Abstract: In this study, the statistical analysis of manganese contents for soil, leaf and grain samples of the wheat plants, Triticum spelta, in the Cukurova Region of Adana in Turkey was performed to determine the relationship among the variables and correlation coefficients of manganese (Mn) contents. The soil samples were taken from the plant rhizosphere. Leaf samples at the stem elongation time and grain samples at the physiological maturity stage were analysed for Mn contents. The Mn contents of soil (MnS) were between 1.47 and 3.80 mg kg-1, but the MnS of some samples were measured below the critical level of soil (1.00 mg kg-1). Whereas Mn contents of leaves (MnL) were obtained between 47.55 and 126.40 mg kg-1. The Mn contents of grain (MnG) were obtained between 20.16 and 49.08 mg kg-1. Direct correlation was found between MnL and MnG. But indirect correlations between was found MnS and MnG. Correlation between MnL and MnG was significant at the 0.01 level according to statistical analysis.
INTRODUCTION
Many elements of the periodic table are trace elements. Although some trace elements are essential for life, some of them have toxic effects in high concentrations. The chemical composition, behaviour of plant nutrients and heavy metals in soil depend on chemical properties and composition of the soil matrix, so the variation of composition in the soil matrix may lead to significant variation of composition and behaviour of soil nutrients and heavy metals. The distribution of a specific element or a micro element in the solid phase is important for controlling its initial rate of leaching. Elements adsorbed on particle surfaces will be more readily accessible to the soil solution (Zhang et al., 2003).
As staple crops contribute substantially to daily caloric intake among people in developing countries, there has been a resurgence of interest in addressing human malnutrition through breeding of staple crops, specifically to address micronutrient malnutrition (Gregorio et al., 2000; Long et al., 2004).
The recent studies showed the important role of micro elements in human and plant nourishment. The studies made especially on zinc point out that the problem of zinc deficiency is in serious condition in Turkey. Insufficient content of micronutrient elements in soil has a negative impact on the development of crops, which, in turn, affects human health. Micro element deficiencies like zinc and iron resulted in some serious health problems especially in children at developmental age. In this respect, micronutrient elements exhibit a profound significance for the condition of human health as much as they do for a successful production of crops.
Manganese, an essential trace element, is often applied to agricultural and horticultural crops. There are very little studies about Mn in the Turkey. The objectives of this study was to determine the soil Mn content of wheat production field in Cukurova region was to assess effects of MnS, on MnL, MnG and 1000 kernel.
MATERIALS AND METHODS
Description of the area: Cukurova Region is one of the most important
agricultural areas of Turkey (Fig. 1). The area is characterized
by xeric climate.
| Fig. 1: | The study area in Cukurova Region |
The average amount of annual rainfall is 67.08 cm and potential total evaporation is 153.60 cm. The mean annual air temperature is 19.1°C. The mean annual soil temperature at 50 cm depth is 20.8°C. All the soils are xeric moist regime. The vegetations in the study area are grasses, cereal and leguminous crops. The vegetation was dominated by cereal and leguminous grasses. Wheat, cotton, maize, grape and soybean have been commonly growing in Cukurova Plain as industrial crops in Turkey.
Laboratory experiments and data analysis: In this study, 30 leaves samples, 30 grain samples and 30 soil samples in 2006 were collected to research from wheat (Triticum sp.) fields in Cukurova Region of Turkey. Plants were sampled during growing (heading) to determine MnL (Manganese in leaf). Grain samples were taken in the harvest season to determine MnG. Soil samples collected from 0-30 cm from roots region for laboratory analysis and dried with air to pass under screen (-2 mm). The particle size distribution of soil samples was determined by the pipette method (Xu et al., 2001). The pH was measured on saturation extracts (Radiometer PHM 82 standard pH meter). Organic C was measured by using a modified Walkley-Black procedure (Chan et al., 1995). Carbonate content was determined by the Scheibler calcimeter method (McKeague, 1978). Cation-exchange capacity was measured with Mg saturation followed by NH4 substitution (Nelson and Sommers, 1996). Available P2O5 analysis was carried out by Olsen (Olsen and Sommers, 1982). Extractable Mn by the citrate dithionite-bicarbonate method was carried out by Olsen et al. (1954). The results were evaluated using correlation matrix and correlation graphics. For the purpose of data analysis, the SPSS 11.0 statistical software which offer a choice of correlation were used statistical analysis.
RESULTS AND DISCUSSION
Some chemical properties of soils: CaCO3 and organic
matter content of soil samples were between 16 and 21% and 1.46 and 2.33%,
respectively (Table 1). The CEC values changed between
21.24 and 38.02 cmol kg-1. Soil pH of samples changed between
7.50 and 7.99 for all measurements. The lowest utilizable P2O5
content was observed as 16 kg ha-1 in all samples. The highest
amount of utilizable P2O5 was measured in sample
6 as 179 kg ha-1 while the amount of utilizable P2O5
changed between 16 and 179 kg ha-1. It is believed that the
excess amount of utilizable P2O5 in soil was caused
by overdose application of fertiliser (Irmak et al., 2007). The
optimum amount of soil P2O5 content to provide favourable
growing condition for plants is about 80 kg ha-1. The excess
amount of utilizable P2O5 content seems to have
a negative effect on other microelements uptake from soil such as Fe,
Mn, Mo, Cu, B, Zn, Cl, Na, Co, V and Si (Cakmak et al., 1997; Long
et al., 2004).
| Table 1: | Physico-chemical properties of soil samples (Irmak et al., 2008) |
Manganese contents of soils: Manganese contents of soils (Table 2) showed that Mn contents of soil were low ranging from 1.47 to 3.80 mg kg-1. Mn contents of all soil samples were appeared to be lower than Mn critical level being 4.00 mg kg-1. The sample 5 have had the lowest amount of Mn content being 1.47 mg kg-1 and the sample 20 have had the highest amount of Mn content being 3.80 mg kg-1. The high Mn content may be associated with chemical composition of parent material. The fields of the region were crossed with irrigation channels and connected with Seyhan River which was originated from Toros Mountains in Turkey. Therefore, the high Mn content of plants may be associated with irrigation waters. Ozturk (1997) mentioned considerable manganese sources located in Toros Mountains (Northern of Cukurova Plain, Turkey). Also, it is known that soil parent material and irrigation waters have an effect on chemical properties of soil such as pH, salinity (EC), Cation Exchange Capacity (CEC), Organic matter, Carbon to Nitrogen ratio (C/N) (Sahin and Nakiboglu, 2006; Irmak et al., 2007).
Manganese contents of leaves: Mn contents of leaf samples (Table 2) showed that Mn contents were varied between 47.55 and 126.40 mg kg-1. Mn contents of leaves were appeared to be higher than critical level being 40 mg kg-1. MnL content of sample 30 was determined as the lowest value (47.55 mg kg-1). On the other hand, MnL content of sample 4 was determined as the highest value (126.40 mg kg-1). There was a very applicable correlation between MnL and MgG when statistically data reduction applied on the measured values (Fig. 3). The best correlation coefficient was R2= 0.81 (R= 0.90). Also, correlation coefficient was increased from 0.61 to 0.90, statistically when sample size was 22 (Fig. 2, 3).
Manganese contents of grains: MnG of the samples (Table
2) showed that the amount of MnG samples varied between 20.16 and
49.08 mg kg-1. The sample 30 contained the lowest amount of
Mn content with the maximum kernel weight (54.80 g). But, the sample 4
contained the highest amount of Manganese (49.08 mg kg-1).
While there was an inverse relation between MnL and soil samples, there
was a direct relation between MnG and MnL, respectively (Fig.
2, 3).
| Table 2: | Manganese content of soils (MnS), leaves (MnL) and grains (MnG) |
| *Because of data reduction, the pointed values were not used (Fig. 3) | |
| Fig. 2: | General variations or correlations between MnS, MnL and MnG |
| Fig. 3: | The variation between MnL and MnG after statistical data reduction |
Also, correlation between MnG and MnL is significant at the 0.01 level
according to statistical analysis (Table 3). It means
that there are very suitable distributions between MnG and MnL.
| Table 3: | The correlation matrix for MnS, MnL and MnG |
| *Correlation is significant at the 0.05 level (2-tailed), **Correlation is significant at the 0.01 level (2-tailed) | |
Also, it shows that the plant can took the manganese as a microelement from another source. It should be concluded that the irrigation water of Seyhan River in Cukurova plain may consist of some micro elements or trace minerals. Table 2 showed that MnL contents were very high with maximum variation limits, but Mn contents of soils were very low values with minimum variation limits. The biggest standard deviation was observed for MnL data.