (P2O5) and potassium (K2O). Growing rice under AWD could consequently lead to a greater loss of applied fertilizer N and soil N compared with that under continous flooding conditions; the latter itself has been characterized as having low N-use efficiency (Peng et al., 2006). Belder et al., (2005) reported that N recovery of rice under AWD (about 20%) was significantly lower Treatment Details I1 Continuous submergence of 3 cm up to PI and thereafter 5 cm up to PM I2 AWD – Flooding to a water depth of 3 cm when water level drops to 5 cm BGL from 15 DAT to PM I3 AWD – Flooding to a water depth of 3 cm when water level drops to 10 cm BGL from 15 DAT to PM I4 AWD – Flooding to a water depth of 3 cm when water level drops to 15 cm BGL from 15 DAT to PM I5 AWD – Flooding to a water depth of 5 cm when water level drops to 5 cm BGL from 15 DAT to PM I6 AWD – Flooding to a water depth of 5 cm when water level drops to 10 cm BGL from 15 DAT to PM I7 AWD – Flooding to a water depth of 5 cm when water level drops to 15 cm BGL from 15 DAT to PM I8 AWD – Flooding to a water depth of 3 cm from 15 DAT to PI and thereafter 5 cm up to PM when water level drops to 15 cm The SCMR readings were recorded from 15 DAT to flowering at every 15 days interval for all the treatments. The youngest fully expanded leaf of a plant was used for the SCMR value measurement. The LCC ratings were measured under the body shade in the morning time. The LCC ratings were taken up to 50 per cent flowering. The plant samples collected for dry matter estimation at 30, 60, 90 DAT and at harvest from the respective 910 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 treatments were oven dried and finely ground in Willey mill and used for chemical analysis to estimate N content in the straw at 30, 60 and 90 DAT and in straw and grain at harvest. Nitrogen content of shoot and grain at harvest was estimated by Modified Micro Kjeldhal‟s Method as outlined by Jackson (1967) and expressed in percentage. The data on various parameters studied during the course of investigation were statistically analyzed as suggested by Gomez and Gomez (1984). Crop yield (dependent variable) was assumed as a function of various growth traits and the following straight line model was established by least square technique (Gomez and Gomez, 1984) as follows: 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube), I3 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 10-cm BGL in field water tube), I5 (Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube) and I6 (Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 10-cm BGL in field water tube) at 45 DAT in 2013 and I2 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube), I4 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 15-cm BGL in field water tube), I5 and I6 at 45 DAT in 2014 and at 60 DAT both in 2013 and 2014. The higher SCMR readings could be traced increased uptake of N in wet irrigation regimes over stressed regimes, which could be due to reduced leaching losses (Aulakh and Singh, 1997). On the other hand intermittent aerobic conditions in AWD irrigation regimes increased the average soil N supply or induced increased root development, or both in turn the SCMR, thus compensating for reduced growth during drought phases (Haefele et al., 2010). Further, the SCMR values between I7 and I8 at 45 DAT in 2013 and that between I3 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 10-cm BGL in field water tube), I7 (Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 15-cm BGL in field water tube) and I8 (Flooding to a water depth of 3-cm from 15 DAT to PI and 5-cm from PI to PM as and when pond water level drops to 15-cm BGL in field water tube) at 45 DAT in 2013 and 60 DAT in 2013 and 2014 were statistically on par. Where, Y = Grain yield of rice (g m-2) a = Y–axis intercept b = Regression coefficient x = Independent variable i.e., Growth and yield components Likewise, to characterize the crop weather relationship all growth and yield components and grain yield were related to weather elements adopting the above linear model. Results and Discussion SCMR readings The SCMR readings were not significantly influenced by different irrigation treatments at 15 and 30 DAT, but were significant at 45 and 60 DAT. Both at 45 and 60 DAT significantly higher SCMR readings were registered by the crop in I1 (Continuous Submergence depth of 3-cm from transplanting to PI and 5 cm from PI to PM) over other AWD irrigation regimes (Table 1) except that it was statistically on par with I2 (Flooding to a water depth of 3-cm between The SPAD meter is a simple portable diagnostic tool used for monitoring crop N 911 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 status in situ in the field. The relationship between leaf N content and SCMR value indicated that when a variety will show higher SCMR reading, it has certainly higher amount of nitrogen (Islam et al., 2009). To achieve the maximum yield target, the N concentration of the upper most fully expanded leaf must be maintained at or above 1.4 g N m-2 (leaf area basis) (Islam et al., 2009). Leaf N status at this critical level gives a SPAD value of 35 regardless of genotypes (Dobermann and Fairhurst, 2000). The SPAD meter- based N management appeared to be more efficient and would save 20 – 30 kg N ha-1 than the conventional N management practices to produce similar grain yield (Miah and Ahmed, 2002). Cabangon et al., (2011) opined that a combination of AWD and SCMR based N management by maintaining a critical value of 38 can contribute to savings in irrigation water and fertilizer N while maintaining high yield as in continuous submergence conditions with fixed time and rate of nitrogen application (180 kg ha−1). It can be noticed that in the present study the AWD treatments I5 and I6 registered SCMR readings more than 38 and were on par with continuous submergence treatment (I1). A good correlation between leaf N content and the SCMR reading was reported by Cabangon et al., (2011) suggesting that the SCMR reading can be used to estimate leaf N of rice grown under AWD in a way similar to that under continuous submergence.A good correlation was observed between N uptake and SPAD readings with a determination coefficient of R2 = 75.7% (Fig. 1). These results suggest that SPAD-based management can be used for timing of N topdressing for a given variety at a specific crop growth stage or during the entire growing period under AWD irrigation regime. The result was similar to previous findings for rice under continuous submergence conditions (Cabangon et al., 2011). The findings implied that SPAD can be used to assess N uptake of rice under AWD conditions as it is used in continuous submergence rice (Cabangon et al., 2011). As large part of N in the plant is allocated to the leaves throughout the life of the plant and photosynthetic capacity per unit leaf area is considered to be an important factor related to crop productivity. Since leaf N concentration/N uptake is closely related to the leaf chlorophyll content, the measure of chlorophyll content can estimate the crop N status and thereby determine the need for additional N fertilizer. The chlorophyll (SPAD) meter provides an instantaneous, non-destructive indication of leaf chlorophyll or N concentration in the field. Figure 1 is a scatter diagram for N uptake versus SPAD readings of the present experiment. A good correlation was observed between N uptake and SPAD readings with a determination coefficient of R2 = 75.7%. These results suggest that SPAD-based management can be used for timing of N topdressing for a given variety at a specific crop growth stage or during the entire growing period under AWD irrigation regime. The result was similar to previous findings for rice under continuous submergence conditions (Cabangon et al., 2011). The findings implied that SPAD can be used to assess N uptake of rice under AWD conditions as it is used in continuous submergence rice (Cabangon et al., 2011). Leaf colour chart (LCC) ratings The LCC ratings were not significantly influenced by different irrigation treatments at 15 and 30 DAT, but were significant at 45 and 60 DAT. Both at 45 and 60 DAT significantly higher LCC ratings were registered by the crop in I1 (Continuous Submergence depth of 3-cm from transplanting to PI and 5 cm from PI to PM) over other AWD irrigation regimes (Table 2) except that it was statistically on par with I2 912 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube), I3 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 10-cm BGL in field water tube), I5 (Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube), I6 (Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 10-cm BGL in field water tube) and I7 (Flooding to a water depth of 5-cm between 15 DAT to PM as and when pond water level drops to 15-cm BGL in field water tube) at 45 DAT and I2 (Flooding to a water depth of 3cm between 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube), I3 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 10-cm BGL in field water tube) only in 2013, I5 and I6 at 45 DAT. Higher LCC rating in I2 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 5-cm BGL in field water tube) could be traced to favourable soil water balance, reduced leaching and better uptake of N. and impaired active transport and membrane permeability (Hsiao, 1973) resulting in reduced absorbing power. Nutrient uptake from the soil solution is also closely linked to soil water status. Thus a decline in soil moisture as indicated by soil moisture content and plant water balance parameters RWC and LWP in I4, I7 and I8 might have been associated with decrease in diffusion rate of nutrients from soil matrix to the absorbing root surface (Viets, 1972) in turn affecting the LCC ratings. A positive and significant correlation (P = 0.01) was observed between N-Uptake and LCC rating with a Determination Coefficient of R2 = 0.87 (Fig. 2). These results suggest that LCC-based management can be used for timing of N topdressing for a given variety at a specific crop growth stage or during the entire growing period under AWD irrigation regime. While SCMR readings provide objective information on the chlorophyll content of the leaf, the LCC rating is subjectively judged by visually differentiating the leaf colour. Figure 3 shows a good and highly significant (R2 = 0.89, P=0.01) correlation between LCC rating and SCMR readings. The result was similar to previous findings for rice under continuous submergence conditions (Cabangon et al., 2011). The findings implied that LCC can also be used to assess N uptake of rice under AWD. However, the LCC ratings registered in I2, I3, I6 and I7 at 45 DAT in 2013; I4 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 15-cm BGL in field water tube), I7 and I8 at 45 DAT in 2014; I4 and I8 at 60 DAT in 2013 and that between I4, I7 and I8 at 60 DAT in 2014 were statistically not significant. Significantly lowest LCC rating were recorded by the crop in I4 (Flooding to a water depth of 3-cm between 15 DAT to PM as and when pond water level drops to 15-cm BGL in field water tube) AWD irrigation regime in both the years. Nutrient uptake by plants is decreased under water stress conditions due to reduced transpiration (Yambao and O‟Toole, 1984) However, given the high cost of the SPAD meter, the LCC rating is potentially an inexpensive alternative tool to the SPAD meter (Furuya, 1987) and the LCC could be used instead of the SCMR readings for estimating leaf N or crop N status and for determining the timing of N top dressing. 913 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 Table.1 SCMR readings of rice as influenced by different AWD irrigation regimes during kharif 2013 and 2014 Code I1 I2 I3 I4 I5 I6 I7 I8 Description of Treatment Continuous submergence of 3 cm up to PI and thereafter 5 cm up to PM AWD – Flooding to a water depth of 3 cm when water level drops to 5 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 3 cm when water level drops to 10 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 3 cm when water level drops to 15 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 5 cm when water level drops to 5 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 5 cm when water level drops to 10 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 5 cm when water level drops to 15 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 3 cm from 15 DAT to PI and thereafter 5 cm up to PM when water level drops to 15 cm 15 DAT 2013 2014 31.40 37.77 30 DAT 2013 2014 38.48 37.17 45 DAT 2013 2014 39.73 40.39 60 DAT 2013 2014 42.74 42.78 35.74 40.22 36.89 35.83 38.74 38.84 39.40 39.59 36.91 40.37 35.96 35.72 37.92 37.50 37.92 38.40 39.28 37.78 33.44 34.32 35.18 35.55 33.41 33.52 35.31 39.19 38.46 36.72 39.55 40.09 41.21 41.78 33.95 39.97 38.03 37.10 39.33 39.17 40.04 40.83 36.73 40.36 36.60 36.87 36.06 36.43 35.63 36.23 38.12 40.72 35.20 35.68 35.71 35.61 35.22 35.55 SEm ± 1.51 1.43 1.46 1.12 1.09 1.14 1.86 CD at P = 5% NS NS NS NS 3.32 3.47 5.65 General Mean 35.93 39.54 36.63 36.17 37.77 37.94 38.19 PI – Panicle Initiation; PM – Physiological Maturity; DAT – Days After Transplanting; BGL – Below Ground AWD – Alternate Wetting and Drying SCMR- SPAD chlorophyll Meter Readings 914 1.66 5.04 38.58 Level Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 Table.2 LCC ratings of rice as influenced by different AWD irrigation regimes during kharif 2013 and 2014 15 DAT 30 DAT 45 DAT 60 DAT 2013 2014 2013 2014 2013 2014 2013 2014 Continuous submergence of 3 cm up to PI and thereafter 5 cm up 2.92 3.10 3.65 3.50 3.52 3.69 3.83 3.94 I1 to PM AWD – Flooding to a water depth of 3 cm when water level drops 2.66 3.07 3.25 2.98 3.35 3.51 3.59 3.51 I2 to 5 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 3 cm when water level drops 2.61 3.03 3.27 3.21 3.29 3.36 3.40 3.14 I3 to 10 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 3 cm when water level drops 2.74 2.84 3.10 2.37 2.43 2.7 2.54 2.36 I4 to 15 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 5 cm when water level drops 2.74 3.02 3.36 3.35 3.50 3.58 3.73 3.74 I5 to 5 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 5 cm when water level drops 2.81 2.82 3.28 3.29 3.47 3.54 3.69 3.52 I6 to 10 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 5 cm when water level drops 2.80 2.48 3.19 2.84 3.03 3.27 3.16 2.76 I7 to 15 cm BGL from 15 DAT to PM AWD – Flooding to a water depth of 3 cm from 15 DAT to PI 2.63 2.59 3.11 2.80 2.98 3.06 2.63 2.48 I8 and thereafter 5 cm up to PM when water level drops to 15 cm SEm ± 0.15 0.18 0.14 0.63 0.16 0.19 0.16 0.15 CD at P = 5% NS NS NS NS 0.49 0.56 0.49 0.46 General Mean 2.73 2.86 3.27 3.04 3.19 3.34 3.32 3.18 PI – Panicle Initiation; PM – Physiological Maturity; DAT – Days After Transplanting; BGL – Below Ground Level AWD – Alternate Wetting and Drying LCC- Leaf Color Chart Code Description of Treatment 915 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 Table.3 Nitrogen uptake (kg ha-1) of rice at 30, 60 and 90 DAT as influenced by different AWD irrigation regimes during kharif 2013, 2014 and pooled means 30 DAT 60 DAT 90 DAT 2013 2014 Pooled 2013 2014 Pooled 2013 2014 Pooled Continuous submergence of 3 cm up to PI and 22.45 24.37 23.41 49.00 51.34 50.17 72.77 75.50 74.14 I1 thereafter 5 cm up to PM AWD – Flooding to a water depth of 3 cm when 20.84 22.88 21.86 47.07 49.05 48.06 63.77 67.32 65.54 water level drops to 5 cm BGL from 15 DAT to I2 PM AWD – Flooding to a water depth of 3 cm when 19.96 21.17 20.57 46.49 48.57 47.53 61.30 65.78 63.54 water level drops to 10 cm BGL from 15 DAT to I3 PM AWD – Flooding to a water depth of 3 cm when 19.26 21.54 20.40 35.20 39.16 37.18 52.25 53.53 52.89 water level drops to 15 cm BGL from 15 DAT to I4 PM AWD – Flooding to a water depth of 5 cm when 20.95 23.05 22.00 48.03 50.52 49.28 68.64 72.90 70.77 water level drops to 5 cm BGL from 15 DAT to I5 PM AWD – Flooding to a water depth of 5 cm when 20.14 21.90 21.02 47.39 49.50 48.45 65.18 70.26 67.72 water level drops to 10 cm BGL from 15 DAT to I6 PM AWD – Flooding to a water depth of 5 cm when 19.38 21.09 20.23 45.93 45.86 45.90 60.60 62.63 61.61 water level drops to 15 cm BGL from 15 DAT to I7 PM AWD – Flooding to a water depth of 3 cm from 15 15.34 18.21 16.78 36.04 39.26 37.65 55.99 56.54 56.26 DAT to PI and thereafter 5 cm up to PM when I8 water level drops to 15 cm SEm ± 1.77 1.42 1.45 1.67 2.12 1.70 3.06 2.48 2.70 CD at P = 5% NS NS NS 5.08 6.44 5.15 9.27 7.51 8.19 General Mean 19.79 21.77 20.78 44.39 46.65 45.52 62.56 65.55 64.05 PI – Panicle Initiation; PM – Physiological Maturity; DAT – Days After Transplanting; BGL – Below Ground Level AWD – Alternate Wetting and Drying Code Description of Treatment 916 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 Table.3a Nitrogen uptake (kg ha-1) of rice at harvest as influenced by different AWD irrigation regimes during kharif 2013, 2014 and pooled means Grain Straw Total 2013 2014 Pooled 2013 2014 Pooled 2013 2014 Pooled Continuous submergence of 3 cm up to PI and 59.27 61.84 60.56 43.55 47.01 45.28 102.83 108.85 105.84 I1 thereafter 5 cm up to PM AWD – Flooding to a water depth of 3 cm when 45.11 48.94 47.03 35.98 39.87 37.93 81.09 88.81 84.95 water level drops to 5 cm BGL from 15 DAT to I2 PM AWD – Flooding to a water depth of 3 cm when 40.75 46.71 43.73 32.84 37.49 35.17 73.59 84.20 78.89 water level drops to 10 cm BGL from 15 DAT I3 to PM AWD – Flooding to a water depth of 3 cm when 32.91 35.01 33.96 27.41 30.12 28.77 60.32 65.13 62.72 water level drops to 15 cm BGL from 15 DAT I4 to PM AWD – Flooding to a water depth of 5 cm when 54.42 58.82 56.62 39.95 44.92 42.44 94.37 103.75 99.06 water level drops to 5 cm BGL from 15 DAT to I5 PM AWD – Flooding to a water depth of 5 cm when 52.05 56.64 54.35 37.42 42.62 40.02 89.47 99.26 94.36 water level drops to 10 cm BGL from 15 DAT I6 to PM AWD – Flooding to a water depth of 5 cm when 46.83 52.18 49.51 30.94 35.02 32.98 77.78 87.20 82.49 water level drops to 15 cm BGL from 15 DAT I7 to PM AWD – Flooding to a water depth of 3 cm from 42.09 44.94 43.52 30.15 32.04 31.10 72.23 76.98 74.60 15 DAT to PI and thereafter 5 cm up to PM I8 when water level drops to 15 cm SEm ± 2.54 2.21 2.22 2.94 1.84 2.00 4.53 3.31 3.83 CD at P = 5% 7.69 6.71 6.74 6.30 5.59 6.06 13.73 10.04 11.62 General Mean 46.67 50.63 48.66 34.78 38.63 36.71 81.46 89.27 85.36 PI – Panicle Initiation; PM – Physiological Maturity; DAT – Days After Transplanting; BGL – Below Ground Level AWD – Alternate Wetting and Drying Code Description of Treatment 917 Int.J.Curr.Microbiol.App.Sci (2017) 6(2): 909-921 Fig.1 Regression of rice N uptake on SPAD readings Fig.2 Regression of nutrient uptake by rice on LCC rating 918