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Journal of Plant Nutrition
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CATEGORIZATION OF BRASSICA CULTIVARS FOR PHOSPHORUS ACQUISITION FROM PHOSPHATE ROCK ON BASIS OF GROWTH AND IONIC PARAMETERS
Tariq Aziza; Rahmatullahb; M. Aamer Maqsoodb; M. Sabirb; S. Kanwalb a Institute of Soil and Environmental Science, University of Agriculture, Depalpur, Pakistan b Institute of Soil & Environmental Sciences, University of Agriculture, Faisalabad, Faisalabad, Pakistan Online publication date: 06 February 2011
To cite this Article Aziz, Tariq , Rahmatullah, Maqsood, M. Aamer , Sabir, M. and Kanwal, S.(2011) 'CATEGORIZATION
OF BRASSICA CULTIVARS FOR PHOSPHORUS ACQUISITION FROM PHOSPHATE ROCK ON BASIS OF GROWTH AND IONIC PARAMETERS', Journal of Plant Nutrition, 34: 4, 522 — 533 To link to this Article: DOI: 10.1080/01904167.2011.538114 URL: http://dx.doi.org/10.1080/01904167.2011.538114
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Journal of Plant Nutrition, 34:522–533, 2011 C Taylor & Francis Group, LLC Copyright ISSN: 0190-4167 print / 1532-4087 online DOI: 10.1080/01904167.2011.538114
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CATEGORIZATION OF BRASSICA CULTIVARS FOR PHOSPHORUS ACQUISITION FROM PHOSPHATE ROCK ON BASIS OF GROWTH AND IONIC PARAMETERS
Tariq Aziz,1 Rahmatullah,2 M. Aamer Maqsood,2 M. Sabir,2 and S. Kanwal2 1 Institute of Soil and Environmental Science, University of Agriculture, Faisalabad at Depalpur, Depalpur, Pakistan 2 Institute of Soil & Environmental Sciences, University of Agriculture, Faisalabad, Faisalabad, Pakistan
2 We categorized sixteen Brassica cultivars for their differential growth response and phosphorus (P) acquisition from phosphate rock (PR) and monoammonium phosphate (MAP). Plants were grown with both P sources in a nutrient solution experiment for 40 days. Cultivars differed significantly (P < 0.01) both for absolute as well as relative values of growth and physiological parameters at both P sources. Phosphorus deficiency in PR treatment significantly depressed biomass production (more than 2.5 times than control) and P concentration (about 1.5 times) in all of the cultivars. ‘Rainbow’ and ‘Poorbi Raya’ produced significantly more relative biomass than other cultivars grown with PR. Cultivars were classified into three classes on the basis of mean values of different parameters and their standard deviation viz low, medium and high. Cultivars were also classified into different classes while regressing biomass and P contents. Cultivars ‘Rainbow’ and ‘Poorbi Raya’ accumulated maximum shoot dry matter (1.21 and 1.27 g dry matter/plant, respectively) grown with phosphate rock, hence were categorized as high biomass producers. Cultivars ‘Rainbow’, ‘KS-74’, and ‘Poorbi Raya’ accumulated maximum P (5.58, 5.24, and 4.81 mg P plant −1, respectively) from PR and were categorized as high P accumulators. Cultivars with high biomass and high P contents such as ‘Rainbow’ and ‘Poorbi Raya’ at low available P (Rock P) would be used in further screening experiments to improve P efficiency in Brassica.
Keywords:
Brassica, phosphorus, genetic variability, categorization
INTRODUCTION Phosphorus (P) deficiency in soil is a major limiting factor for crop production as >30% of the world’s arable land is deficient in available P (von Uexkull and Mutert, 1995). Phosphorus deficiency can lead to yield Received 1 April 2009; accepted 29 April 2010. Address correspondence to Tariq Aziz, Institute of Soil and Environmental Science, University of Agriculture, Faisalabad at Depalpur, Depalpur, Pakistan. E-mail:
[email protected]
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losses from 5% to 15% of the maximal yields (Shenoy and Kalagudi, 2005). Recently, Tan et al. (2005) estimated global soil nutrient budget for wheat, rice, maize and barley. They reported a global soil P deficit of 5.1 kg ha−1yr−1, covering 85% of harvested area in the year 2000. Globally P deficit results in the average yield loss of about 1093 kg ha−1yr−1 and a total production loss of 491.5 × 106 kg yr−1. The situation impels seeking multi-dimensional solutions for this problem instead of conventionally available high input approach because of increased environmental concerns of phosphatic fertilizer use (Vance et al., 2003). The development of crops that either acquire or use P more efficiently may sustain crop productivity on soils low in available P as sufficient variability for P efficiency has been reported among different crop cultivars (Gahoonia et al., 2000; Vance et al., 2003; Aziz et al., 2005, 2006; Hao et al., 2008; Yasin and Malhi, 2009). Plants efficient in P acquisition and utilization may greatly increase the efficiency of applied P fertilizers and reduce the environmental degradation as well as input cost. Hence, exploitation of genetic variations for increased P efficiency can sustain agricultural productivity in low P environments. Categorization/classification of crop cultivars on the basis of their growth performance under nutrient stress conditions is a pre-requisite of any breeding programs for the improvement of P efficiency in any crop. This selection will in turn be helpful in identifying genotypes suitable for cultivation on soils having different P status. Classification of existing germplasm would also help in selection of parents for recombination breeding to develop P efficient cultivars (Kang et al., 1998; Gill et al., 2004). Kosar et al. (2003) and Aziz et al. (2005) classified wheat and rice cultivars on the basis of dry matter and P use efficiency into four groups viz i) efficient and responsive, ii) efficient and non-responsive, iii) inefficient and responsive and iv) inefficient and non-responsive following Fageria and Baligar (1993). They proposed that efficient and responsive cultivars can be cultivated on soils with varying levels of P supply. But the division between efficient and inefficient or between responsive and non-responsive cultivars is not very sharp as it is based only on population mean. A cultivar with a minor difference from mean value may be classified as responsive (if more) or non-responsive (if less). Hence this classification may not be more useful while screening germplasm on a large scale. Recently Gill et al. (2004) used metroglyph for classification of wheat cultivars on the basis of different growth and yield parameters. The classification proposed by Gill et al. (2004) made nine different categories in place of four made by Aziz et al. (2005) for rice and by Kosar et al. (2003) for wheat. They made three categories each of efficiency and responsiveness viz high, medium and low (efficient or responsive). Hence difference between low and high efficient or responsive cultivars was significant as a wide range of medium cultivars existed between these two extremes.
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Brassica is known to utilize P more efficiently than most of other crops mainly by increased exudation of organic acids in rhizosphere (Hoffland, 1992; Akhtar et al., 2008). The present experiment was conducted to categorize 16 Brassica cultivars for P acquisition from phosphate rock.
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MATERIALS AND METHODS The experiment was conducted under natural conditions in a rain protected wire house at Institute of Soil & Environmental Sciences, University of Agriculture, Faisalabad, Pakistan. Faisalabad is situated at latitude 31◦ 02 to 31◦ 45 north and longitude 72◦ 50 to 73◦ 22 East. The temperature of wire house varied from a minimum of 9◦ C to a maximum of 22◦ C with a mean value of 14◦ C. Relative humidity in greenhouse ranged from 45% to 85% at day and night, respectively. Light intensity varied between 300 and 1400 µmol photon m2 S−1 depending upon day and cloud conditions during the growth period. Seeds of 16 Brassica cultivars (Table 1) were sown in polyethylene coated iron trays containing washed river-bed sand. One week after germination, uniform seedlings were transplanted in foam-plugged holes of thermopore TABLE 1 Mean and standard error of shoot dry matter, root dry matter and root:shoot ratio of 16 Brassica cultivars grown with phosphate rock (PR). Plants were grown for 40 days in nutrient solution with PR or mono ammonium phosphate (MAP) as P source
S. No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 F value
Shoot dry matter (g/plant)
Root dry matter (g/plant)
Root:shoot ratio
Cultivar
RP
MAP
RP
MAP
RP
MAP
B.S.A. Toria Toria Selection Brown Raya Peela Raya DG L Dunkeld KS-74 Rainbow Shiralle CON-1 Poorbi Raya Raya Anmol RL-18 BARD-1 19-H
0.25 ± 0.04 0.16 ± 0.03 0.31 ± 0.0 0.54 ± 0.03 0.47 ± 0.03 0.80 ± 0.06 0.96 ± 0.08 1.08 ± 0.08 1.21 ± 0.05 0.29 ± 0.07 0.80 ± 0.11 1.27 ± 0.10 0.92 ± 0.04 1.10 ± 0.09 0.95 ± 0.05 0.63 ± 0.08
1.54 ± 0.18 1.22 ± 0.10 1.09 ± 0.13 1.90 ± 0.23 0.61 ± 0.13 1.53 ± 0.11 1.49 ± 0.16 2.23 ± 0.15 1.53 ± 0.03 1.19 ± 0.29 1.12 ± 0.21 2.86 ± 0.33 2.09 ± 0.23 2.56 ± 0.39 2.23 ± 0.16 1.00 ± 0.12
0.03 ± 0.01 0.02 ± 0.002 0.04 ± 0.01 0.07 ± 0.004 0.06 ± 0.004 0.10 ± 0.01 0.11 ± 0.01 0.12 ± 0.01 0.11 ± 0.01 0.03 ± 0.01 0.11 ± 0.01 0.12 ± 0.01 0.08 ± 0.01 0.13 ± 0.01 0.11 ± 0.01 0.08 ± 0.01
0.18 ± 0.02 0.10 ± 0.01 0.08 ± 0.01 0.14 ± 0.02 0.11 ± 0.01 0.19 ± 0.02 0.14 ± 0.02 0.25 ± 0.03 0.09 ± 0.00 0.09 ± 0.02 0.15 ± 0.01 0.24 ± 0.02 0.17 ± 0.02 0.24 ± 0.01 0.15 ± 0.02 0.14 ± 0.02
0.13 ± 0.02 0.14 ± 0.05 0.11 ± 0.01 0.14 ± 0.01 0.13 ± 0.01 0.13 ± 0.01 0.11 ± 0.01 0.11 ± 0.01 0.12 ± 0.01 0.12 ± 0.02 0.14 ± 0.02 0.10 ± 0.01 0.09 ± 0.01 0.12 ± 0.01 0.12 ± 0.01 0.12 ± 0.00
0.12 ± 0.02 0.08 ± 0.01 0.07 ± 0.00 0.07 ± 0.01 0.25 ± 0.08 0.13 ± 0.01 0.09 ± 0.01 0.11 ± 0.01 0.06 ± 0.00 0.09 ± 0.02 0.17 ±0.05 0.09 ± 0.01 0.08 ± 0.01 0.10 ± 0.01 0.07 ± 0.01 0.14 ± 0.01
C = 16, P = 233, C × P = 4.69
C = 21, P = 243, C × P = 5.72
C = 2.93, P = NS, C × P = 1.82
C = cultivars, P = Phosphorus sources and C × P = interaction between cultivars and P sources.
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sheets floating on continuously aerated nutrient solution in polyethylene lined iron tubs. The solution contains 6 mM nitrogen (N), 3 mM potassium (K), 2 mM Calcium (Ca), 1 mM magnesium (Mg), 50 µM chloride (Cl), 25 µM boron (B), 2 µM manganese (Mn), 2 µM zinc (Zn), 1 µM copper (Cu), 0.05 µM molybdenum (Mo), and 50 µM iron (Fe). Two P sources, i.e., phosphate rock (PR) as insoluble P source (powdered form) and monoammonium phosphate (MAP) as a soluble P source, were used to maintain 0.2 mM P (total P) in nutrient solution. The PR used in the experiment contained 27% of total P and 0% of soluble P. There were five replications for each genotype in each treatment. Plants were harvested 40 d after transplanting. They were washed in distilled water and blotted dry using filter paper sheets and separated into shoots and roots before air drying for 2 d. The samples then were oven dried at 75◦ C in a forced air driven oven for 48 h to record dry weight yield (g plant−1). Dried samples of shoots and roots were finely ground in a mechanical grinder (MF 10 IKA-Werke, Staufen, Germany) to pass through a 1 mm sieve and mixed uniformly. A 0.5 g portion of plant sample was digested in diacid mixture of nitric acid and perchloric acid (3:1) at 150◦ C (Miller, 1998). Phosphorus concentration in shoot and root digest was determined by vanadate-molybdate colorimetric method (Chapman, 1961) using UV-visible spectrophotometer (Shimadzu, Kyoto, Japan). Cultivars were grouped into three classes on the basis of varietal mean (µ) and standard deviation (SD) for seven parameters (Gill et al., 2004). These classes were low (µ−SD to < µ+SD), and high (>µ+SD). These classes were assigned the numerical value as index score for each parameter as 1 to low, 2 to medium and 3 to high. Relative biomass production by Brassica cultivars grown with PR compared to MAP was calculated by using following formula. Relative dry weight production(%) = 100 × (DWPR /DWMAP ) DWPR is dry weight of shoot or root of plants grown with PR and DWMAP is dry weights of shoot or root of plants grown with MAP. Phosphorus contents (mg P plant−1) were calculated in root and shoot by multiplying P concentration in the respective tissue with its dry weight and on whole plant basis by adding up shoot and root P contents. Phosphorus utilization efficiency was calculated by the following formula (Siddiqi and Glass, 1981). Phosphorus Utilization Efficiency = Dry weight of shoot / Shoot P concentration The data were subjected to statistical treatments using computer software MS-Excel(Microsoft, Redmond, WA, USA) and MSTAT-C (Michigan State
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University, East Lansing, MI, USA) following the methods of Gomez and Gomez (1984). Completely randomized factorial design was employed for analysis of variance (ANOVA). Least square method of regression/linear correlation was used to calculate regression and correlation coefficients among different parameters. RESULTS
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Biomass Production Cultivars differed significantly both for absolute as well as relative values (% of maximum potential for these parameters) of shoot dry matter (SDM), root dry matter (RDM) and root: shoot ratio of plants grown with PR and MAP (Table 1). Biomass produced by the cultivars grown with PR was significantly (P < 0.01) lower than those grown in MAP treatments. Cultivars “Rainbow” and “Poorbi Raya” produced SDM > 1.10 g plant−1 and gained maximum index score (3) when grown with PR (Table 2). Cultivars ‘B.S.A.’, ‘Toria’, ‘Toria Selection’, and ‘Shiralle’ gained lowest index score (1) as they produced SDM 18% of their maximum root P contents grown with MAP (Table 4). Cultivars differed significantly (P