Research Article
Soil science
Fatemeh Bibi Shahabi; Reza Khorasani; zahra gheshlaghi
Abstract
Introduction:
This study examined the influence of glutathione on iron availability in calcareous soils and its effect on the iron availability from various sources for peanut plants. Calcareous soils, prevalent in many regions, challenge nutrient availability, particularly for micronutrients such as ...
Read More
Introduction:
This study examined the influence of glutathione on iron availability in calcareous soils and its effect on the iron availability from various sources for peanut plants. Calcareous soils, prevalent in many regions, challenge nutrient availability, particularly for micronutrients such as iron, manganese, and zinc, owing to their high pH levels. Despite adequate iron levels in these soils, plant accessibility remains restricted, often resulting in iron deficiency symptoms, such as chlorosis, due to impaired chlorophyll synthesis. Various strategies, including the development of resistant cultivars, organic amendments, and mineral or chelated iron fertilizers, have been explored to mitigate Fe deficiency. Chelated iron fertilizers, especially iron sequestration (EDDHA) agents, are commonly used in calcareous soils to enhance iron availability in plants. However, their environmental impact and cost-effectiveness are concerns, prompting interest in alternatives such as iron oxides, which are cost-effective and environmentally friendly. Research suggests that iron oxides, particularly magnetite nanoparticles, support plant growth and enhance the availability of iron. Additionally, growth stimulants, such as glutathione (a tripeptide with antioxidant properties), have been investigated for their potential to alleviate iron deficiency. Glutathione not only boosts plant defense mechanisms but also improves reactive oxygen species availability. Recent studies have shown that the foliar application of glutathione in iron-deficient plants can significantly increase total iron uptake and enhance photosynthesis. This study aimed to investigate the effects of glutathione on iron bioavailability from various iron sources and growth parameters in peanuts cultivated in calcareous soils.
Materials and Methods (331 words):
The experiment was conducted in a greenhouse at the Agricultural Research Center of Ferdowsi University of Mashha and, employed a completely randomized factorial design with three replications. The factors were iron sources (control, iron sequestration (EDDHA), iron oxide, and iron filings) and glutathione foliar application (0, 1, and 2 mM, four times per growth season: 29, 38, 42, and 48, after planting). Soil was collected from a farm, and some of its physical and chemical properties were analyzed using conventional methods. Macronutrients were added at the recommended dosage to minimise interference with iron treatment. The iron levels were 0 and 50, 1.37, and 0.108 mg/kg for sequestration, iron oxide, and iron filings, respectively. Glutathione foliar treatments were applied at four growth stages (29, 38, 42, 48 days after planting) in concentrations of 0, 1, and 2 mM. The plants were grown in pots with soil moisture maintained at the field capacity. After 66 days, the plants were harvested, and parameters such as dry shoot weight, total iron uptake, and nitrogen were measured. The iron content in plants was determined using atomic absorption spectroscopy, and nitrogen was quantified using the Kjeldahl method. Statistical analyses were conducted using SAS software, and mean comparisons were performed using Duncan's test at the 5% significance level. This study aimed to assess the effects of different iron sources and glutathione on iron bioavailability and plant growth in calcareous soil conditions.
Results and Discussion
The study revealed that glutathione, either alone or in combination with iron sources, notably improved peanut plant growth and iron uptake. Iron sequestration (EDDHA) was the most effective treatment, significantly increasing dry shoot weight, particularly when combined with 2 mM glutathione. The combination of glutathione and iron treatment substantially boosted total iron uptake in both the shoots and roots of peanut plants. Notably, iron sequestration (EDDHA) with glutathione resulted in a 20% increase in shoot iron uptake and a 34.3% increase in shoot nitrogen uptake compared to glutathione treatment alone. Glutathione application also enhanced iron filings, leading to a 55.6% increase in root iron uptake by shoots and a 50.6% increase in iron concentration in shoots, as extracted by phenanthroline. The results indicated that glutathione improves and facilitates iron translocation from the roots to the shoots. Iron filings, a cost-effective iron source, showed significant results when paired with glutathione, enhancing both shoot dry weight and iron uptake. This synergy between glutathione and iron treatments suggests that iron sequestration (EDDHA) is more effective when combined with glutathione, resulting in alleviating deficiency symptoms of iron, such as chlorosis, and promoting overall growth.
Conclusion):
This study underscores the positive impact of glutathione on iron availability and growth in peanut plants grown in calcareous soils. Appliying glutathione significantly increased iron uptake in both shoots and roots, nitrogen uptake, and plant biomass. Iron sequestration (EDDHA), combined with glutathione, emerged as the most effective treatment, improving shoot iron and nitrogen uptake by 20% and 34.3%, respectively. Additionally, glutathione enhanced the efficacy of iron filings, an economical iron source, suggesting its potential as an alternative to expensive iron fertilizers. Glutathione application also reduced chlorosis and improved iron translocation from roots to shoots, supporting its role in enhancing iron nutrition in crops grown in iron-deficient soils. This study offers insights into the role of glutathione in managing iron deficiency stress and recommends further exploration of optimal application rates and effects on diverse crops and soil conditions.
Research Article
Soil science
Mahsa Hasanpour Kashani; Shokrollah Asghari
Abstract
Introduction Soil available water (SAW) is defined as the difference between field capacity (FC) and permanent wilting point (PWP). FC is the amount of soil water content held by the soil after the gravitational water was drained from the soil. PWP is defined as a minimum water content of a soil which ...
Read More
Introduction Soil available water (SAW) is defined as the difference between field capacity (FC) and permanent wilting point (PWP). FC is the amount of soil water content held by the soil after the gravitational water was drained from the soil. PWP is defined as a minimum water content of a soil which is needed for the crop survival and if the water content decreases lower than PWP, a plant wilts and can no longer recover itself. The direct measurement of FC and PWP soil water contents is very costly and time consuming; Therefore, it is useful the use of different intelligent models such as neuro-fuzzy (NF), gene expression programming (GEP) and random forest (RF) to estimate FC, PWP and SAW through easily accessible and low-cost soil characteristics. The objectives of this research were: (1) to obtain NF, GEP and RF models for estimating SAW from the easily accessible soil variables in the cultivated lands of Ardabil plain (2) to compare the accuracy of the mentioned models in estimating SAW using the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) criteria.
Materials and methods The measured data from 102 soil samples taken from 0-10 cm soil depth of the cultivated lands of Ardabil plain, northwest of Iran, were used in this study. Sand, clay, mean geometric diameter (dg) and geometric standard deviation (σg) of soil particles, bulk density (BD) and organic carbon (OC) were introduced as input variables to the applied three intelligent models for estimating soil available water (SAW). Data randomly were divided in two series as 82 data for training and 20 data for testing of models. In all models, six different input variables combinations were used; SPSS 22 software with stepwise method was applied to select the input variables. MATLAB, Gene Xpro Tools 4.0 and Weka softwares were used to derive neuro-fuzzy (NF), gene expression programming (GEP) and random forest (RF) models, respectively. One of the important steps using NF method is selecting the appropriate membership functions (MFs) and its numbers. Based on a trial and error procedure, 3 numbers of MFs and 50 to 100 optimum replications were found for the NF modeling. Also, the input MFs were chosen as “triangular”, “trapezoid”, “generalized bell” and “pi” and the output MF was selected as “constant”. A set of optimal parameters were chosen before developing a best GEP model. The number of chromosomes and genes, head size and linking function were selected by the trial and error method, and they are 30, 3, 8, and +, respectively. The rates of genetic operators were chosen according to literature studies. Various tree numbers were analyzed for choosing the best random forest (RF) method. Increasing the tree numbers beyond 100 made lower variations in the average squared error values for the SAW estimation cases. The accuracy of NF, GEP and RF models in estimating SAW was evaluated by coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) statistics.
Results and discussion The studied soils had loam (n= 53), clay loam (n= 26), sandy loam (n= 15), silt loam (n= 6) and clay (n= 2) textural classes. The values of sand (24.40 to 68.00 %), clay (3.80 to 42.90 %), dg (0.02 to 0.26 mm), σg (7.48 to 19.41), BD (1.04 to 1.70 g cm-3), OC (0.31 to 1.52 %) and SAW (5.10 to 25.10 % g g-1) indicated good variations in the soils of studied region. There were found significant correlations between SAW with BD (r= - 0.59**), clay (r= 0.56**), OC (r= 0.45**) and sand (r= - 0.44**). NF, GEP and RF models were applied to estimate SAW using six different combinations of input soil variables (sand, clay, dg, σg, BD and OC). The results of the best NF, GEP and RF models indicated that the most appropriate input variables to predict SAW were OC and BD. The values of R2, RMSE, ME and NS criteria were obtained equal 0.73, 2.51 % g g-1, 0.09 % g g-1and 0.71, and 0.76, 3.10 % g g-1, - 1.41 % g g-1 and 0.56, 0.68, 3.30 % g g-1, - 1.45 % g g-1, 0.50 for the best NF, GEP and RF models in the testing data set, respectively. Numerous investigations also showed that there are significant negative correlation between SAW with BD and sand and positive correlation between SAW with OC and clay.
Conclusion The results of three investigated intelligent models showed that OC and BD were the most important and readily available soil variables to predict soil available water (SAW) in the studied area. According to the lowest values of RMSE and the highest values of NS, the accuracy of NF models to estimate SAW was more than GEP and RF models. RF approach gave the worst estimates for SAW in this research.
Research Article
Soil science
Fereydun Nourgholipour; maryam mohammady; Hossein Mir Seyed Hosseini; Reza Soleimani
Abstract
Introduction
The cultivation area of canola (Brassica napus L.) has increased globally due to its climatic adaptability and its different growing season compared to other oilseeds. Additionally, its ability to be cropped in rotation with other plants, such as cereals, has contributed to its popularity. ...
Read More
Introduction
The cultivation area of canola (Brassica napus L.) has increased globally due to its climatic adaptability and its different growing season compared to other oilseeds. Additionally, its ability to be cropped in rotation with other plants, such as cereals, has contributed to its popularity. Canola has the largest cultivated area among oilseed crops in Iran. Proper consumption of nutrients is crucial for improving growth and increasing seed yield in canola plants. The use of sulfur as an essential nutrient, along with selenium in low concentrations as a beneficial nutrient, plays a significant role in enhancing plant tolerance to environmental stresses. Sulfur and selenium are both elements of group 16 of the periodic elements table and have similar physical and chemical properties, and it is believed that selenium utilizes the same pathways for sulfur immobilization and uptake in plants. Given the similarity of selenium to sulfur, sulfur metabolic pathways are shared, so the effect of selenium on growth is expected to be largely influenced by sulfur nutrition. This study aims to investigate the effects of sulfur and selenium application on nutrient absorption and their interaction on canola plant growth indices.
Materials and Methods
The experiment was conducted in greenhouse conditions as a factorial in a completely randomized design with 12 treatments and three replications. For cultivation, plastic pots with a diameter of 20 cm were utilized. Four kilograms of sieved soil were added to each pot. 100 mg kg-1 of nitrogen from urea source was applied in the pre-planting stage and 100 mg of nitrogen was applied in two stages (after establishment on day 21 and then in the stem elongation before flowering stage). Triple superphosphate at a rate of 80 mg of phosphorus per kg of soil was added to the pots in powder form before planting and iron at a rate of 5 mg kg-1 in the form of iron chelate solution was added to the pots. The experimental treatments included elemental sulfur fertilizer at two levels of zero and 20 mg kg-1 (inoculated with Thiobacillus inoculum), two sources of selenium fertilizer (sodium selenate and selenite) at three levels of zero, 30, and 60 μg/kg in soil form before planting. The amount of sulfur and selenium available in the soil before planting was 3.8 and 0.025 mg/kg, respectively. The cultivated canola variety was Dalgan and grown in greenhouse conditions for 5 months. This cultivar is open-pollinated. The sulfur was in powder form with a purity of 99%, which was added to the soil of the sulfur-containing treatments, along with Thiobacillus inoculum (with a population of 1×108 cells per ml) two weeks before planting. After the seed growth and maturation period (5 months), at the final stage of growth (physiological maturity with a two-digit growth code of 80), the seed components were separated from the aerial parts. The dry weight of the seed and the aerial parts of the plant were weighed separately.
Results and Discussion
Sulfur application significantly increased shoot dry weight, root dry weight, leaf area, and canola grain weight compared to conditions without sulfur application (48.8% increase in shoot weight, 28.1% in root weight, 15.7% in leaf area, and 51.3% increase in grain weight). Grain weight had a correlation of 0.94** with grain sulfur uptake and 0.9** with shoot sulfur uptake. Therefore, the growth characteristics of roots, shoots, and sulfur concentration in shoots and seeds have a significant impact on grain weight. Application of selenium from selenate source resulted in higher selenium absorption in shoots and canola grain compared to selenite source. In grain, sulfur application increased selenium absorption from both sources. Grain sulfur uptake had a correlation of -0.42** with seed selenium concentration, 0.94** with seed weight, 0.86** with shoot sulfur concentration, -0.43* with shoot selenium concentration, 0.87** with shoot sulfur uptake, 0.7** with shoot weight, 0.69** with leaf area, and 0.83** with root weight. The highest grain selenium concentration was observed at the rate of 60 μg kg-1 from selenate source (0.48 mg kg-1). If increasing the selenium concentration of the grain is desired for enrichment purposes (from 0.12 μg g-1 in the sulfur-free and selenium-free treatments), a sulfur treatment of 20 mg kg-1 and a selenate content of 60 μg kg-1 could be considered to achieve a concentration of 0.42 μg g-1. This is because the grain weight of this treatment (3.87 g pot-1) was closest to the high levels of grain weight in the sulfur treatment of 20 mg kg-1 and selenium-free condition (4.32 g pot-1).
Conclusion
Grain selenium concentrations of 0.10-0.11 mg kg-1 and sulfur concentrations of 0.325-0.33% produced suitable canola yield. The highest canola grain weight was obtained with a concentration of 19.86 mg kg-1 sulfur and 0.0267 mg kg-1 selenium in the soil.
