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Published in Agron. J. 96:1606-1621 (2004).
© American Society of Agronomy
677 S. Segoe Rd., Madison, WI 53711 USA

Nitrogen Management

Calibrating the Leaf Color Chart for Nitrogen Management in Different Genotypes of Rice and Wheat in a Systems Perspective

Arvind K. Shuklaa, Jagdish K. Ladhab,*, V. K. Singha, B. S. Dwivedia, Vethaiya Balasubramanianb, Raj K. Guptac, S. K. Sharmaa, Yogendra Singha, H. Pathakd, P. S. Pandeya, Agnes T. Padreb and R. L. Yadave

a Y. Singh, Project Directorate for Cropping Syst. Res. (PDCSR), Modipuram, Meerut-250110, India
b Int. Rice Res. Inst., DAPO Box 7777, Metro Manila, Philippines
c Rice–Wheat Consortium for IGP, CIMMYT-RWC, CG Block, NASC Complex, DPS Marg Pusa Campus, New Delhi-110012, India
d Indian Agric. Res. Inst., New Delhi, India
e Natl. Agric. Technol. Project, Krishi Anusandhan Bhawan-II, New Delhi 110012, India

* Corresponding author (J.K.Ladha{at}cgiar.org)

Received for publication October 22, 2003.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Low N use efficiency (NUE) continues to be a problem in the rice (Oryza sativa L.)–wheat (Triticum aestivum L.) cropping system. The leaf color chart (LCC)–based real-time N management can be used to optimize/synchronize N application with crop demand or to improve existing fixed split N recommendations. We conducted a field experiment during 2001–2003 at Modipuram, India, to determine the threshold LCC values for N application in rice and wheat, assess the need for basal N application, calibrate the LCC with a chlorophyll meter (SPAD), and work out the economics of rice–wheat systems. Treatments consisted of LCC scores of 2 to 5 for different cultivars of rice and wheat and were compared with the zero-N control and a recommended fixed-time N splitting. In rice, LCC ≤ 3 for ‘Basmati-370’, 4 for ‘Saket-4’, and 5 for ‘Hybrid 6111/PHB-71’ produced higher yield and NUE than recommended N splits. In wheat, maintenance of LCC ≤ 4 required 120 kg N ha–1, which produced higher grain yield, N uptake, and NUE than that of recommended N splits. Chlorophyll meter reading and crop growth rate (g m–2 day–1) at 15 d after transplanting in rice and 21 d after seeding in wheat were not significantly different with or without basal N application, indicating that basal N application in rice and wheat was not necessary in soils having relatively high indigenous N supply. Both LCC and SPAD readings (r = 0.84 to 0.91) were highly correlated in rice and wheat. Net returns were 19 to 31% higher in LCC-based N management than in fixed-time N application for rice–wheat cropping.

Abbreviations: AEN, agronomic efficiency of nitrogen • CRI, crown root initiation • DAS, days after sowing • DAT, days after transplanting • INS, indigenous nitrogen supply • LCC, leaf color chart • Na, leaf nitrogen content on leaf area basis • Ndw, leaf nitrogen content on dry weight basis • NR, net return(s) • NUE, nitrogen use efficiency • PI, panicle initiation • REN, recovery efficiency of nitrogen • SLW, specific leaf weight • SPAD, soil plant analysis development • TCC, total cost of cultivation


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
RICE AND WHEAT, the staple food crops for South Asian people, are of great significance, as these crops contribute more than 80% of the total cereal production in South Asia—Bangladesh, Pakistan, India, and Nepal (Timsina and Connor, 2001). Nitrogen is the nutrient that most often limits crop production. Cereals including rice and wheat accounted for approximately 56% of the worldwide N fertilizer utilized (IFA, 2002). Nitrogen use efficiency in rice and wheat is low. Based on a recent worldwide evaluation, the fertilizer N recovery efficiency has been found to be around 30% in rice and wheat with current practices (Krupnik et al., 2004). The main reason of low NUE is inefficient splitting of N applications, including the use of N in excess to the requirements. Fixed-time recommended N split applications at specified growth stages is the most common practice followed by the farmers (PhilRice, 1991; Pillai and Kundu, 1993).This does not consider the dynamic crop N requirement and soil N supply because N recommendations were mainly derived from empirical testing of N response to few fixed doses. In fixed-time recommended N split schedule, the N splitting is skewed, the first two splittings [one as basal at the time of planting/sowing and another at 25 to 30 d after transplanting (DAT) in rice and 21 to 25 d after sowing (DAS) in wheat] occur at 21 to 30 DAS/DAT, and third dose is split at panicle initiation (PI) stage. In some rice-growing countries, present recommendations call for 50 to 67% of total fertilizer N inputs to be broadcast-incorporated before transplanting and the remainder top dressed at 5 to 7 d before PI (Cassman et al., 1998). Farmers do not appear to recognize differences in soil N supply because no relationship exists between the amount of N fertilizer they apply and crop N uptake in plots established within their fields that did not receive applied N (Cassman et al., 1998).

The optimum use of N can be achieved by matching N supply with crop demand. A potential solution has been tried to regulate the timing of N application in rice and wheat using a chlorophyll meter (or SPAD meter) or a LCC to determine the plant N needs (Balasubramanian et al., 2003; Bijay-Singh et al., 2002). The concept is based on results that show a close link between leaf chlorophyll content and leaf N content. Moreover, leaf-area–based N concentration (Na) varies within a narrow range at different growth stages. The close relationship between Na and SPAD or LCC readings facilitates the use of a single critical value for SPAD or LCC to monitor leaf N status at all growth stages. Thus, the chlorophyll meter or LCC can be used to quickly and reliably assess the leaf N status of crops at different growth stages. The LCC, because of its low cost for farmers, has shown much promise in real-time N management studies conducted in India and elsewhere. But, these studies were restricted to coarse rice cultivars having similar genetic potential and harvest index (Balasubramanian et al., 1999, 2003; Bijay-Singh et al., 2002). In LCC-based N management, chart readings start at 15 DAT in rice and 21 DAS in wheat. An important issue is whether to use the basal N (at planting) when the LCC is used as an approach for managing N. In the rice–wheat cropping systems, genotypes of various background and growth duration are grown in a sequence (wheat after the harvest of rice in the same plot) to fit in a system. No information is available on critical LCC values for rice genotypes having different genetic background, plant type, and leaf color. It is also important to determine whether the LCC could be useful for applying N in wheat, particularly before the maximum tillering stage.

Therefore, this study was designed to examine these issues while considering a systems perspective. Our objectives were to (i) assess the need for basal N application in LCC-based N management in rice and wheat, (ii) establish the validity of LCC with chlorophyll meter readings and leaf N status of crop, (iii) determine threshold LCC values for different rice and wheat genotypes based on agronomic parameters [i.e., yield, agronomic efficiency of N (AEN) and recovery efficiency of N (REN)], and (iv) determine economic return of different rice–wheat genotype combinations, using LCC and fixed-N split methods for N management.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Experimental Site
A field experiment during two consecutive years (2001–2002 and 2002–2003) was conducted on a typic Ustrochrept (Sobhapur sandy loam) soil of the research farm of the Project Directorate for Cropping Systems Research, Modipuram, Meerut (29°4'N, 77°46'E; 237 m above mean sea level), in western Uttar Pradesh, representing Transect 3 (the Upper Gangetic Plains) of the Indo-Gangetic Plains Region. This is an intensively cultivated transect with 150% cropping intensity. The climate of Meerut is semiarid subtropical, with dry, hot summers and cold winters. The average annual rainfall is 810 mm, 75% of which is received during July–September. Mean maximum and minimum temperatures were 34.0 and 24.1°C during rice cropping (July to Oct.) and 26.9 and 10.1°C during the wheat (Nov. to Apr.) season. The soil of the experimental sites derived from Gangetic alluvium is well drained, slightly alkaline in reaction (pH 8.2), and sandy loam in texture (160 g clay kg–1, 190 g silt kg–1, and 630 g sand kg–1). The organic C, Olsen P and available K, and diphenyl triamine penta acetic acid (DTPA) extractable Zn were 5.4 g kg–1, 10.6 mg kg–1, 0.19 C mol kg–1, and 0.60 mg kg–1, respectively.

Experimental Design and Treatments
The experiment was laid out in a split-plot design with rice and wheat grown in sequence. In rice, three genotypes, Basmati-370 [traditional, tall, long fine grain, scented, long-duration (155–160 d), high-value crop], Saket-4 [inbred, coarse grain, short duration (115–120 d)], and Hybrid 6111/PHB-71 [improved, high yield potential, coarse grain, medium duration (135–140 d)], were grown in main plots with three replications. In wheat, cultivars PBW-343 (early sown), HD-2687 (timely sown), and PBW-226 (late sown) were grown in the same layout in the plots vacated from Saket-4, the hybrid, and Basmati-370, respectively. The five fertilizer N (as urea) management treatments assigned to subplots are described in Tables 1 and 2. In rice, the LCC scores of ≤ 2, 3, and 4 for Basmati-370 and ≤ 3, 4, and 5 for Saket-4 and Hybrid 6111/PHB-71 were compared with fixed-time recommended N rates (80, 120, and 150 kg N ha–1 for Basmati-370, Saket-4, and Hybrid 6111/PHB-71, respectively). In wheat, LCC scores of ≤ 3, 4, and 5 were evaluated as critical values for all three cultivars and compared with locally recommended N splits (120 kg N ha–1). In the recommended N rate treatment, N was applied in three equal splits at transplanting (basal), midtillering, and PI in rice and at sowing (basal), crown root initiation stage (CRI), and PI in wheat. Both rice and wheat received P and K at the uniform rate of 26 and 33 kg ha–1 through single superphosphate and muriate of potash, respectively. In addition, 5 kg Zn ha–1 was also applied uniformly as zinc sulfate to each rice crop.


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  		Table 1. Treatments used in rice under rice–wheat system during 2001–2002 and 2002–2003 at Modipuram, Meerut, India.

 

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  		Table 2. Treatments used in wheat under rice–wheat system during 2001–2002 and 2002–2003 at Modipuram, Meerut, India.

 
Crop Management
The land was prepared by two crisscross plowings and two harrowings. Land was leveled and puddled for rice transplanting on 7 July 2001. Thereafter, 25-d-old seedlings were transplanted at 20- by 15-cm spacing in 8- by 6-m subplots on 8 July 2001. After harvest on 14 Oct. (Saket-4), 30 Oct. (Hybrid-6111), and 21 Nov. 2001 (Basmati-370), the individual plots were prepared after irrigation for wheat sowing. The wheat cultivars PBW-343 (early sown), HD-2687 (timely sown), and PBW-226 (late sown) were sown in rows 20 cm apart in the same layout using 100 kg seed ha–1 on 8 Nov., 26 Nov., and 13 December 2001 in plots vacated from Saket-4, Hybrid-6111, and Basmati-370, respectively. These wheat cultivars were harvested on 10, 16, and 20 Apr. 2002, respectively. Similarly, during the second year (2002–2003), rice genotypes Saket-4, Hybrid-PHB-71, and Basmati-370 were transplanted on 10 July and harvested on 15 Oct., 2 Nov., and 24 Nov. 2002, respectively. Wheat cultivars PBW-343, HD-2687, and PBW-226 were sown on 2 Nov., 22 Nov., and 16 Dec. 2002 and harvested on 8, 11, and 15 Apr. 2003, respectively.

Both crops were grown under assured irrigation. For rice cultivation, plots were kept continuously flooded 2 wk after transplanting. In addition to rainfall, a total of 9, 9, and 11 irrigations during 2001 and 14, 15, and 16 irrigations during 2002 were given to rice genotypes Saket-4, Hybrid-6111/PHB-71, and Basmati-370, respectively. At each irrigation, 3 to 5 cm of water was applied, and the interval between two irrigations depended on the disappearance of water. In wheat, the number of irrigations depended on time of sowing (cultivar duration) and rainfall events during the growing season. In 2001–2002, early sown wheat cultivar PBW-343 received four irrigations at 21, 42, 66, and 112 DAS; timely sown HD-2687 received irrigations at 21, 42, 66, and 101 DAS; and late-sown PBW-226 received only three irrigations at 21, 42, and 81 DAS. In 2002–2003, the early sown wheat (PBW-343) received five irrigations at 21, 42, 64, 85, and 111 DAS, and four irrigations were applied to both timely sown HD-2687 at 21, 43, 64, and 101 DAS and late-sown PBW-226 at 21, 40, 76, and 92 DAS. Standard practices were followed for insect pest and disease control. At maturity, rice and wheat were harvested manually at ground level, and grain and straw yields of both rice and wheat were determined from an area of 27 m2 located in the center of each plot. The grains were threshed using a plot thresher, dried in a batch grain dryer, and weighed. Grain moisture was determined immediately after weighing, and subsamples were dried at 70°C for 48 h. Grain yield of rice and wheat were reported at 140 and 120 g kg–1 moisture content, respectively. Straw weights were expressed on an oven dry weight basis.

Leaf Color Chart and Chlorophyll Meter Measurement
The LCC jointly developed by the International Rice Research Institute (IRRI) and Philippine Rice Research Institute (PhilRice), consisting of six green shades from yellowish green to dark green, was used in this study. In rice, 15 hills were selected at random in each plot. From each hill, three readings were taken from the uppermost fully expanded leaf. In wheat, 10 disease-free plants were chosen in each plot, and the color of the youngest fully expanded leaf was measured. The SPAD reading of the same leaf used for LCC measurement was also taken simultaneously for calibration of the LCC. In rice, both LCC and SPAD readings were taken at 10-d intervals, starting from 15 DAT till 50% flowering. In wheat, the LCC and SPAD meter readings started at the CRI stage (21 DAS) and ended at 50% flowering. In addition, the LCC score and chlorophyll meter reading were also taken at PI. Whenever the LCC reading was equal to or below the set critical value, fertilizer N was applied at 20 kg N ha–1 for Basmati-370 and 30 kg N ha–1 each for Saket-4 and Hybrid-6111/PHB-71 in 2001–2002. Since LCC ≤ 5 could not be attained in Year 1, 45 kg N ha–1 was applied to Saket-4 and Hybrid-PHB-71 during the rapid growth period (29 to 49 DAT) in Year 2. In wheat, 30 kg N ha–1 was applied in LCC ≤ 3 and 4 and 40 kg N ha–1 in LCC ≤ 5 treatments. No basal N was applied in the LCC-based treatments on rice or wheat.

Potential Yield Simulation
Potential yields, i.e., maximum yield of a variety restricted only by the season-specific climatic conditions, of rice and wheat grown during the experiment were estimated using CERES-RICE 3.5 (98.0) (Singh et al., 1998) and CERES-WHEAT 3.5 (98.0) (Ritchie et al., 1998) models, respectively. The genetic coefficients for the cultivars in this study were estimated from the first year of the field observations by repeated iterations until close matches were observed between simulated and observed phenology and yield. The performance of the models has been well validated in the rice–wheat growing environments of India (Timsina et al., 1998; Pathak et al., 2003). The daily weather data (solar radiation, maximum temperature, and minimum temperature) required for simulation were collected from the meteorological observatory located at Modipuram.

Plant Sampling Measurements and Analysis
Leaf samples of 1-m row length were collected for the measurement of leaf area, dry weight, and N content at PI and flowering stages. Leaf area was measured by leaf area meter (LI-3100, LI-COR, Lincoln, NE). The crop growth rate was determined by harvesting the plant aboveground biomass from 1-m row length area at 7, 11, 15, and 20 DAT of rice and 8, 11, 15, 21, and 31 DAS of wheat following the method of Leopold and Kriedemann (1975). Dry weight was determined after oven drying at 70°C to constant weight. Grain and straw samples of rice and wheat collected from each plot were dried at 70°C in a hot-air oven. The dried samples were ground in a stainless steel Wiley Mill, and N content in leaf, grain, and straw was determined by digesting the samples in sulfuric acid (H2SO4) followed by analysis of total N by the Kjeldahl method (Bremner and Mulvaney, 1982) using a Kjeltec autoanalyzer.

Economic Analysis
The total cost of cultivation (TCC) of rice and wheat was calculated on the basis of different operations performed and materials used for raising the crops, including the cost of fertilizer N. The cost of labor for recording LCC readings was calculated on actual basis. For each recording date, 2 person days ha–1 were required, and depending on crop duration, LCC readings were recorded 5 to 7 times in rice and 7 to 10 times in wheat. One person day ha–1 was required for supplying the extra N split. Thus, on average, 26 to 32 person days were engaged in various LCC treatments. The cost of additional fertilizer, if any, was also added to the TCC. The prices of important materials used and operations performed were rice seed, US$0.76, US$0.23, and US$3.26 kg–1 for Basmati-370, Saket-4, and Hybrid-6111/PHB-71, respectively; wheat seed, US$0.45 kg–1; N, US$0.23 kg–1; irrigation, US$4.13 irrigation–1 ha–1; labor, US$1.57 person days–1 d–1; plowing/harrowing, US$2.61 ha–1 operation–1; puddling, US$9.35 ha–1 operation–1. The current exchange rate is US$1 = Rs46.

Gross returns (GR) were calculated by multiplying grain yield by grain price: US$0.24 kg–1 for Basmati-370, US$0.12 kg–1 for both Saket-4 and Hybrid-6111/PHB-71, and US$0.14 kg–1 for wheat. Net returns (NR) were calculated as

[1]

The NR of rice genotypes Basmati-370, Saket-4, and Hybrid-6111/PHB-71 were added to the NR of wheat cultivars PBW-226, PBW-343, and HD-2687, respectively, to calculate the system net return (SNR) as

[2]
where NRr is the net return from rice and NRw is the net return from wheat.

The NR of the rice–wheat system was calculated for the LCC-based N management at agronomically determined optimum threshold values and compared with the fixed split recommended N application.

Data Analysis
The statistical analysis of data consisted of analysis of variance for yield parameters of rice and wheat to determine the effects of rice genotypes/wheat cultivars, N treatments, and their interactions using IRRISTAT Version 1992 (IRRI, 1992). Duncan's multiple range test (DMRT) was used at the <0.05 level of probability to test differences between treatment means. The relationship of LCC score to SPAD readings was determined for different rice and wheat genotypes by regression analysis using the data at different growth stages and data pooled across growth stages, N management options, and years. To test the significance of LCC and SPAD regression equation, the confidence limit (95%) was calculated as given by Draper and Smith (1986). Correlations between LCC scores and SPAD readings were determined by correlation analysis.

Calculations
Nitrogen Use Efficiency
Agronomic efficiency of added N (AEN) was calculated (Cassman et al., 1998):

[3]

Recovery efficiency of added N (REN) was calculated (Cassman et al., 1998):

[4]


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Assessing Need for Basal Nitrogen Application in Rice and Wheat
In 2001, total N applied with LCC ≤ 3 in Basmati-370 and ≤ 4 for Saket-4 and Hybrid 6111 was the same as in fixed-schedule recommended N treatment (Table 1). But grain yield, AEN, and REN were higher for LCC-based N treatments than for fixed-schedule N application (Table 3). The threshold LCC values that optimized the yield, AEN, and REN were LCC ≤ 3 for Basmati-370 and LCC ≤ 4 for Saket-4 and Hybrid 6111 during 2001.


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  		Table 3. Grain yield, total N uptake, and N use efficiencies [agronomic efficiency of nitrogen (AEN) and recovery efficiency of nitrogen (REN)] of three rice genotypes grown during 2001 with different N management treatments at Modipuram, India.

 
In 2002, the threshold value of LCC ≤ 3 with an application 80 kg N ha–1 optimized the yield, AEN, and REN for Basmati-370; the threshold value of LCC ≤ 4 for Saket-4 required 135 kg N ha–1 to optimize yield, AEN, and REN; similarly, the threshold value of LCC ≤ 5 required 165 kg N ha–1 for Hybrid PHB71 to optimize yield, AEN, and REN (Table 4). This means that Saket-4 and hybrid PHB71 required 15 kg ha–1 more N for LCC-based N management than for fixed-schedule N application during 2002. In wheat also, the LCC ≤ 4 treatment (120 kg N ha–1without basal) produced a higher grain yield and greater AEN and REN than recommended N splits (Tables 5 and 6). These results indicate that N applied starting at 14 DAT in rice and at 21 DAS in wheat based on crop need as determined by the LCC was used more efficiently to optimize both grain yield and NUE. Results of this study and published elsewhere (Ladha et al., 2000) showed that the current recommendation of fixed-time split N applications at specified growth stages is not adequate to synchronize N supply with actual crop N demand because of poorly designed N splitting and variations in crop N demand and indigenous N supply (INS). Although basal N application (applied just before or at planting) is recommended, its need has not been based on the early-season INS. The INS is defined as plant N accumulation in grain and straw at physiological maturity in zero-N plots, which represents all sources of N (soil, organic materials, crop residues, rhizosphere N fixation, irrigation water, rainfall, etc.) available to crops during the growing season (Dobermann et al., 2003). The INS capacity varies with cropping season, soil, and crop (Dobermann et al., 2002; Adhikari et al., 1999; Stalin et al., 1996). The INS capacity in the present study (calculated from N omission plots) was 60 ± 3.2, 54 ± 2.2, and 61 ± 2.6 kg N ha–1 for Basmati-370, Saket-4, and Hybrid 6111/PHB-71 and 44.3 ± 1.8, 45 ± 2.5, and 35 ± 1.5 kg ha–1 for wheat cultivars PBW-343, HD-2687, and PBW-226, respectively. The low INS in wheat could be due to less residual N left after rice harvest and low biological activity in the winter season when wheat is grown. Since the leaf chlorophyll content is closely related to leaf N concentration, SPAD meter readings during the early stage of crop growth should reflect the INS status. The chlorophyll meter readings taken at 15 DAT in rice and at 21 DAS in wheat in the LCC ≤ 4 treatment (no basal N application), fixed-time recommended N split (40 kg N ha–1 basal), and zero-N control plot did not show a significant difference (Fig. 1). The crop growth rate up to 15 DAT in rice and up to 21 DAS in wheat also did not exhibit a difference between treatments, i.e., with and without basal N application (Fig. 2). This indicated that basal N application had no effect on early crop growth and N absorption by plants and that INS levels of 50 to 60 kg ha–1 for rice and 35 to 45 kg ha–1 for wheat were adequate to meet the plant's need of N at early stages in these soils. The contribution of N acquired during early vegetative growth to grain and total biomass production at maturity is considerably less important than the contribution of N uptake after midtillering when crop demand is greatest and reproductive growth begins (Cassman et al., 1996; Peng et al., 1995a). Further, the LCC- and SPAD-based N management experiments conducted by Bijay-Singh et al. (2002) with 20 kg N ha–1 as basal and without basal N application showed no difference in grain yield. Rice seedlings need about 7 to 8 d to recover from transplanting shock (Meelu and Gupta, 1980), and thus, N uptake within 2 wk of transplanting is very small (Peng and Cassman, 1998). Likewise, in wheat, N uptake at 21 DAS remained very small (3 to 5 kg ha–1). We also found that wheat N uptake at 21 DAS in treatments with and without basal N did not differ (data not shown), suggesting that N uptake up to 21 DAS was very low and N demand could be met from the seed (100 kg ha–1 wheat seed supply 1.6 kg N ha–1) and INS. In both 2001 and 2002, the rice grain yields in zero-N control plots were >3 Mg ha–1 in Saket-4 and Hybrid 6111/PHB-71 and >2.5 Mg ha–1 in Basmati–370 (Tables 3 and 4), indicating adequate native N supply from soil. This supports the suggestion of Balasubramanian et al. (1999) that for high-yielding rice varieties, soils producing a grain yield of >3 Mg ha–1 without any fertilizer application may not need basal N application. Dobermann et al. (2003) found that about 50% of rice soils in their studies had INS > 53 kg ha–1 and required no basal N application while only 25% of the soils had INS < 41 and responded to basal N application. These results strongly indicate that fertilizer NUE could be increased by using the LCC- or SPAD-based N management strategy without any basal N application at planting for both rice and wheat crops provided that INS is sufficiently high (50–60 kg N ha–1 for rice and 35–45 kg N ha–1 for wheat).


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  		Table 4. Grain yield, total N uptake, and N use efficiencies [agronomic efficiency of nitrogen (AEN) and recovery efficiency of nitrogen (REN)] of three rice genotypes grown during 2002 with different N management treatments at Modipuram, India.

 

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  		Table 5. Wheat grain yields, total N uptake, and N use efficiencies [agronomic efficiency of nitrogen (AEN) and recovery efficiency of nitrogen (REN)] of three wheat cultivars grown during 2001–2002 using different fertilizer N management criteria at Modipuram, India.

 

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  		Table 6. Wheat grain yields, total N uptake, and N use efficiencies [agronomic efficiency of nitrogen (AEN) and recovery efficiency of nitrogen (REN)] of three wheat cultivars grown during 2002–2003 using different fertilizer N management criteria at Modipuram, India.

 


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  		Fig. 1. Chlorophyll meter reading as influenced by N management—zero-N control, leaf color chart (LCC)-based (no basal N), and fixed-time recommended N split (28, 40, and 50 kg N ha–1 in Basmati-370, Saket, and hybrid rice, respectively, and 40 kg N ha–1 in each cultivar of wheat) in rice and wheat. Vertical bar indicates the mean standard error (in rice, n = 15; in wheat, n = 30).

 


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  		Fig. 2. Initial crop growth rate (CGR, g m–2 day–1) of rice and wheat as influenced by N management—zero-N control, leaf color chart (LCC)-based (no basal N), and fixed-time recommended N split (28, 40, and 50 kg N ha–1 in Basmati-370, Saket, and hybrid rice, respectively, and 40 kg N ha–1 in each cultivar of wheat). Vertical bar indicates the mean standard error (n = 6).

 
Since the issue of basal N application has an important bearing on overall N management in the rice–wheat system, further on-farm studies need to be conducted for a long enough period to determine the minimum yield level in zero-N plots above which no basal N is required.

Calibration of Leaf Color Chart with SPAD Value and Leaf Nitrogen Content
The LCC and SPAD readings of all the genotypes had a strong positive correlation (r = 0.84 to 0.91) in both rice and wheat. The regression analysis showed a significant linear relationship between LCC and SPAD value at all growth stages for all cultivars of rice and wheat (Fig. 3 and 4). But the coefficients of determination, slopes, and intercepts varied among the growth stages within the genotype and between the genotypes. In rice, the coefficients of determination at different growth stages varied from 0.68 to 0.87, 0.65 to 0.85, and 0.71 to 0.82 for Basmati-370, Saket-4, and Hybrid 6111, respectively (Fig. 3). Similarly in wheat, the coefficients of determination varied from 0.61 to 0.89 at different growth stages among the three cultivars (Fig. 4). In general, the LCC score and SPAD values increased with increasing the crop age and LCC threshold value from 3 to 5, but no definite trend was noticed in coefficients of determination among the growth stages and N management options. When data were pooled across the cultivars and growth stages, treatments had no significant effect on the relationship between SPAD and LCC score. When data were pooled across N management options, the difference in slopes and intercept disappeared. When data were pooled across growth stages and N management options, rice cultivars Saket-4 and Hybrid 6111/PHB 71 exhibited similar slopes and intercepts while coefficients of determination were comparable in Basmati-370 and Hybrid 6111/PHB 71 (Fig. 5). In wheat, slope intercept and coefficients in PBW-343 were as good as in HD-2687. However, cultivar PBW-226 had different slope and intercept and coefficient than PBW-343 and HD-2687. The regression equations between LCC scores and SPAD readings for rice and wheat genotypes, combining data across growth stages, N management options, and year, are found in Table 7.



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  		Fig. 3. Relationship between leaf color chart (LCC) score and chlorophyll meter reading starting from 15 d after transplanting till 50% flowering (45–65 d after transplanting) at 10-d interval in rice cultivars across N management options in 2001 and 2002.

 


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  		Fig. 4. Relationship between leaf color chart (LCC) score and chlorophyll meter reading from 21 (crown root initiation) to 81 to 91 (50% flowering) d after sowing at 10-d interval in wheat cultivars across N management options in 2001–2002 and 2002–2003.

 


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  		Fig. 5. Relationship between leaf color chart (LCC) score and chlorophyll meter reading (SPAD) for rice and wheat cultivars across N management options and growth stages in 2001–2002 and 2002–2003.

 

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  		Table 7. Regression equations between leaf color chart (LCC) scores and SPAD readings for rice and wheat genotypes.

 
In rice, Basmati-370 and hybrid genotypes had similar coefficients of determination, but the intercepts and slopes were different. However, Saket-4 and the hybrid rice were comparable in slope, with different intercept and coefficients, and Saket-4 and Basmati-370 were alike in intercept with different slopes and coefficients. For wheat, coefficients, intercepts, and slopes were similar for all cultivar–planting date combinations. On the basis of grain yield, N uptake, and NUE, LCC ≤ 3 was appropriate for Basmati-370, LCC ≤ 4 for Saket-4, LCC ≤ 5 for Hybrid 6111/PHB-71, and LCC ≤ 4 for all three cultivars of wheat. The corresponding SPAD values for different varieties/LCC were Basmati-370 (LCC ≤ 3), 33; Saket-4 (LCC ≤ 4), 44; and Hybrid 6111/PHB-71 (LCC ≤ 5), 47. The relationship between SPAD value and LCC score for rice cultivar IR72 reported by Yang et al. (2003) was SPAD = 11.67 + 7.25LCC, where LCC 3, 4, and 5 corresponded to SPAD values of 33, 41, and 48, respectively, which are nearly similar to those of our study except for Saket-4, which exhibited higher value of SPAD at a specified LCC score. We speculate the greater leaf thickness/specific leaf weight (SLW) of Saket-4 could be the reason for getting higher SPAD value in Saket-4. In wheat, LCC 4 corresponded to a SPAD value of 41.3, 41.7, and 40 for PBW-343, HD-2687, PBW-226, respectively. A study conducted by Follett et al. (1992) to estimate leaf N content and determine the need for additional fertilizer N in dryland winter wheat revealed that grain yield responded with a meter reading of less than about 42. Another study conducted by Bijay-Singh et al. (2002) at Ludhiana, India, indicated that wheat responded to N application at maximum tillering when SPAD values were ≤42. Thus, these results inferred that the LCC could replace the SPAD meter for real-time N management in rice and wheat.

To establish the validity of LCC for assessing leaf N content, the SPAD value, leaf N content on dry weight (Ndw), SLW, and Na recorded at PI and flowering stages had significant responses to N management options and rice genotypes/wheat cultivars in both 2001 and 2002 (Tables 8 to 11). In rice, LCC score, SPAD, Ndw, and Na increased with increasing the N application rates as per LCC threshold value from 3 to 5, but SLW decreased as the N application increased at both PI and flowering stages (Table 8). Similar findings were reported by Yang et al. (2003) while estimating leaf N content using LCC in the Philippines. However, the values reported for Na were greater in this study for Saket-4 and hybrid rice than those reported by Yang et al. (2003). This could be attributed to higher values of SLW and Ndw recorded for these genotypes in the present study than that of ‘IR72’, ‘PSBRc52’, and ‘IR65620’ used by Yang et al. (2003). Within a growth stage, the SPAD reading, SLW, Ndw, and Na were comparable for Saket-4 and hybrid rice. However, these parameters were significantly different than those of Basmati-370 rice (Table 9). Growth stages had no significant effect on the relationship between Na and LCC score. When leaf N concentration was measured on leaf area basis (Na), there was a similar linear correlation between SPAD values and Na for all stages of development and lines tested (Peng et al., 1995b, 1996). Moreover, the direct relationship of LCC score with Na and SPAD across growth stages provides confidence that one value can be used as the critical LCC color for the timing of N topdressing with a given cultivar (Yang et al., 2003). The estimated Na across growth stages and cropping years at LCC scores 3, 4, and 5 in Basmati-370, Saket-4, and Hybrid 6111/PHB-71 rice were 1.26, 1.89, and 2.36 g m,–2 respectively. Except for Basmati-370, these values are higher than the 1.4 g m–2 at SPAD = 35 for IR72 as reported by Peng et al. (1996). The differences in leaf thickness are largely responsible for variations in the relationship between Ndw and SPAD values in rice (Peng et al., 1993). Since Na is equal to the product of Ndw and SLW, the greater leaf thickness in Saket-4 and hybrid rice as evidenced by higher SLW resulted in greater value of Na compared with Basmati-370.


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  		Table 8. Mean values of leaf color chart (LCC) score, chlorophyll meter (SPAD) reading, leaf N concentration per unit dry weight (Ndw), specific leaf weight (SLW), and leaf N content per unit leaf area (Na) of rice at panicle initiation (PI) and flowering (FL) in different N management across three genotypes during 2001 and 2002.

 

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  		Table 11. Mean values of leaf color chart (LCC) score, chlorophyll meter (SPAD) reading, leaf N concentration per unit dry weight (Ndw), specific leaf weight (SLW), and leaf N content per unit leaf area (Na) of wheat cultivars PBW 343, HD 2687, and PBW 226 at panicle initiation (PI) and flowering (FL) across N management options during 2001–2002 and 2002–2003.

 

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  		Table 9. Mean values of leaf color chart (LCC) score, chlorophyll meter (SPAD) reading, leaf N concentration per unit dry weight (Ndw), specific leaf weight (SLW), and leaf N content per unit leaf area (Na) of rice genotypes Basmati-370, Saket 4, and Hybrid 6111/PHB-71 at panicle initiation (PI) and flowering (FL) across N management options during 2001 and 2002.

 

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  		Table 10. Mean values of leaf color chart (LCC) score, chlorophyll meter (SPAD) reading, leaf N concentration per unit dry weight (Ndw), specific leaf weight (SLW), and leaf N content per unit leaf area (Na) of wheat at panicle initiation (PI) and flowering (FL) in different N management options across three cultivars during 2001–2002 and 2002–2003.

 
In wheat, the LCC score, SPAD, Ndw, SLW, and Na increased with increasing LCC threshold values for N application (Table 10). However, at the same LCC score, the SPAD, Ndw, and Na values were higher than those of rice. Within a growth stage, the LCC score, SPAD, Ndw, SLW, and Na were similar for cultivars PBW-343 (early sown) and HD-2687 (timely sown); however, these values were significantly higher than those of late-sown wheat cultivar PBW-226 (Table 11). It appears that the vegetative phase in late-sown wheat was abridged as the increase in minimum and maximum temperature hastened the early flowering. The relationship between LCC score and Na was similar for PBW-343 (early sown) and HD-2687 (timely sown) cultivars. However, late-sown wheat (PBW-226) had different slope, intercept, and regression coefficient during both years. The values of Na at LCC 4 were 2.08, 2.21, and 1.86 g m–2 for cultivars PBW-343, HD-2687, and PBW-226, respectively. Since the LCC values are closely related to SPAD and Na, LCC can be used directly for diagnosing leaf N status and determining the timing of N topdressing for real-time N management in rice and wheat.

Determination of Threshold Leaf Color Chart Value for Rice and Wheat Genotypes Based on Agronomic Parameters
Improving the synchronization between crop N demand and the available N supply is an important key to improve NUE. Crop N requirements are closely related to yield levels, which in turn are sensitive to climate, particularly solar radiation and the supply of nutrients and crop management practices. A fertilizer N management strategy must therefore be responsive to variations in crop N requirements and soil N supply. The LCC strategy, which has been calibrated with SPAD, is a simple and efficient way of managing N in real time. However, this requires the determination of critical LCC values for a group of varieties exhibiting similar plant type and growth duration (e.g., traditional long duration, semidwarf short duration, hybrid, etc.). Once the critical values for different varietal groups are determined, they are valid for similar groups of varieties grown elsewhere in the tropics. Areas with distinct differences in radiation between dry and wet seasons (e.g., Central Luzon, Philippines) may require different LCC critical values for dry and wet seasons to optimize N use in rice.

Critical or threshold LCC values are defined as those that optimize simultaneously the grain yield and NUE (AEN and REN). Based on published data (Dobermann et al., 2004) and experience, AEN and REN exceeding 20 and 50, respectively, with consistent high grain yield are regarded as efficient for rice germplasm. Likewise, AEN of 20 and REN of 50 for late-sown wheat and AEN of 25 and REN of 60 for early and timely sown wheat with high grain yields are regarded as efficient. Using these agronomic parameters, the following LCC values were judged to be critical values: LCC ≤ 3 for Basmati-370, LCC ≤ 4 for Saket-4, and LCC ≤ 5 for Hybrid PHB-71 for rice (Table 3 and 4) and LCC ≤ 4 for all wheat cultivars (Tables 5 and 6).

Potential Yield
The actual yields of both rice and wheat were remarkably similar between 2 yr (Tables 3 to 6). Excellent soil, crop, and water management followed during the experiment must have contributed to this consistency of the data. In addition, the analysis of weather parameters showed that the differences between 2 yr were not large (except rainfall). On an average, differences at critical growth stages (tillering, PI, and flowering) between 2 yr in average minimum temperatures were 0.7°C in rice and 0.3°C in wheat, and in solar radiation, differences were 33.3 MJ m–2 in rice and 37.8 MJ m–2 in wheat (Table 12). Maximum temperature during maximum tillering in rice was lower in 2001 than that of 2002, but at PI and flowering stages, it was reversed, thereby compensating for the differences. Rainfall had a large variation in different growth stages, but this is of no significance because the experiments were conducted under fully irrigated condition. Relatively smaller differences in weather parameters were further reflected in model-simulated climatic potential yields of rice and wheat. The potential yields of rice and wheat varieties were 6.4, 10.2, and 11.6 Mg ha–1 in Basmati-370, Saket-4, and Hybrid 6111 during 2001 and 6.5, 9.9, and 11.7 Mg ha–1 in 2002, respectively. In wheat, the potential yields for PBW-343, HD-2687, and PBW-226 were 6.4, 7.5, and 4.9 Mg ha–1 and 6.2, 8.3, and 5.2 Mg ha–1 during 2001–2002 and 2002–2003, respectively.


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  		Table 12. Weather parameters in various critical growth stages of rice and wheat.{dagger}

 
Economic Analysis
The economics of rice–wheat system depends on two parameters, namely the relative yield of rice and wheat as determined by N treatments and wheat yield as determined by the time of planting of wheat. The rice–wheat combinations that provide optimum planting dates for wheat will maximize yield and profit. The TCC for rice–wheat system varied from US$569.3 to US$678.7 and US$576.8 to US$692.0 during 2001–2002 and 2002–2003, respectively. Of the total system cost, rice and wheat crop shared 48 and 52%, respectively. Among the rice cultivar, Hybrid 6111 has highest cost of cultivation (US$306) followed by Saket-4 (US$292) and then Basmati-370 (US$285). The input costs for growing wheat varied from US$274 to US$342, depending on cultivar and planting dates. Compared with fixed-time split N application, LCC-based N management required US$25.3 to US$58.4 extra investments in different LCC treatments.

System's net return varied from US$702 to US$851 in first year and US$735 to US$886 in second year (Fig. 6). Among the three-genotype combinations of rice and wheat evaluated in the rice–wheat cropping system, the NR from Basmati-370–late-sown wheat (PBW-226) and hybrid 6111/PHB-71–timely sown wheat (HD-2687) combinations were comparable in both 2001–2002 and 2002–2003. Saket-4–early sown (PBW-343) combination gave the lowest NR (i.e., US$702 and US$735, respectively) in both years.



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  		Fig. 6. Total net return ($ ha–1) from different genotype combinations in rice–wheat system as influenced by leaf color chart (LCC)-based N management. LSD (P < 0.05) for system (S) = 20.6 and 16.7, N management (N) = 26.6 and 36.7, and S x N = 52.7 and 43.5. T1 = LCC 3, 4, and 5 for Basmati-370, Saket 4, and Hybrid 6111/PHB-71 rice, respectively, and LCC 4 for wheat; T2 = N applied as per fixed-time recommended split in rice and wheat.

 
It is important to note that in both economically superior rice–wheat combinations, the profit was dictated by rice. In the Basmati-370–late-sown wheat combination, higher returns were due to the premium value of Basmati-370 rice, whereas in hybrid rice–timely sown wheat, the high yield of hybrid gave higher profit. However, farmers preferred the Basmati-370–late-sown wheat combination because of the greater market demand for Basmati-370 rice. In the Basmati-370–late-sown wheat combination, the NR was highest when 80 kg N ha–1 (as per LCC ≤ 3) in rice and 120 kg N ha–1 (as per LCC ≤ 4) in wheat were applied in both 2001–2002 and 2002–2003. Compared with the recommended N splits, in which a similar quantity of fertilizer N was applied, the LCC treatment combinations (LCC ≤ 3 in Basmati-370 and LCC ≤ 4 in wheat) gave 20 and 23% higher NR in 2001–2002 and 2002–2003, respectively. In Saket-4–early sown wheat (PBW-343) combination, the fertilizer N application based on LCC ≤ 4 in rice and wheat was more profitable than any other treatment combination. In hybrid rice–timely sown wheat (HD-2687) combination, the N application based on LCC ≤ 5 in rice and 4 in wheat gave extra NR of 28 and 31% in 2001–2002 and 2002–2003, respectively, over recommended N splits. Thus, on the basis of system's net return, the threshold LCC ≤ 4 for both rice and wheat was suitable for Saket-4-early sown wheat (PBW-343) and LCC ≤ 5 and 4 for Hybrid 6111/PHB-71 rice-timely sown wheat (HD-2687) combinations. However, in Basmati-370–late-sown wheat (PBW-226) combination, the threshold value, i.e., LCC ≤ 3 in Basmati-370 and LCC ≤ 4 in wheat, proved superior over any other LCC combination.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
The simultaneous optimization of grain yield and N use in rice and wheat crops is possible by matching N supply with crop N demand. In many field situations, more than 60% of applied N is lost due in part to the lack of synchrony of plant N demand with N supply. Results presented in a 2-yr rice–wheat system study provide evidence that current fertilizer N recommendations (fixed-time split N) are not adequate for maintaining the high yields and efficient use of N in rice and wheat. The LCC-based N management assures high yields consistent with efficient N use in both rice and wheat and enhances rice–wheat systems' total productivity and farmer's profit. The LCC is a simple and easy-to-use tool that can help farmers manage N judiciously.

Future studies can compare the efficiency, labor use, cost, and profit of improved fixed-time spilt N strategies derived from this and other studies and the LCC-based real-time N management in rice and wheat. Improved fixed-time split N recommendations will work well for homogenous domains, but real-time N management will still be needed to tackle high spatial and temporal variability in INS and to refine fixed-time split N recommendations periodically (once every 4–5 yr).


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 




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