Published online 19 September 2005
Published in Agron J 97:1380-1389 (2005)
DOI: 10.2134/agronj2004.0268
© 2005 American Society of Agronomy
677 S. Segoe Rd., Madison, WI 53711 USA
Nitrogen Management
N-Tester Use in Soft Winter Wheat
Evaluation of Nitrogen Status and Grain Yield Prediction
M. A. Ortuzar-Iragorria,*,
A. Alonsoa,
A. Castellóna,
G. Besgaa,
J. M. Estavillob and
A. Aizpuruaa
a Neiker, Berreaga 1, 48160 Derio, Spain
b Dpto. Biología Vegetal y Ecología, UPV/EHU, Apdo. 644, 48080 Bilbao, Spain
* Corresponding author (hortuzar{at}neiker.net)
Received for publication October 25, 2004.
 |
ABSTRACT
|
|---|
Chlorophyll meters can be an alternative to traditional tissue analysis as plant N nutritional diagnostic tools. In the present study, the relationships among chlorophyll meter N-Tester measurements, plant N concentration, N uptake at different growth stages (GS-32, GS-37), and grain yield were studied to evaluate the N-Tester as a tool to diagnose the N status of soft red winter wheat (Triticum aestivum L. cv. Soissons) and predict yield. Ten experiments were conducted in the years 2001, 2002, and 2003 where 0, 100, 140, 180, and 220 kg N ha–1 were applied. N-Tester values ranged between average values of 382 and 608 at GS-32 for 0 and 220 kg N ha–1, respectively, and between 408 and 649 at GS-37 for 0 and 220 kg N ha–1 correspondingly. The normalization of N-Tester values in relation to a non-N-limited plot (i.e., 
220 kg N ha–1) enabled the prediction of plant N concentration (R2 = 0.64) of Soissons soft red winter wheat at GS-32 and N uptake at both at GS-32 and GS-37 (R2 > 0.6) in contrast to absolute N-Tester values (R2 < 0.4). However, when excluding the N-Tester values corresponding to control treatments (0 kg N ha–1), the robust correlations diminished as to invalidate comparison of normalized N-Tester readings for N concentration and N uptake across different sites and years for rates in the 100 to 220 kg N ha–1 range. Normalized N-Tester values could discriminate between grain yields from non-N-fertilized and fertilized plots but could not distinguish grain yields among plots fertilized in the 100 to 220 kg N ha–1 range.
Abbreviations: GS, growth stage • SRWW, soft red winter wheat
|
INTRODUCTION
|
|---|
ACCORDANCE BETWEEN N needs of the crop and N fertilization is essential to achieve high grain yields and decrease N losses to the environment. To synchronize N applications and crop demand, the need for a tool that indicates the nutritional status of the plant arises. Dried tissue analysis conventionally employed to ascertain the nutritional status of the plant is time-consuming and destructive. Thus, the instantaneous and nondestructive chlorophyll meter is gaining acceptance as an alternative. The N-Tester is based on the chlorophyll meter SPAD 502, which is designed and produced by Minolta Corp. (Tokyo, Japan). Yara International adapted this device especially to agronomic needs and developed fertilizer recommendations based on plant chlorophyll concentration (Neukirchen and Lammel, 2002). The device measures the light transmittance of the leaf at red (650 nm, around maximum chlorophyll absorption) and near-infrared (NIR, 960 nm) wavelengths. By measuring both wavelengths simultaneously, it is possible to correct the reading for any differences in leaf thickness. Using red and NIR values, the N-Tester calculates a numeric, dimensionless value that is proportional to the amount of total chlorophyll present in the leaf (Neukirchen and Lammel, 2002).
Chlorophyll meter readings have largely proven to be well correlated with leaf chlorophyll and/or leaf N concentration in several cereals such as barley (Hordeum vulgare L.) (Wienhold and Krupinsky, 1999), corn (Zea mays L) (Schepers et al., 1992), rice (Oryza sativa L.) (Peng et al., 1993), and wheat (Follett and Follett, 1992; Peltonen et al., 1995). The correlation between chlorophyll meter values and N content of shoots has been less studied but has also proven to be good (Vaugham et al., 1990; Fox et al., 1994; López-Bellido et al., 2004). Using N concentration of the aerial part of the plant facilitates sampling and avoids problems described by various authors about what part of the plant best represents the N status (Duru, 2002; Hoel, 1998).
The basic utility of the N-Tester chlorophyll meter is providing information on the N nutritional status of the plant for guidance in N fertilizer application. However, since N status throughout the growing season has a clear influence on yield, several authors (Follett and Follett, 1992; Fox et al., 1994; López-Bellido et al., 2004) have studied the relationships between chlorophyll meter readings at different GS's and yield. Follett and Follett (1992) reported that, for winter wheat, little relationship existed between chlorophyll meter readings and either leaf N concentration or grain yield across sites, leading the authors to conclude that more research was needed on the effects of site location, moisture availability, cultural practices, and cultivar differences; thus, the importance of extending the study to diverse edaphoclimatic conditions. They also suggested that normalizing the data using a non-N-limited reference plot may be necessary, as has been suggested for corn (Piekielek Fox, 1992; Schepers et al., 1992; Fox et al., 1994).
The objectives of this study were to validate the N-Tester as a diagnostic tool for determining the N status of soft red winter wheat (SRWW) and evaluate its usefulness for predicting grain yield. The relationships among N concentration of shoots, N extracted by the aerial part of the plant, and grain yield were compared with N-Tester measurements at different wheat GS's.
|
MATERIALS AND METHODS
|
|---|
Field Trials
Ten experiments were conducted for three consecutive years (2001, 2002, and 2003) near Vitoria city (42°51' N, 2°41' W; 513 m above sea level), in the province of Alava, on SRWW (cv. Soissons). Each experiment consisted of a randomized complete block experimental design with four replications, the size of each plot being 50 m2. Sowing dates ranged between 2 November and 2 January. Harvest occurred between 13 July and 8 August.
Table 1 summarizes the chemical and textural features of the soils. The soil parameters shown in this table were obtained from a mixture of eight samples per experiment before sowing. The exception was soil mineral N (ammonium N plus nitrate N), which was determined from a mixture of 24 samples per experiment (i.e., eight samples on three blocks at each experiment) sampled at the end of winter before the first N application. Soils were analyzed for extractable K (NH4AcO), P (sodium bicarbonate, 0.5 M) (Olsen and Dean, 1965), pH (1:2.5 water), and soil mineral N (KCl, 1 M). Potassium was determined by atomic absorption spectrophometry and P and soil mineral N by colorimetry. Organic carbon was determined by the Walkey method (1935).
Before seeding, 90 kg P2O5 ha–1 and 90 kg K2O ha–1 were broadcast at every experiment as 0–14–14. The N treatments applied are shown in Table 2 and ranged from 0 to 220 kg N ha–1. In 2001, ammonium nitrosulphate (26% N, w/w) was used at tillering and ammonium calcium nitrate (27% N, w/w) at jointing. For the 2002 and 2003 seasons, ammonium nitrate (33.51% N, w/w) was used both at tillering and jointing. In 2001, ammonium nitrosulphate was used to satisfy possible sulfur deficiencies as reported by wheat growers in the zone. Not observing such in year 2001, the N source was replaced by ammonium nitrate.
N-Tester Measurements
Readings were taken using the N-Tester chlorophyll meter at midlength of the uppermost fully expanded leaf from 30 randomly selected plants per plot at GS 32 and 37 (Zadoks et al., 1974) that respectively correspond to the GS when the second node is visible and when the flag leaf is visible. These timings are recommended by the Yara International and permit a later N fertilizer application. The measurements were taken from 1000 to 1600 h in days that it did not rain.
Normalized N-Tester values were calculated to avoid the noise encountered by variables other than N fertilization such as site location or edaphoclimatic conditions. Normalized values were calculated as a percentage by assigning the 100% value for each experiment to the plot in the same block that received 220 kg N ha–1.
Plant Measurements
Biomass and N concentration per plot were estimated at GS-32 and GS-37 in years 2001 and 2002. These measures were taken in the same GS's as N-Tester readings GS-32 and GS-37, with the aim of setting the relationships between the chlorophyll meter and the N concentration and N uptake of the aerial part of the plant at these moments. A 0.25-m2 area of every plot in one block per experiment was randomly chosen and the plants in this area cut. Fresh plants were oven-dried at 70°C for at least 48 h to assess their biomass and then ground through a 1-mm screen before being analyzed for total N concentration in the aerial part of the plant. Total N was determined by the Kjeldahl procedure (AOAC Int., 1999) with a Kjeltec Auto Sampler System 1035 analyzer (Tecator). Shoot N uptake was calculated as the product of observed N concentration of the aerial part of the plant and its biomass. The normalized plant N concentration and normalized N uptake values were calculated by respectively assigning the 100% value to the plant N concentration and N uptake, both at the aerial part of the plant, obtained in the plot fertilized with 220 kg N ha–1.
Grain yield was determined by harvesting the central 1.5 m of each plot. Grain yield results were adjusted to 120 g kg–1 moisture content. Grain was finely ground to pass through a 0.5-mm sieve, and total N was determined as noted above.
Weather Conditions
Years 2001 and 2002 were very similar in temperature while 2003 was noticeably colder during the months of January and February and hotter from June to September (Fig. 1)
. Winter was rainiest in 2003. However, during all 3 yr, sufficient precipitation occurred in late spring to allow a normal growing season for the region.
View larger version (30K):
[in this window]
[in a new window]
|
Fig. 1. Total rainfall (mm) and mean temperature (Ta, °C) per month in the years 2001, 2002, and 2003 in Gauna (Alava).
|
|
Statistics
Determination coefficients relating N-Tester readings with the studied variables corresponding to the linear, exponential, logarithmic, quadratic, and potential equations were calculated. Due to the similarity between results, the linear model was chosen for simplicity, and only determination coefficients regarding this model are shown in this work.
The determination coefficient (R2) between the study variables was calculated by the PROC REG procedure (SAS Inst, 1998). In the case of N-Tester vs. N concentration and vs. N uptake by the aerial part of the plant, single values were correlated while in the case of N-Tester vs. grain yield, the values stated are mean values among three or four blocks as suggested by Gomez and Gomez (1983) for cases when more than one replication exists.
Statistical differences in yield among treatments were evaluated by ANOVA according to the linear model in the PROC GLM procedure in the SAS system, Version 8.0 for Windows.
|
RESULTS AND DISCUSSION
|
|---|
N-Tester vs. Shoot Nitrogen Concentration and Shoot Nitrogen Uptake
N-Tester values ranged between 271 and 723 units for Soissons SRWW in Alava. The values obtained over the 10 experiments for the treatments where 0, 140, and 220 kg N ha–1 was applied were 382, 560, and 608, respectively, at GS-32 and 408, 600, and 649, respectively, at GS-37. In general, N-Tester values measured in Alava were similar to those attained in the neighbor region of Navarra (Arregui and Irañeta, personal communication, 2004). In contrast, the values obtained were slightly below those obtained by the Hanninghof Research Centre for the Yara International on the same SRWW variety under German edaphoclimatic conditions (Brentrup, personal communication, 2004). In the edaphoclimatic conditions of Alava at the GS-37 phenological stage, the Yara International N-Tester reads, on average, 649 units on what has been considered non-N-limited (220 kg N ha–1) Soissons SRWW. In contrast, in Germany, for the same wheat variety, when the N-Tester reads 660 units at the same phenological stage, an addition of 20 or 30 kg N ha–1 is recommended, and it is at 680 units or beyond when further fertilization is not advised. López-Bellido et al. (2004) state that a note of caution is needed regarding the universality of chlorophyll meter calibrations across geographical locations since different growing conditions among sites may affect the relationship with N concentration of the shoots. Again, the importance of studying the chlorophyll meter results under different climatic and soil conditions is evident.
The R2 values corresponding to the relationship between N-Tester values and shoot N concentration and between N-Tester values and shoot N uptake are shown in Table 3. It can be observed that at GS-32, better relationships were attained between N-Tester readings and shoot N concentration than between N-Tester readings and shoot N uptake. In fact, the first correlations are generally strong enough as to consider absolute N-Tester readings as accurate prediction of aboveground plant N concentration at GS-32 at each individual experiment.
View this table:
[in this window]
[in a new window]
|
Table 3. Range and mean of N-Tester values, shoot N concentration, and shoot N uptake and determination coefficients (R2) corresponding to the relationship between N-Tester values and shoot N concentration and between N-Tester values and shoot N uptake at GS-32 and GS-37 in 2001 and 2002.
|
|
As described by Leigh and Johnston (1985) and Justes et al. (1997), in Table 3, it can be noticed that as plants grew, N concentration in shoots decreased due to the dilution of N with structural cellulose, which is specially marked during stem elongation, from GS-31 to GS-37 (Barraclough, 1997). While N-Tester values measure the greenness of the uppermost fully expanded leaf and remained quite constant from one phenological stage to the next, N concentration in shoots measures the percentage of N in the whole aerial part of the plant and decreased as the plant grew older (Table 3). Thus, as stems grow, N concentration values of the whole aerial part of the plant differ more from those in the leaf. In an attempt to account for the dilution of N with structural cellulose, N-Tester measurements were also related to N uptake of shoots (Table 3). Shoot N uptake was slightly better related than shoot N concentration to N-Tester readings only at GS-37 when the leaf N concentration differs more from that of the aerial part of the plant. At this phenological stage, the biomass parameter needed for the calculation of shoot N uptake slightly restored the divergence between the shoot N concentration and the leaf N concentration, which as previously commented, has been proven to be well correlated to chlorophyll content as measured by the N-Tester. Correlations between N-Tester readings and N concentration in the aboveground part of the plant at GS-37 were not significant in any of the individual experiments while correlations between N-Tester readings and shoot N uptake were significant for three experiments out of seven. These three strong correlations do not validate the N-Tester at GS-37 as a good indicator of shoot N uptake in every experiment. At GS-32, where the dilution effect is less influential, the correlation between the N-Tester readings and shoot N uptake was worse than the very robust correlation between N-Tester and shoot N concentration. In contrast, Fox et al. (1994) and López-Bellido et al. (2004) found the readings of the Minolta SPAD 502 chlorophyll meter to be highly correlated to shoot N concentration at GS-30 and even at the advanced phenological stage of GS-60 (anthesis). This led these authors to consider the chlorophyll meter an effective indicator of shoot N concentration.
When data from all experiments obtained at GS-32 were gathered and plotted, the determination coefficient between N-Tester readings and shoot N concentration decreased to 0.44 in comparison with the individual correlations obtained for each experiment (Table 3). This indicates the existence of factors other than N fertilization that affected the N-Tester readings, presumably the management and the edaphoclimatic conditions of each site and year when the experiments were performed. At GS-37, the R2 (0.43) obtained for all values corresponding to N-Tester readings and shoot N uptake was stronger than the R2 (0.27) obtained for all values corresponding to N-Tester readings and N concentration in shoots because this measurement accounted for the dilution effect, similar to what was observed for the individual correlations. In no case could the linear model explain more than 44% of the variance of the studied variables, as expressed by determination coefficients below 0.44. Thus, it is not advisable to compare N-Tester readings for either shoot N concentration or N uptake without regard to the site or year of measurement.
To avoid this problem, variables were normalized similar to the technique suggested by Follett and Follett (1992). A value of 100% was assigned to the plot in the same block that received 220 kg N ha–1 (Table 3). Normalization enhanced the prediction of both shoot N concentration and shoot N uptake of aboveground plant, especially at GS-32 in the case of the normalized shoot N concentration and at GS-32 and GS-37 in the case of the normalized shoot N uptake. In these cases, correlations were robust enough (R2 > 0.6) to consider normalized data quite free of influences other than N nutritional status (Table 3). However, Baret and Fourty (1997) stated that, with respect to chlorophyllmeter methodology, the choice of a light spectrum band centered close to the maximum chlorophyll absorption at 680 nm is not optimal for high chlorophyll concentration values because of the very small sensitivity of the transmittance in those conditions. They suggested that the choice of two or three bands in the red edge in between 680 and 780 nm would allow the method to be more sensitive across the widest range of situations. In fact, when excluding the N-Tester values corresponding to the control treatments (0 kg N ha–1), the robust correlation between normalized N-Tester values and normalized shoot N concentration in the aerial part of the plant at GS-32 diminished from 0.64 to 0.57 and so did the correlation between normalized N-Tester and normalized shoot N update, decreasing from 0.61 both at GS-32 and GS-37 to 0.46 and 0.48 at GS-32 and GS-37, respectively. Therefore, when N rates ranging from 100 to 220 kg N ha–1 were applied, comparison of normalized N-Tester readings across different sites and years that refer to normalized shoot N concentration and normalized shoot N uptake is not possible.
N-Tester vs. Grain Yield
Apart from the utility of the chlorophyll meter as a plant N nutritional diagnostic tool, many authors (Follett and Follett, 1992; Fox et al., 1994; López-Bellido et al., 2004) have studied its yield-predicting capacity.
In Fig. 2 and 3
, N-Tester values are plotted vs. the corresponding grain yield values at GS-32 and GS-37, respectively. At each experiment, the linear model was applied both including and excluding the control treatments (0 kg N ha–1). Grain yields ranged from 1.1 Mg ha–1 in control treatment at Experiment 3 to 10 Mg ha–1 at Experiment 5, which was preceded by bean (Phaseolus vulgaris L.). When all treatments (control included) were studied at each experiment individually, the relationships between leaf chlorophyll meter readings and grain yield were generally strong both at GS-32 and GS-37 (Fig. 2 and 3) and would lead to the conclusion that the N-Tester was an effective indicator of grain yield. Correlations remained quite constant from one stage to the other, also leading to the conclusion that N-Tester readings are equally correlated to grain yield regardless of phenological stage at measurement from GS-32 or GS-37 (Fig. 2 and 3). López-Bellido et al. (2004) found Minolta SPAD readings from the flag leaf to be highly correlated with grain yield at the more advanced phenological stages, from GS-39 to GS-41.
View larger version (22K):
[in this window]
[in a new window]
|
Fig. 2. N-Tester values at Growth Stage 32 vs. grain yield. The normal and dotted lines represent the linear relationship between the variables when the control treatment (0 kg N ha–1 applied) is respectively included (equation and R2 in the upper corner) and excluded (equation and R2 in the lower corner).
|
|
View larger version (25K):
[in this window]
[in a new window]
|
Fig. 3. N-Tester values at Growth Stage 37 vs. grain yield. The normal and dotted lines represent the linear relationship between the variables when the control treatment (0 kg N ha–1 applied) is respectively included (equation and R2 in the upper corner) and excluded (equation and R2 in the lower corner).
|
|
However, the correlations commented to the moment must be dismissed since they derive from curves where two clusters of data are clearly observed: data from non-N-fertilized plots and data generated at the rest of the plots (Fig. 2 and 3). If control treatments were excluded, significant correlations for each individual experiment were only attained at GS-32 in Experiments 2, 4, 6, and 10 and at GS-37 in Experiment 2. Yield response to N-rate was analyzed by ANOVA to prove there were differences in yield not only in the 0 to 220 kg N ha–1 but also in the 100 to 220 kg N ha–1 rate range that the N-Tester could not detect. The model showed N rate affected yield at all experiments when control treatment was included and at Experiments 2, 3, 4, 5, 6, 8, 9, and 10 when it was excluded (Table 4). Consequently, the N-Tester could not be considered a tool for discerning and predicting grain yields among differently fertilized plots in the phenological stages of GS-32 and GS-37 when the minimum N rate was greater than 100 kg N ha–1. Delaying N-Tester measurement might be considered since a later knowledge of the N nutritional status of the plant may correlate with yield more accurately. In such way, the probabilities of unexpected happenings such as diseases, climatic changes, etc., that affect grain yield after measurement are reduced. However, within the habitual crop management where neither irrigation nor leaf N applications are practiced, late measures of N nutritional status of the plant are of little practical value for it is too late to take corrective fertilizer action to improve grain yield.
View this table:
[in this window]
[in a new window]
|
Table 4. Existence of statistical differences in yield among treatments detected by ANOVA (p < 0.05), expressed by an X.
|
|
Grain yield values were normalized by assigning a value of 100% to the grain yield obtained at the plot that received 220 kg N ha–1 for comparison across sites and years. Determination coefficients between normalized N-Tester values and the corresponding normalized grain yield values obtained at all experiments are concurrently shown in Table 5. Normalized N-Tester values ranged from 43.9 to 111.1%, the average being 88.4% at GS-32 and 87.9% at GS-37. When the control treatment was excluded, determination coefficients radically decreased from 0.75 to 0.20 at GS-32 and from 0.64 to 0.09 at GS-37 (Table 5). These correlations are weak, and therefore normalized N-Tester values cannot be considered a tool for normalized grain yield prediction when only N rates greater than 100 kg ha–1 are applied. These weak correlations are explained by the fact that normalized shoot N concentration and N uptake with normalized N-Tester and also normalized shoot N concentration and N uptake with normalized grain yield (Table 6) were poorly correlated both at GS-32 and GS-37 phenological stages when control treatments were not included. Fox et al. (1994) also found a weak relationship between tissue N concentration and grain yield but concluded that the chlorophyll meter was a useful tool since it was more accurate than tissue N concentration in predicting N fertilizer needs.
View this table:
[in this window]
[in a new window]
|
Table 5. Normalized N-Tester values, normalized grain yield values, and the determination coefficients (R2) of the relationship between normalized N-Tester values and normalized grain yield values at GS-32 and GS-37 phenological stages at all 10 experiments. When specified, the R2 does not include the control treatment.
|
|
View this table:
[in this window]
[in a new window]
|
Table 6. Determination coefficients (R2) corresponding to the relationship between normalized grain yield values and normalized shoot N concentration and between the normalized grain yield values and normalized N uptake in 2001 and 2002. When specified, the R2 does not include the control treatment.
|
|
When data in Table 5 were plotted (Fig. 4)
, it could be observed that normalized N-Tester values differed between the grain yield of a non-N-fertilized plot and a N-fertilized one but did not distinguish statistically different grain yields (Table 4) within differently fertilized plots. Normalized N-Tester values below 76% predicted a normalized grain yield that corresponded to an unfertilized plot (<63% grain yield), with an error of 9%, as calculated by the method described by Cate and Nelson (1971) (Fig. 4). Normalized N-Tester values greater than 76% predicted grain yields corresponding to fertilized plots, failing in 2% of the analyzed cases. It is also possible to use absolute N-Tester readings for the same purpose. Values below 461 N-Tester units predicted a normalized grain yield that corresponded to an unfertilized plot (<63% grain yield) with an error of 7%, and values beyond 461 predicted a normalized grain yield larger than 63% failing in 2% of the cases studied (Fig. 5)
. Fox et al. (1994) also found the Minolta SPAD meter to detect the response of a N fertilized plot in contrast to an unfertilized one in terms of grain yield. In the edaphoclimatic conditions of Alava, control treatments can easily be distinguished by sight; besides, wheat is never left unfertilized. Thus, the N-Tester is of little use in grain yield prediction in these edaphoclimatic conditions. Nonetheless, it could be used as a detector for banned fertilization on green filters. A large portion of the area where wheat is grown in Alava lies in a zone declared as vulnerable to water pollution caused by nitrates derived from agriculture by the European Directive 91/676/CEE. In this area, no N fertilization is allowed within 3 m of watercourses of any kind. The N-Tester could be a tool to detect banned N fertilization in case it took place. If normalized N-Tester values were to be used, a non-N-limited area (i.e., 220 kg N ha–1) should be provided.
View larger version (19K):
[in this window]
[in a new window]
|
Fig. 4. Normalized N-Tester values vs. normalized grain yield values at Growth Stage (GS) 32 and GS-37 phenological stages. Values obtained at control treatments are plotted as open symbols.
|
|
View larger version (16K):
[in this window]
[in a new window]
|
Fig. 5. Absolute N-Tester values vs. normalized grain yield values at Growth Stage (GS) 32 and GS-37 phenological stages. Values obtained at control treatments are plotted as open symbols.
|
|
|
CONCLUSIONS
|
|---|
The normalization of N-Tester values in relation to a non-N-limited plot (i.e., 220 kg N ha–1) enabled the prediction of the N nutritional status of Soissons wheat as N concentration of the aerial part of the plant at GS-32 (R2 = 0.64) and as shoot N uptake both at GS-32 and GS-37 (R2 > 0.6) in contrast to absolute N-Tester values (R2 < 0.4). However, when excluding N-Tester values corresponding to control treatments, the robust correlations for normalized N concentration and N uptake diminished as to invalidate comparison of normalized N-Tester readings across site-years.
Similarly, normalized N-Tester values could discriminate between grain yields from non-N-fertilized and fertilized plots with a boundary normalized grain yield value of around 63%. However, they could not distinguish grain yields among plots fertilized in the 100 to 220 kg N ha–1 range.
|
ACKNOWLEDGMENTS
|
|---|
The authors gratefully acknowledge the expert technical assistance of Dr. Neurkirchen and Dr. Brentrup as well as Yara International for the apparatus facilities. This work was financially supported by FEDER funds (2FD97-2425-C06-03) and the Spanish Government (MCyT project AGL2001-2214-CO6-06).
|
REFERENCES
|
|---|
- AOAC International. 1999. Plants. p. 1–35. In Patricia Cunniff (ed.) Official methods of analysis of AOAC International. 16th ed. AOAC Int., Gaithersburg, MD.
- Baret, F., and Th. Fourty. 1997. Radiometric estimates of nitrogen status of leaves and canopies. p. 201–229. In G. Lemaire (ed.) Diagnosis of the nitrogen status in crops. Springer-Verlag, Berlin Heidelberg, Germany.
- Barraclough, P.B. 1997. N requirement of winter wheat and diagnosis efficiency. p. 117–124. In M.J. Gooding and P.R. Shewry (ed.) Optimising cereal inputs: Its scientific basis, Part I: Genetics and nutrition. The Assoc. of Appl. Biol., Warwick, UK.
- Cate, R., and L.A. Nelson. 1971. A simple statistical procedure for partitioning soil test correlation data into two classes. Soil Sci. Soc. Am. J. 35:658–660.[Abstract/Free Full Text]
- Duru, M. 2002. Evaluation of chlorophyll meter to assess N status of cocksfoot sward. J. Plant Nutr. 25:275–286.
- Follett, R.H., and R.F. Follett. 1992. Use of a chlorophyll meter to evaluate the nitrogen status of dryland winter wheat. Commun. Soil Sci. Plant Anal. 23:687–697.
- Fox, R.H., W.P. Piekielek, and K.M. Macneal. 1994. Using a chlorophyll meter to predict nitrogen fertilizer needs of winter wheat. Commun. Soil Sci. Plant Anal. 25:171–181.
- Gomez, K.A., and A.A. Gomez. 1983. Regression and correlation analysis. p. 357–423. In John Wiley & Sons (ed.) Statistical procedures for agricultural research. 2nd ed. John Wiley & Sons, New York.
- Hoel, B.O. 1998. Use of a hand-held chlorophyll meter in winter wheat: Evaluation of different measuring positions on the leaves. Acta Agric. Scand., Sect. B 48:222–228.
- Justes, E., M.H. Jeuffroy, and B. Mary. 1997. Wheat, barley and durum wheat. p. 163–188. In G. Lemaire (ed.) Diagnosis of the nitrogen status in crops. Springer-Verlag, Berlin Heidelberg, Germany.
- Leigh, R.A., and A.E. Johnston. 1985. Nitrogen concentrations in field-grown spring barley: An examination of the usefulness of expressing concentrations on the basis of tissue water. J. Agric. Sci. 105:397–406.
- López-Bellido, R.J., C.E. Shepherd, and P.B. Barraclough. 2004. Predicting postanthesis N requirements of bread wheat with a Minolta SPAD meter. Eur. J. Agron. 20:313–320.
- Neukirchen, D., and J. Lammel. 2002. The chlorophyll content as an indicator for nutrient and quality management. Nawozy i Nawozenie–Fertilizers and Fertilization 11:89–109.
- Olsen, S.R., and L.A. Dean. 1965. Phosphorous. p. 1035–1049. In C.A. Black (ed.) Methods of soil analysis. Part 2. ASA, Madison, WI.
- Peltonen, J., A. Virtanen, and E. Haggren. 1995. Using a chlorophyll meter to optimize nitrogen fertilizer application for intensively-managed small-grain cereals. J. Agron. Crop Sci. 174:309–318.
- Peng, S., R.C. García, R.C. Laza, and K.G. Cassman. 1993. Adjustment for specific leaf weight improves chlorophyll meter's estimate of rice leaf nitrogen concentration. Agron. J. 85:987–990.[Abstract/Free Full Text]
- Piekielek, W.P., and R.H. Fox. 1992. Use of a chlorophyll meter to predict sidedress nitrogen requirements of maize. Agron. J. 84:59–65.[Abstract/Free Full Text]
- SAS Institute. 1998. SAS version 8. SAS Inst., Cary, NC.
- Schepers, J.S., D.D. Francis, M. Vigil, and F.E. Below. 1992. Comparison of corn leaf nitrogen concentration and chlorophyll meter readings. Commun. Soil Sci. Plant Anal. 23:2173–2187.
- Vaugham, B., D.G. Westfall, and K.A. Barbarick. 1990. Spring nitrogen fertilizer recommendation models for dryland hard red winter wheat. Agron. J. 82:565–571.[Abstract/Free Full Text]
- Walkey, A. 1935. An examination of methods for determining organic carbon and nitrogen in soils. J. Agric. Sci. 25:598–609.
- Wienhold, B.J., and J.M. Krupinsky. 1999. Chlorophyll meter as nitrogen management tool in malting barley. Commun. Soil Sci. Plant Anal. 30:2551–2562.
- Zadoks, J.C., T.T. Chang, and C.F. Konzak. 1974. A decimal code for the growth stages of cereals. Weed Res. 4:415–421.
This article has been cited by other articles:
|
|
|
|
 
J. Zhang, A. M. Blackmer, J. W. Ellsworth, and K. J. Koehler
Sensitivity of Chlorophyll Meters for Diagnosing Nitrogen Deficiencies of Corn in Production Agriculture
Agron. J.,
May 7, 2008;
100(3):
543 - 550.
[Abstract]
[Full Text]
[PDF]
|
|
|
TOP
ABSTRACT
INTRODUCTION
