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NITROGEN MANAGEMENT

Using Leaf Color Charts to Estimate Leaf Nitrogen Status of Rice

^a Rice Cultivation Res. Div., Natl. Crop Exp. Stn., Rural Dev. Administration, 209 Seodundong, Suwon 441-100, Republic of Korea
^b Crop, Soil, and Water Sci. Div., Int. Rice Res. Inst. (IRRI), DAPO Box 7777, Metro Manila, Philippines

* Corresponding author (s.peng{at}cgiar.org)

Received for publication April 4, 2002.

	ABSTRACT

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Leaf color charts (LCCs) have substituted for chlorophyll meter (SPAD) to estimate leaf N status of rice (Oryza sativa L.) and to properly time N fertilizer application. The objectives of this study were to (i) compare three different types of LCC in estimating leaf N status, (ii) determine if specific leaf weight (SLW) affects the estimation of dry weight–based N concentration (N_dw) by LCC, and (iii) determine the relationship between LCC scores and SPAD values. Two field experiments were conducted in the Philippines with different N rates and cultivars grown during 2000 wet season and 2001 dry season. The LCC score and SPAD reading were taken on uppermost fully expanded leaves at three growth stages, and SLW was calculated as the ratio of dry weight to leaf area. Nitrogen content was determined by micro-Kjeldahl procedure and expressed as N_dw and leaf area–based N content (N_a). There was a linear relationship between LCC scores and N_dw at each growth stage (R² range of 0.25–0.97) and across growth stages (R² range of 0.46–0.62). Adjusting LCC scores for SLW (LCC/SLW) greatly improved the prediction of N_dw across growth stages (R² range of 0.84–0.92), suggesting that leaf thickness affects LCC scores. Leaf color chart estimated N_a better than N_dw across growth stages. Leaf color chart scores were closely related to SPAD values (R² range of 0.62–0.98). Strong correlations existed among the scores of the three types of LCC (r range of 0.93–0.99). They are all suitable for use by rice farmers in timing N topdressing.

Abbreviations: DS, dry season • FL, flowering • IRRI, International Rice Research Institute • LCC, leaf color chart • MT, midtillering • N_a, leaf area–based nitrogen content • N_dw, dry weight–based nitrogen concentration • PI, panicle initiation • SLW, specific leaf weight • SPAD, chlorophyll meter • UCD, University of California, Davis • WS, wet season • ZAU, Zhejiang Agricultural University

	INTRODUCTION

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MONITORING OF PLANT N STATUS is important in improving the balance between crop N demand and N supply from soil and applied fertilizer (Shiga et al., 1977; Cassman et al., 1994). Because leaf N content is closely related to photosynthetic rate (Peng et al., 1995a) and biomass production (Kropff et al., 1993), it is a sensitive indicator of the dynamic changes in crop N demand within a growing season. The direct measurement of leaf N concentration by laboratory procedures is laborious, time consuming, and costly. Such procedures have limited use as a diagnostic tool for optimizing N topdressing because of the extensive time delay between sampling and obtaining results.

The chlorophyll meter (SPAD) provides a simple, quick, and nondestructive method for estimating leaf chlorophyll content (Watanabe et al., 1980). The ability to predict chlorophyll content on a leaf area basis from SPAD readings was demonstrated in several crops (Jiang and Vergara, 1986; Takebe and Yoneyama, 1989; Dwyer et al., 1991). Because chlorophyll content in a leaf is closely correlated with leaf N concentration (Evans, 1983; Blackmer and Schepers, 1994), the measurement of chlorophyll provides an indirect assessment of leaf N status.

The SPAD also estimated N_dw of rice leaves with the goal of predicting the need for fertilizer N topdressing (Chubachi et al., 1986; Miyashita et al., 1986; Takebe and Yoneyama, 1989; Takebe et al., 1990; Turner and Jund, 1991). Peng et al. (1993) reported a linear relationship between N_dw and SPAD values at each growth stage, but regression lines differed significantly among growth stages. Adjusting SPAD values for SLW, defined as dry weight per unit leaf area, improved the prediction of N_dw. Therefore, SLW influences the prediction of N_dw by SPAD. Peng et al. (1995b) further demonstrated that SPAD estimated N_a better than N_dw.

The most recent fully expanded leaf is usually considered the index leaf to reflect N status of the rice plant. Peng et al. (1996) proposed that a single SPAD threshold value can be used to determine the need for N topdressing during the entire growing season of a cultivar because N_dw of the index leaf decreases and SLW increases with plant age while SPAD values and N_a remained relatively constant throughout the growing period. Real-time N management using SPAD readings improved N use efficiency compared with the fixed-timing N treatment (Peng et al., 1996). In farmers' fields, SPAD-based N management produced higher yield and N use efficiency than farmers' practice (Garcia et al., 1996).

The high price of SPAD limits its use by individual income-poor farmers. Another simple, quick, and nondestructive method for estimating leaf N status is a LCC. There are several types of LCC developed for determining leaf greenness in rice. The most common ones are those developed by the International Rice Research Institute (IRRI); Zhejiang Agricultural University (ZAU), China; and the University of California, Davis (UCD), USA. The gamut of green colors is visually different among the three LCCs. Unlike the SPAD, which measures light absorption, an LCC measures leaf greenness and the associated leaf N by visually comparing light reflection from the surface of leaves and the LCC. Even though LCC has been tested for real-time N management in the farmers' fields in several countries (Balasubramanian et al., 1999), very limited information is available on the accuracy of LCC in estimating leaf N status of rice plants.

The objectives of this study were to (i) compare three different types of LCC in estimating rice leaf N status, (ii) determine if SLW affects the estimation of N_dw by LCC, and (iii) determine the relationship between LCC scores and SPAD values.

	MATERIALS AND METHODS

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This study was conducted at the IRRI Farm, Los Baños, Laguna (14°11' N, 121°15' E; 21 m above sea level), in the wet season (WS) of 2000 and the dry season (DS) of 2001. The soil at IRRI Farm was an Andaqueptic Haplaquoll. Three types of LCC as developed by IRRI, ZAU, and UCD were used. The LCC of IRRI has a scale of six colors scored 1 to 6. The LCC of ZAU has a scale of eight colors (3, 4, 5, 5.5, 6, 6.5, 7, and 8). The LCC of UCD has a scale of eight colors scored 1 to 8.

In 2000 WS, a split-plot design with four replicates was used. Nitrogen treatment (0, 45, 90, and 135 kg ha^-1) was designated as main plot and cultivar (IR72, PSBRc52, and IR65620-192-3-3-3-2) as subplots. Twelve-day-old seedlings were transplanted on 9 September at a hill spacing of 0.2 by 0.2 m with four seedlings per hill. Fertilizer N in the form of urea was split-applied, with 45% at 15 d after transplanting (DAT), 33% at panicle initiation (PI), and 22% at flowering (FL). All plots received 26 kg P ha^-1 and 40 kg K ha^-1 at 1 d before transplanting. All fertilizers were uniformly broadcasted by hand.

In 2001 DS, a split-plot design with four replicates was used. Nitrogen treatment (0, 60, 120, and 200 kg ha^-1) was designated as main plot and cultivar (IR72, IR8, and IR68440-36-2-2-3) as subplots. Fourteen-day-old seedlings were transplanted on 3 January at a hill spacing of 0.2 by 0.2 m with four seedlings per hill. Nitrogen was split-applied, with 30% at basal, 20% at midtillering (MT), 30% at PI, and 20% at FL. All plots received 30, 40, and 5 kg ha^-1 P, K, and Zn, respectively, at 1 d before transplanting. The timing and proportion of fertilizer application in both experiments were typical for irrigated rice in WS and DS in the Philippines. Pests were intensively controlled using chemicals to avoid yield loss. Fields were flooded 4 d after transplanting, and a floodwater depth of 5 to 10 cm was maintained until 7 d before harvest when fields were drained.

The LCC score and chlorophyll meter reading [SPAD-502, Soil Plant Analysis Dev. (SPAD) Section, Minolta Camera Co., Osaka, Japan] were taken at PI, 9 d after PI (PI + 9 d), and FL in 2000 WS and at MT, PI, and FL in 2001 DS. In each plot, the LCC score and SPAD reading were taken on four uppermost fully expanded leaves with similar leaf age. Three SPAD readings were taken around the midpoint of each leaf blade on one side of the midrib. Leaf color chart scores were also taken at the midsection of the same leaves. After LCC and SPAD measurements, the four leaves were sampled and combined for the measurement of area, dry weight, and N content. Area was measured by a leaf area meter (LI-3100, LI-COR, Lincoln, NE). Dry weight was determined after oven-drying at 70°C to constant weight. Leaf N contents were determined by micro-Kjeldahl digestion and distillation method (Bremner and Mulvaney, 1982) and calculated as the amount of N per unit dry weight (N_dw) and per unit leaf area (N_a). Specific leaf weight was calculated as the ratio of dry weight to leaf area.

Data were analyzed following analysis of variance (SAS Inst., 1982), and means were compared by LSD. Relationships of LCC scores to N_dw, N_a, and SPAD readings were determined by the regression analysis using data from each growth stage and pooled data across growth stages. Correlations among the scores of the three types of LCC were determined by the correlation analysis.

	RESULTS

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Nitrogen rates and cultivars had significant effect on LCC score, SPAD reading, N_dw, N_a, and SLW in most cases (Tables 1–4). Interactive effects between N rates and cultivars on LCC score, SPAD reading, N_dw, N_a, and SLW were significant in 11 out of 42 cases and mainly at FL in both seasons (data not shown). Values of the three LCCs, SPAD reading, N_dw, and N_a increased as the N rate increased while SLW decreased as the N rate increased (Tables 1 and 2). The N rate had larger effect on N_dw than on N_a and SPAD reading, especially at PI + 9 d and FL and when the variation in SLW was greatest among the N rates. Within a growth stage, the three LCCs responded to the N rates as sensitively as N_dw did.

Strong correlation existed among the scores of the three LCCs in WS and DS (Table 5). Leaf color chart score was related to N_dw, but the coefficients of determination varied depending on growth stage and season (Fig. 1). The coefficients of determination between LCC scores and N_dw were similar among the three LCCs. In general, LCC scores were related to N_dw more closely in 2001 DS than in 2000 WS. Furthermore, the relationships between LCC scores and N_dw were different across growth stages, as evidenced by the poor relationship between LCC scores and N_dw when data were pooled across growth stages.

View larger version (29K): [in this window] [in a new window]   Fig. 1. Relationship between leaf color chart (LCC) scores and leaf N concentrations per unit dry weight (Ndw) at panicle initiation (PI), 9 d after PI (PI + 9 d), and flowering (FL) in the wet season (WS) of 2000 and at midtillering (MT), PI, and FL in the dry season (DS) of 2001 across three cultivars and four N rate treatments. Leaf color charts were developed by the International Rice Research Institute (IRRI); Zhejiang Agricultural University (ZAU), China; and the University of California, Davis (UCD), USA.

View larger version (31K): [in this window] [in a new window]   Fig. 2. Relationship between leaf color chart (LCC) scores adjusted for specific leaf weight (SLW) and leaf N concentration per unit dry weight (Ndw) at panicle initiation (PI), 9 d after PI (PI + 9 d), and flowering (FL) in the wet season (WS) of 2000 and at midtillering (MT), PI, and FL in the dry season (DS) of 2001 across three cultivars and four N rate treatments. Leaf color charts were developed by the International Rice Research Institute (IRRI); Zhejiang Agricultural University (ZAU), China; and the University of California, Davis (UCD), USA.

View larger version (30K): [in this window] [in a new window]   Fig. 3. Relationship between leaf color chart (LCC) scores and leaf N content per unit area (Na) at panicle initiation (PI), 9 d after PI (PI + 9 d), and flowering (FL) in the wet season (WS) of 2000 and at midtillering (MT), PI, and FL in the dry season (DS) of 2001 across three cultivars and four N rate treatments. Leaf color charts were developed by the International Rice Research Institute (IRRI); Zhejiang Agricultural University (ZAU), China; and the University of California, Davis (UCD), USA.

View larger version (30K): [in this window] [in a new window]   Fig. 4. Relationship between leaf color chart (LCC) scores and chlorophyll meter (SPAD) values at panicle initiation (PI), 9 d after PI (PI + 9 d), and flowering (FL) in the wet season (WS) of 2000 and at midtillering (MT), PI, and FL in the dry season (DS) of 2001 across three cultivars and four N rate treatments. Leaf color charts were developed by the International Rice Research Institute (IRRI); Zhejiang Agricultural University (ZAU), China; and the University of California, Davis (UCD), USA.

	DISCUSSION

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Relationship between LCC scores and N_dw varied depending on the growth stage of rice plants. Adjusting LCC scores by SLW improved estimates of N_dw. Peng et al. (1993) reported that SPAD reading adjusted for SLW improved the prediction of N_dw of rice leaves. Because SPAD indirectly measures chlorophyll content of a leaf based on the amount of absorption of red light (at approximately 650 nm), a thick leaf, which usually has a larger SLW and likely greater chlorophyll content on an area basis, should absorb more light than a thin leaf. In contrast to measurements of light absorption, the LCC method visually matches the color of light reflected by the LCC and leaf surface. Apparently, a thick leaf tends to match with higher LCC scores than a thin leaf when the two leaves have the same chlorophyll and N contents on a dry weight basis.

Peng et al. (1995b) reported that SPAD estimated N_a better than N_dw within and across growth stages. Results of the present study also support this finding (data not shown). We expected that LCC, like SPAD, would also estimate N_a better than N_dw because of close relationship between LCC/SLW and N_dw. Leaf color chart scores were related to N_a more closely than to N_dw when growth stages were combined (Fig. 3 vs. 1). This was not always true when individual growth stage was considered.

All three types of LCC had a close relationship with SPAD reading across growth stages as well as within a growth stage. Leaf color chart could substitute for SPAD in estimating leaf N status. When the data were combined across N rates, cultivars, growth stages, and seasons, the regression equations between LCC scores and SPAD readings for the three LCC were

[1]

[2]

[3]

The three equations had similar coefficients of determination but appear to have different intercepts and slopes.

In irrigated rice grown under favorable tropical conditions, leaf N status is the major limiting factor for tillering, leaf area growth, biomass production, and grain yield. High and stable grain yield and great fertilizer use efficiency can be achieved if optimum leaf N status can be maintained throughout the growing season in this system (Peng et al., 1996). Photosynthesis per unit leaf area largely drives the crop growth rate, and leaf N content per unit leaf area is closely related to the photosynthetic rate (Peng et al., 1995a). Leaf color chart and SPAD are closely correlated with N_a. Therefore, for diagnosing leaf N status in real-time N management, LCC and SPAD can be used directly for determining the timing of N topdressing without adjusting for SLW. However, if LCC or SPAD is used to estimate N_dw, SLW has to be considered.

A single SPAD threshold value was used to determine the need for N topdressing during the entire growing season of a cultivar (Peng et al., 1996). The direct relationship of LCC score with N_a and SPAD across growth stages also provides confidence that one value can be used as the critical LCC color for the timing of all N topdressing with a given cultivar. Peng et al. (1996) reported that a SPAD threshold value of 35 is suitable to determine the optimal timing of N topdressing for most modern indica cultivars. The SPAD value of 35 corresponded to an LCC-IRRI score of 3.2, an LCC-ZAU score of 4.8, and an LCC-UCD score of 5.2 according to Eq. [1], [2], and [3], respectively. An LCC score of 3.0 has been used with LCC-IRRI in the Long-Term Fertilizer Experiment at IRRI to guide in-season N management of modern indica cultivars (R. Buresh, personal communication, 2001). Singh et al. (2002) reported that N management based on the critical LCC score of 4.0 with LCC-IRRI helped avoid overapplication of N to rice crop. Leaf color chart has been tested for real-time N management in the farmers' fields in several countries (Balasubramanian et al., 1999). The critical LCC score for the timing of N topdressing, however, has to be determined for different cultivar, crop establishment (direct seeding vs. transplanting), season (DS vs. WS), and location (Singh et al., 2002).

All three LCCs are suitable for use by rice farmers in determining the timing of N topdressing for real-time N management. However, they are not interchangeable because the critical leaf color grade for use in determining the timing of N topdressing varies among the LCCs. Promotion in a given area of only one type of LCC—with high consistency in color grades among manufactured pieces—would help avoid confusion among farmers regarding the critical LCC grade for N topdressing.

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This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (14) Citing Articles via Google Scholar Google Scholar Articles by Yang, W.-H. Articles by Witt, C. Search for Related Content PubMed Articles by Yang, W.-H. Articles by Witt, C. Agricola Articles by Yang, W.-H. Articles by Witt, C. Related Collections Rice Crop Physiology & Metabolism Nitrogen Nutrient Management Plant Analysis Plant Nutrition