Soil science
Mehdi Zangiabadi
Abstract
IntroductionSoil pore size distribution curve and using the optimal ranges of the location and shape parameters of this curve can be used to evaluate the soil physical quality. This research was carried out in an area of about 220 hectares of Torogh Agricultural and Natural Resources Research and Education ...
Read More
IntroductionSoil pore size distribution curve and using the optimal ranges of the location and shape parameters of this curve can be used to evaluate the soil physical quality. This research was carried out in an area of about 220 hectares of Torogh Agricultural and Natural Resources Research and Education Station, to determine the optimal ranges for soil pore size distribution curve parameters using the soil physical quality index. Different soil textures and the diversity in soil properties are the distinct features of this research station. Materials and MethodsTorogh Agricultural and Natural Resources Research and Education Station of Khorasan-Razavi province, with a semiarid climate, is located in south-east of Mashhad city. For the field measurements and laboratory analysis to determine the soil physical properties and indices, 30 points with different soil textures and structures were selected. Intact soil cores (5 cm diameter by 5.3 cm length) and disturbed soil samples were collected from 0-30 cm depth of each point. After the laboratory analysis and field measurements, 35 soil physical properties were measured and calculated. Soil particle size distribution and five size classes of sand particles, soil bulk, and particle density, dry aggregates mean weight diameter (MWD) and stability index (SI), soil moisture release curve (SMRC) parameters, S-index, soil porosity (POR) and air capacity (AC), soil pore size distribution (SPSD) curves, relative field capacity (RFC), plant available water measured in matric pressure heads of 100 and 330 hPa for the field capacity (PAW100 and PAW330), least limiting water range measured in matric pressure heads of 100 and 330 hPa for the field capacity (LLWR100 and LLWR330), integral water capacity (IWC) and integral energy (EI) of different soil water ranges, were the soil physical properties and indices which were determined in this study. Three parameters of modal, median, and mean pore sizes of the SPSD curves were considered as the location (central tendency), and three parameters of standard deviation, skewness, and kurtosis of the SPSD curves were considered as the shape parameters. Selection of the most important soil physical characteristics using principal component analysis (PCA) method by JMP software (ver. 9.02), weighting and scoring of the selected characteristics using PCA and scoring functions, respectively, and the summation of multiplied characteristics weights by their scores for each soil sample, were the four steps of calculation of the 0-1 value of soil physical quality index (SPQI). Soil samples were classified into four soil physical quality classes by SPQI values. The soils of the first class with the highest SPQIs (> 0.78) were considered to determine the optimal ranges of SPSD curves location and shape parameters. Results and DiscussionThe texture of soil samples were loam (40 %), silt loam (23 %), silty clay loam (17 %), clay loam (13 %), and sandy loam (7 %). Soil organic carbon was between 0.26-1.05 (%), and the average soil bulk density was 1.45 (gr.cm-3). The MWD values of studied soil samples were between 0.94-2.88 (mm), an average of 1.93 (mm). The average modal, median, and mean pore sizes as the location parameters of the SPSD curves were 60.3 (μm), 12.4 (μm), and 6.5 (μm), respectively. The average of standard deviation, skewness, and kurtosis as the shape parameters of the SPSD curves were 71.56 (μm), -0.36 and 1.15, respectively. The average modal pore sizes showed that the pores with a size of 60 (μm) had the highest frequency in soil samples. The range of calculated standard deviation of SPSD curves, along with the difference between the minimum and maximum mean pore sizes (24.6 μm), implied the diversity of pore sizes in the studied soils. The results of PCA showed that the four soil physical properties of PAW330 (0.1-0.2 cm3.cm-3), PORt (0.40-0.51 cm3.cm-3), LLWR100 (0.12-0.22 cm3.cm-3) and SI (0.76-2.61 %) accounted for about 88% of the variance between soil samples and were selected to calculate the SPQIs. The PAW330, PORt, LLWR100, and SI were entered into the calculation of SPQIs with weights of 0.46, 0.31, 0.15, and 0.08, respectively. All the selected physical properties were scored using the scoring function of more is better. The maximum and minimum values of SPQIs for the studied soils were 0.84 and 0.14, respectively. Five soil samples with SPQIs greater than 0.78 were classified as class 1 with the highest physical quality. The ranges between the minimum and maximum values of the SPSD curves, location, and shape parameters of these five soils were proposed as the optimal ranges. In this regard, the ranges of 29-92 (μm), 5-16 (μm), and 2-7 (μm) were suggested for optimal ranges of modal, median, and mean pore sizes, respectively. The optimal ranges of standard deviation, skewness, and kurtosis of the SPSD curves were proposed as 22-81 (μm), (-0.38)-(-0.33), and 1.14-1.15, respectively. ConclusionThe optimal ranges of SPSD curves location and shape parameters suggested in the literature may probably not apply to a wide range of agricultural soils. They must be evaluated in a more extensive range of land uses, soil management, and soil textures. In this research, the soils with the relatively higher physical quality had larger mean pore size and less SPSD curves standard deviation (less diversity of pore size) than the optimal ranges suggested in the literature. The optimal ranges of SPSD curves location and shape parameters proposed in this research are appropriate for medium to coarse-textured soils of regions with the semiarid climate in Iran.
Soil science
B. Atarodi; M. Zangiabadi
Abstract
IntroductionToday, it is an inevitable necessity to make use of advanced and efficient technologies in order to increase productivity and gain a better economic status. Among different methods attracted the attention of researchers for enhancement in quantity and quality yield, cold plasma technique ...
Read More
IntroductionToday, it is an inevitable necessity to make use of advanced and efficient technologies in order to increase productivity and gain a better economic status. Among different methods attracted the attention of researchers for enhancement in quantity and quality yield, cold plasma technique as a modern procedure has shown a promising prospects. Despite the importance of using cold plasma in agriculture, studies have focused more on the effect of this technique on reducing microbial load in agricultural products, less on absorption of nutrients in plants. Therefore, the objectives of this experiment were to evaluate the impacts of plasma treatment of corn seeds and plasma activated water (PAW) on growth and concentration of zinc and iron in the shoots of corn. Materials and MethodsThis research was conducted as a factorial experiment based on completely randomized design (CRD) with 3 replications in a research greenhouse in agricultural and natural resources research and education center of Khorasan Razavi. The factors of experiment were three types of seed (control seeds, seeds treated with dry plasma and wet plasma), two kinds of irrigation water (distilled water and PAW) and two levels of foliar spray (without foliar spray and foliar spray with iron and zinc). Required mass of soil, was gathered, air-dried, sieved from 5 mm mesh and weighted in 6 packs. Based on the soil test values the required macro, micronutrients (except for iron and zinc) was calculated and added to the soil, and then the soil samples were moved to the pot. PLASMA BIOTEC Company located in Khorasan Razavi Park of Sciences and Technology, Mashhad, Iran performed plasma treatment of seeds and water. Plasma treated corn seeds were planted on May 18th with a density of 6 seeds in each pot. Plantlets were reduced to 2 plants after germination and establishment and irrigation was continued with desired treatments. Shoots of each pot was cut 8 weeks after sowing, 1 cm above the ground and delivered to the laboratory, where the samples were washed, dried, grounded and the concentration of zinc and iron were measured using the atomic absorption device (Perkin Elmer, 2380) in dry ash digested in 2 N HCl acid. Data were statistically analyzed by SAS statistical software (version 9.4). Comparison of means for the main effects and interactions was performed by Tukey’s test at 5 percent confidence interval. Results and DiscussionComparison of means for the interaction effects of water × seed × foliar spray showed that the minimum concentration of iron (147.67 mg/kg) was observed in plants grown from non-treated seeds, not foliar sprayed and irrigated with non-PAW (treatment 1 in Table 7). On the other hand, plants grown from wet plasma treated seeds and received foliar spray showed the highest concentration of iron regardless of irrigation water type (treatments 10 and 12 in Table 7). Comparison of means also shows that iron concentration in plants grown from dry plasma treated seeds had no significant difference with that of non-treated seeds (treatments 1 and 5 or 2 and 6). The mean comparison results for zinc concentrations showed that the minimum value was related to plants grown from non-treated seeds, not foliar sprayed and irrigated with non-PAW (treatment 1 in Table 8). The comparison of the simple effects of the type of seed on the concentration of zinc in shoots (Table 6) showed that wet plasma seeds caused a significant increase in the concentration of zinc. However, comparison of means for the interaction effects of water × seed × foliar spray showed that the effect of plasma treatment on zinc concentration was effective only in treatments that received foliar spray (comparison of treatment 2 with 10 in table 8). Based on these results the highest zinc concentration was observed in plants grown from wet plasma seeds and received foliar spray at the same time (treatment 12 in Table 8). In addition, the comparison of treatment 1 with treatment 4 and treatment 9 with treatment 2 indicates that in order to increase the concentration of zinc in plant, plasma treatment of seeds cannot replace the foliar spray method. Comparison of means for the interaction effects of water × seed × Foliar spray showed that the minimum yield was observed in plants grown from non- treated seeds, irrigated with non- activated water and not sprayed with iron and zinc solution (treatment 1 in Table 9). However, the similar treatment which grown from wet plasma treated seeds (treatment 9), showed significantly higher yield. Dry plasma, without foliar spray and without PAW (treatment 5) had no significant priority over the control. Plants grown from seeds treated with wet plasma and without foliar spray could not significantly show more iron and zinc content over the control, while their shoot yield was higher. ConclusionBased on the findings of this study, it can be inferred that irrigation with PAW and utilizing seeds treated with dry plasma exhibited no significant impact on augmenting zinc and iron content, as well as shoot yield. Conversely, wet plasma treatment, while not yielding significant enhancements in the concentration of iron and zinc within the plant, did result in increased yield. It is crucial to note that the extent of influence exerted by factors such as frequency and duration of seed exposure to plasma conditions on the observed outcomes may vary significantly. Therefore, optimizing methodology and conducting further research in this domain are imperative for a comprehensive understanding of these processes.
Soil science
M. Zangiabadi; manoochehr gorji; P. Keshavarz
Abstract
Introduction: Soil quality can be considered as a comprehensive index for sustainable land management assessment. Studying the most important soil physical properties and combining them as an index of soil physical quality (SPQI) could be used as an appropriate criteria for evaluating and monitoring ...
Read More
Introduction: Soil quality can be considered as a comprehensive index for sustainable land management assessment. Studying the most important soil physical properties and combining them as an index of soil physical quality (SPQI) could be used as an appropriate criteria for evaluating and monitoring soil physical changes. In this regard, this study was conducted to determine the most important soil physical properties and calculate the SPQI of medium to coarse-textured soils of Khorasan-Razavi province.
Materials and Methods: Torogh Agricultural and Natural Resources Research and Education Station of Khorasan-Razavi province is located in south-east of Mashhad city (59° 37' 33"-59° 39' 10" E, 36° 12' 31"-36° 13' 56" N). Soil texture variability in this research station is one of its outstanding features. The soil textures are classified into loam, silt loam, silty clay loam, clay loam, and sandy loam. More than 90% of agricultural soils in Khorasan-Razavi province are classified in these five texture classes. Using the available data, 30 points with different soil textures and OC contents were selected. The soil samples were collected from 0-30 cm soil depth at each point. Intact soil cores (5 cm diameter by 5.3 cm length) were used for sandbox measurements, and disturbed soil samples were used to determine other properties. Required laboratory analysis and field measurements were conducted using standard methods. In this research, 35 soil physical properties as total data set (TDS) including: soil moisture release curve (SMRC) parameters, particle size distribution and five size classes of sand particles, soil bulk and particle density, dry aggregates mean weight diameter (MWD) and stability index (SI), S-index, soil porosity and air capacity, location and shape parameters of soil pore size distribution (SPSD) curves, relative field capacity (RFC), plant available water measured in matric pressure heads of 100 and 330 hPa for the field capacity (PAW100 and PAW330), least limiting water range measured in matric pressure heads of 100 and 330 hPa for the field capacity (LLWR100 and LLWR330), integral water capacity (IWC) and integral energy (EI) of different soil water ranges were measured and calculated for 30 soil samples. The most important soil physical properties were selected using principal component analysis (PCA) method by JMP (9.02) software. Selected physical properties as minimum data set (MDS) were weighted and scored using PCA results and scoring functions, respectively. In this study, three types of linear scoring functions were used. The soil physical quality index (SPQI) was calculated by two scoring and two weighting methods for each soil sample and the differences between these four SPQIs were tested by sensitivity index.
Results and Discussion: Principal component analysis results showed that among 35 soil physical properties (TDS) which were studied at this research, six properties of mean pore diameter (dmean), PAW100, total porosity (PORT), EI LLWR330, SI and PAW330 accounted for about 90% of the variance between soil samples. Weight of the selected properties (MDS) was calculated by the ratio of variation in the data set explained by the PC that contributed the selected property to the total percentage of variation explained by all PCs with eigenvalue ˃ 1. In this research, the parameters of PAW100, total porosity (PORT), SI and PAW330 were scored using scoring function of more is better, EI LLWR330 was scored using scoring function of less is better and dmean was scored using scoring function of optimum by two scoring methods with score ranges of 0.1-1 and 0-1. Considering unweighted and weighted MDS and two ranges of scores, four SPQIs were calculated for each soil sample. The results showed that SPQIs which were calculated by the MDS derived from PCA method and scoring weighted MDS at the range of 0-1, had the highest sensitivity index and could represent the differences between the studied soil samples better than other SPQIs. By this method, maximum and minimum SPQI values for the studied soils were 0.82 and 0.12, respectively. SPQI is a relative comparison criterion to quantify the soil physical quality which could be applied only for the studied soils with specific characteristics.
Conclusion: The results of this research showed that minimum data set (MDS) explained about 90% of the variance between soil samples. Combining MDS into a numerical value called soil physical quality index (SPQI) could be used as a physical comparison criterion for the studied soils. From the SPQI based on the MDS indicator method, soil quality was evaluated quantitatively. Soil samples with grade I, II, III, and IV accounted for 10%, 36.7%, 30%, and 23.3% of the soil samples, respectively.
mehdi zangiabadi; manoochehr gorji; Mehdi Shorafa; Payman Keshavarz; Saeed Saadat
Abstract
Introduction: Soil physical quality isone of the most important factors affects plants water use efficiency in agricultural land uses. In the literature, some soil physical properties and indices such as S-index, Pore Size Distribution (PSD), porosity, Air Capacity (AC), Plant Available Water (PAW) content, ...
Read More
Introduction: Soil physical quality isone of the most important factors affects plants water use efficiency in agricultural land uses. In the literature, some soil physical properties and indices such as S-index, Pore Size Distribution (PSD), porosity, Air Capacity (AC), Plant Available Water (PAW) content, Least Limiting Water Range (LLWR) and Integral Water Capacity (IWC) were mentioned as the soil physical quality indicators. It has been reported that the soils with the same PAW, LLWR and IWC may have different physical qualities. The index of Integral Energy (EI) of the soil moistureranges may differ between the soils with equal soilmoistureover a defined water content range. This index is defined as the required energy to uptake the unit mass of soil moistureby plants. According to this definition, the soils with low EI would have better physical quality for plants roots growth. In this research, we hypothesized that EI of different soil moistureranges were negatively related to S-index which means the plants required energy to uptake the soil water in the soils with high S-index, is lower than the soils with poor physical quality (less S-index). So we examined our hypothesis in medium to coarse-textured soils of Khorasan-Razavi province (Iran).
Materials and Methods:This research was conducted in Torogh Agricultural and Natural Resources Research and Education Station in Khorasan-Razavi province, north-eastern Iran (59° 37' 33"-59° 39' 10" E, 36° 12' 31"-36° 13' 56" N). Soil textures of this research station, are classified into loam, silt loam, silty clay loam, clay loam, and sandy loam which is as the same in more than 90% of agricultural soils in Khorasan-Razavi province. Thirty points with different soil textures and organic carbon contents were selected. In order to measure different properties of the soil, two soil samples (5 cm diameter × 5.3 cm length core sample and a disturbed soil sample) were collected from 0-30 cm depth of each point. After conducting required laboratory and field measurements using standard methods, the Soil Moisture Release Curve (SMRC) parameters (RETC program), S-index, PAW and LLWR (measured in matric heads of 100 and 330 cm for the field capacity), IWC and EI of mentioned soil moisture ranges were calculated. In this regard, integration calculations were done by Mathcad Prime 3 software. Finally, the relationships between the measured properties and EI values (for PAW100, PAW330, LLWR100, LLWR330 and IWC) were analyzed using Pearson correlation coefficient and stepwise multivariate linear regression by JMP (9.02) statistical software.
Results and Discussion: The S-index of 30 soil samples were between 0.029-0.070 with average of 0.046. These results showed that 90% of studied soil samples had good and very good and 10% had poor physical quality. The lowest average EI values of different soil moisture ranges were observed in sandy loam and silt loam and the highest was observed in silty clay loam soil textures. The EI(IWC) mean value was lower than EI(PAW) and EI(LLWR) mean values which indicated that calculating the EI values based on continuous effects of water uptake physical limitations, resulted in lower required energy for plants to uptake the unit mass of soil moisture . Statistical analysis resulted in significantly negative relations between S-index and two indices of EI(PAW100) and EI(IWC). Multivariate regression analysis showed that EI(PAW100) and EI(LLWR100) could be estimated by shape parameter (n) of SMRC by regression coefficients of 0.95 and 0.22, respectively and the value of EI(IWC) could be estimated by S-index and organic carbon content by regression coefficient of 0.57. The parameter of saturated volumetric water content (θvs) of SMRC and sand percentage were determining factors of EI(PAW330). In this research, it was not obtained the significant relationship between EI(LLWR330) values and measured soil physical properties. According to the results, increment of the shape parameter (n) of SMRC and S-index led to reducing the plants required energy to uptake the unit mass of soil moisture in PAW100 and IWC ranges. We found that EI of different soil moisture ranges could be used to evaluate the soil physical quality between the soils with equal soilmoisture contents.
Conclusion: This Research investigated the relationship of PAW, LLWR and IWC EI values with soil physical properties and S-Index in medium to coarse-textured soils. The results indicated that increment of S-index led to decreasing EI(PAW100) and EI(IWC) indices. According to the results, the shape parameter of SMRC and S-index could be accounted for determining factors of EI(PAW100) and EI(IWC) indices values.
Mehdi Zangiabadi; manoochehr gorji; Mehdi Shorafa; Saeed Khavari Khorasani; Saeed Saadat
Abstract
Introduction: Soil is the main source of water retention and availability for plant uptake. The supplement of water is completely dependent on soil physical properties. The soils with higher values of available water are generally more productive because they can supply adequate moisture to plants during ...
Read More
Introduction: Soil is the main source of water retention and availability for plant uptake. The supplement of water is completely dependent on soil physical properties. The soils with higher values of available water are generally more productive because they can supply adequate moisture to plants during the intervals between irrigation or rainfall events. Generally according tothe spatial and temporal distribution of precipitation, Iran has an arid climate in which most of the relatively low annual precipitation falls from October through April. Thus, water deficiency along with the lack of organic carbon in the soil justifies the necessity of studying the soil, water and plant relationships that may improve the efficiency of water consumption in agricultural practices. For that reason, this research was conducted to investigate the relationship between some soil physical properties and Integral Water Capacity (IWC) index as one of the soil physical quality indices.
Materials and Methods: This study was conducted in Torogh Agricultural and Natural Resources Research Station in Khorasan-Razavi province, north-eastern Iran during 2013-2014. This station is located in south-east of Mashhad city with a semi-arid climate, annual precipitation of 260 mm and mean air temperature of 13.5 °C. The soil was classified in Entisols and Aridisols with a physiographic unit of alluvial plain that generally had medium to coarse textures in topsoil. Thirty points with different soil textures and organic carbon contents were selected as experimental plots. In order to measure different properties of the soil, two soil cores (8 cm diameter × 4 cm length cylinder for bulk density and 5 cm diameter × 5.3 cm length cylinder for sandbox measurements) and one disturbed soil sample (for other measurements) were collected from 0-30 cm depth of each plot. After conducting required laboratory analysis and field measurements using standard methods, the soil moisture curve parameters (RETC program), Porosity (POR), Air Capacity (AC), Relative Field Content (RFC) and Integral Water Capacity (IWC) index, were calculated. In this regard, integration calculations were done by Mathcad Prime 3 software. Finally, the relationship between the measured properties and IWC index were analyzed using Pearson correlation coefficient and stepwise multiple linear regression by SAS (9.1) statistical software.
Results and Discussion: Laboratory analysis results showed that the soil texture classes of samples were loam (40%), silt loam (23%), silty clay loam (17%), clay loam (13%), and sandy loam (7%). On average, very fine sand particles were dominant between five size classes of sand and the lowest values were devoted to very coarse sand particles. Soil porosity and air capacity calculation results indicated that on average bulk soil porosity (PORt) and bulk soil air capacity (ACt) were 0.46 and 0.20 (cm3cm-3), respectively. According to the results, RFC of 60% of studied soil samples were lower than 0.6, 7% were higher than 0.7 and only 33% were between 0.6-0.7 (optimal range). IWC index calculations were resulted in 0.13-0.25 (cm3cm-3) in different soil textures. The highest IWC were related to Loam and Clay Loam textures, respectively. Statistical analyses indicated that there were no significant relationship between soil particles (sand, silt and clay) and organic carbon content with IWC index. The factors of soil bulk density and RFC were negatively correlated with IWC index that means decreasing the soil bulk density and RFC would lead to the reduction of the effects of water uptake limitation factors by increasing the values of weighting functions (IWC calculations), and improvement of soil physical quality. High significant (P < 0.001) positive correlation coefficients were observed between IWC index and the factors of soil PORt, ACt and soil matrix air capacity (ACf) in this study. Multiple regression analysis results showed that IWC index could be estimated by the factors of ACt and PORt with the determination coefficient of 0.63. The partial determination coefficients indicated that ACt factor accounted for 50% and PORt accounted for 13% of IWC index variations.
Conclusion: The results indicated that in medium to coarse-textured soils, IWC index could be estimated using the bulk soil air capacity (ACt) and bulk soil porosity (PORt) factors that are derived from soil volumetric water content at saturation and field capacity points.
M. Zangiabadi; A.S. Rangavar; H. Gh. Rafahi; M. Shorafa; M. R. Bihamta
Abstract
چکیده
فرسایش خاک یک معضل برای کشاورزی در نواحی استوایی و نیمه خشک میباشد و به علت اثرات دراز مدتش بر روی حاصلخیزی خاک و کشاورزی پایدار، از اهمیت زیادی برخودار است. فرسایش ...
Read More
چکیده
فرسایش خاک یک معضل برای کشاورزی در نواحی استوایی و نیمه خشک میباشد و به علت اثرات دراز مدتش بر روی حاصلخیزی خاک و کشاورزی پایدار، از اهمیت زیادی برخودار است. فرسایش همچنین با رسوبگذاری، آلودگی و تشدید سیلابها باعث وارد آمدن صدمات محیطی میشود. این مطالعه به منظور بررسی و تعیین میزان مقاومت یا سستی خاک در برابر فرسایش آبی و همچنین تعیین عوامل تأثیرگذار بر این فرآیند انجام گرفت. اندازهگیریها در کرتهای آزمایشی مجهز به مخازن رواناب و رسوبگیر که در مراتع شمال شرق استان خراسان رضوی و با اقلیم نیمه خشک قرار داشتند، صورت پذیرفت. در این مطالعه تعداد زیادی از ویژگیهای فیزیکی و شیمیایی خاک، درصد تراکم پوشش گیاهی و شیب منطقه اندازهگیری و در نهایت رابطه این عوامل با میزان خاک فرسایش یافته بر اثر 43 رخداد بارندگی رسوبزا با استفاده از نرم افزارهای آماری بررسی گردید. رگرسیون خطی چند متغیره نشان داد که سه عامل درصد تراکم پوشش گیاهی، درصد سنگریزه درشت (75-13 میلی متر) در لایه سطحی خاک و همچنین درصد شیب زمین به ترتیب مهمترین عوامل تعیینکننده میزان فرسایش خاک میباشند. بنابراین مدیریت پوشش گیاهی و همچنین مدیریت شیب مرتع مورد مطالعه که از مراتع شاخص منطقه به حساب میآید اولین گام در جهت کاهش پتانسیل خاک منطقه نسبت به فرسایش میباشد.
واژههای کلیدی: فرسایش خاک، کرتهای آزمایشی، مرتع نیمه خشک، پوشش گیاهی، سنگریزه
