a. a. moosavi

Understanding the particle size distribution (PSD) is of great importance for plant growth and soil management. In recent years, the science of soil has witnessed a significant increase in digital soil mapping (DSM) activities. In this regard, machine learning models (ML) have emerged as an alternative and tool for DSM, which are mainly used for data mining and pattern recognition purposes, and are now widely used for regression and classification tasks in all fields of science. Hence, this study was undertaken to spatially model sand, silt, and clay particles utilizing machine learning models such as Random Forest (RF), Support Vector Regression (SVR), and the Co-Kriging geostatistical model. Additionally, auxiliary variables with high spatial resolution were incorporated into the analysis. This investigation was conducted in a section of the Marvdasht plain, located in Fars province.

The present study was conducted in a part of Marvdasht plain located between 35.82´41°52' to 1.07´57°52' east longitude and 35.02´48°29' to 14.72´2°30' north latitude, and 40 km north of Shiraz with an area of about 50,000 hectares. After determining the study area boundaries, the positions of 200 sampling points were determined using the R software and the conditioned Latin hypercube sampling method. In other words, for soil feature modeling, 200 samples were taken from two depths of zero to 30 and 30 to 60 centimeters in the study area. Then, the samples were transferred to the laboratory, dried, and passed through a 2 mm sieve. Finally, the soil texture components were measured by the hydrometer method. The environmental variables used in this study are a wide range of representatives of soil-forming factors that were prepared as much as possible from sources with minimum cost and high accessibility. In total, 75 environmental variables were prepared, and the raster format related to all environmental variables, including 39 elevation and altitude variables and 36 remote sensing measurement variables, was extracted. Finally, the factor-tuning inflation variance and Boruta algorithm were used to select the optimal variables.

The minimum amount of clay was measured at 10.21% and 10.45%, respectively, and the maximum amount was 32.65% and 36.35% at the surface and subsurface depths. The average amount of clay in all samples was 37.91% and 35.61%. The average amount of sand was measured at 25.65% and 26.02% at the surface and subsurface depths, respectively. The maximum amount of sand was observed in the northern and higher parts of the study area and was equal to 54.68% and the minimum amount was predicted in the low-lying areas of the study area. Low-lying areas and sedimentary plains in the central part of the study area contained high amounts of silt. Four depth variables valley depths (VD), texture (TE), topographic wetness index (TWI), and clay index (CI) related to geomorphometric parameters and the normalized difference vegetation index (NDVI) variable related to remote sensing indices were selected as optimal variables. The RF model with R2 of 54.0% and 36.0% for predicting sand, 48.0% and 64.0% for predicting silt, and 52.0% and 49.0% for predicting clay at both surface and subsurface depths performed better than the SVR and Co-Kriging models. The most effective variable in predicting the spatial distribution of soil particles was VD with relative importance of 60% and 65% for predicting sand at the surface and subsurface depths, 70% for predicting silt at the surface depth, and 70% and 65% for predicting clay at both surface and subsurface depths, respectively. Only TE and TWI variables were more important than VD for predicting silt at subsurface depth. These results show that topographic variables are effective in the spatial variation of soil particles. Unlike clay, the highest amount of sand in both depths was observed in the northern part and the highest part of the study area, and the lowest amount was predicted in the low-lying areas of the study area.

In general, with the aim of this research, maps of the spatial distribution of soil texture components were prepared at both surface and subsurface depths using machine learning and geostatistical approaches along with environmental covariates in a part of Marvdasht plain. Among the selected environmental covariates, topographic attributes, especially the valley depth (VD), had the highest effect in justifying the spatial prediction of soil texture components. Also, the results of comparing the performance of machine learning models supported the higher efficiency of the RF model than other models. Therefore, the approach used in this study to prepare a map of soil texture components can be useful as a guide for mapping useful soil features in areas with similar climatic and topographic conditions.

Soil erosion is one of the most important and serious threats to food security and as a consequence of human life. In order to perform soil protection activities against soil erosion, knowledge about the amount of soil loss tolerable is very important. In fact, the soil loss tolerable is the potential for soil erosion, loss of productivity and lost production, and the final criterion for controlling soil erosion and degradation of land. Soil thickness methods, particularly Skidmore equation, based on their ability to estimate the tolerable amount of soil loss have been widely used. In the mathematical function developed by Skidmore based on soil thickness, the soil loss tolerable is calculated based on the soil's current depth, the lowest and maximum soil depth for sustained growth of crops, and the upper limit of tolerable erosion in accordance with the environment. Since the determination of soil loss tolerance by soil thickness method and the Skidmore equation requires time, cost and energy, the researchers have tried to estimate the soil tolerance is supported by regression methods using pedotransfer functions and easily available soil properties. Therefore, the present study was carried out with the aims of determining the tolerable tolerance of soil loss by thickness method and the development of regression pedotransfer functions for estimating this property in the upstream of the dam.

The study is place on Kamfiruz Watershed with an area of 422 km2, an average annual precipitation of 443 mm and an average annual temperature of 14 °C. It is closed to the Dorudzan Dam sub-basins and is considered as one of the five parts of Marvdasht plain in Fars province. For this work, 60 soil profiles were excavated by excavating machine. In addition to measuring the depth of soil, some physico-chemical soil properties were measured from the surface layer (0-30 cm) including; soil texture, organic matter, salinity, percentage calcium carbonate, mean weight diameter in the laboratory and filed. In order to develop regression models for estimating the tolerable soil loss, information from 60 soil profiles was divided into two data-sets. One set of the data with 42 samples (70% of whole samples) was used for developing the models and another set of the data with 18 soil samples (30% of whole samples) was used for validation. Multiple linear regression was used to develop the linear models. The same soil properties used in the multiple regression method were considered as inputs in the tree regression method to estimate the tolerable amount of loss.

The results showed that the minimum and maximum Z1 parameters (the lowest soil depth for stable growth of crops in the study area) were considered as 0.25 and 0.51 m based on the current depth of soil. Organic matter of the soils with the highest standardized coefficient (Beta = 0.44) and the highest correlation (-0.77) with soil loss tolerance was the most important soil properties for estimating the soil loss tolerance. In the regression model, only the coefficients of four characteristics of permeability, soil aggregate stability, pH and organic matter appeared among the soil grazing characteristics and entered into the model. Based on the evaluation statistic, tree regression method with the highest determination coefficient in both calibration data sets (R2 = 0.96) and validation (R2 = 0.78) and the lowest error value in the validation data (RMSE= 0.29 ton ha-1 year-1) and validation (RMSE = 0.125 ton ha-1 year-1) were more efficient than the multiple regression method in estimating the tolerable soil loss.

Soil loss tolerance was estimated using regression methods (multiple linear regression and regression tree) in Doroudzan Watershed, Fars province. The soil loss tolerable determined using Skidmore method, was 1.04 tons per hectare per year ranging from 0.29 to 2.25 ton ha-1 year-1. The soils of this area are slightly deep and their depth varies from 0.4 m in the marginal areas in the upstream parts of the catchment area of the dam and the slope of mountain up to 2 meters in the center of the plain with agricultural lands uses. In general, the tree regression method had a better performance than linear regression method for estimating the soil loss tolerance based on the statistical indices.

The effect of zeolite as a soil conditioner that is used for improving physico-chemical soil properties, improving nitrogen use efficiency, and decreasing nitrogen losses has not been studied on leaching of nitrogen from different sources. Therefore, this study was conducted as a factorial greenhouse experiment using a completely randomized design with 3 replications. The objective was to evaluate the effect of 4 levels of zeolite (0, 15, 30 and 45 g zeolite kg-1 soil) on leaching of nitrogen from different nitrogen fertilizers (control and application of 150 mg N kg-1 soil from urea, ammonium sulfate and nano- N- fertilizer) in a calcareous soil under Ocimum basilicum (var. Green Ardestani) planting. At 4 stages, the leachate of experimental pots was collected and nitrate concentration was determined. After harvesting, ammonium, nitrate, and total nitrogen concentrations of postharvest soils were also determined. Application of 15, 30 and 45 g zeolite kg-1 soil increased ammonium concentration of soil by 16%, 13%, and 22 %, and nitrate concentration by 50%, 130%, and 170 % as compared to control, respectively. Application of 30 and 45 g zeolite kg-1 soil increased total nitrogen concentration by 42% and 28 %, respectively. Among the applied levels of zeolite, only application of 45 g zeolite kg-1 soil significantly decreased nitrate concentration in leachates at different stages. The amount of ammonium, nitrate, and total nitrogen were the highest for soils that received nano-N- fertilizer. Furthermore, nitrate concentration in leachate at different stages was the least when soils received nano-N- fertilizer. In general, zeolite increased nitrogen retention from the studied fertilizers and resulted in lower nitrate leaching through soils. Among the studied treatments, application of 45 g zeolite kg-1 soil and using nano- N- fertilizer were the most effective in nitrogen retention and decreasing nitrogen in leachate. Therefore, it is recommended that these treatments be used in field conditions if complementary field trials confirm the results of this greenhouse experiment.

Soils contaminated with heavy metals such as cadmium (Cd), mainly are poor in nutrients and microbial population. Water deficit stress can deteriorate the situation for healthy plant growth. Application of plant growth promoting rhizobacterium as bio-fertilizer can influence the availability of nutrients and improve the plant growth and health. For this reason, a greenhouse factorial experiment was conducted in a completely randomized design with three replications. Treatments consisted of two levels of Micrococcus yunnanensis bacterium (with and without bacterium), four levels of Cd (5, 10, 20, and 40 mg kg-1), and three levels of soil moisture regimes (100, 80, and 65% of field capacity). Results showed that increasing soil Cd contamination, resulted in reduction of shoots dry weight and total manganese (Mn) and zinc (Zn) uptake, while the soil inoculation with bacterium moderated the negative effects of Cd on the plant by increasing shoots dry weight and total Zn uptake. The main effect of water deficit stress on the shoot dry weight, and the uptake of iron (Fe), Mn, Zn, and copper (Cu) were significant and reduced these traits while the soil inoculation with bacterium increased shoot dry weight and uptake of Fe and Zn and mitigated negative effects of water deficit stress.

Drought and its resulting stress is one of the most important common environmental stresses that limit agricultural productions. In order to evaluate the effect of cattle manure biochar on the growth, yield, and water use efficiency of spinach at different soil moisture status, a factorial completely randomized design with 3 replications was conducted under greenhouse conditions during October 2014 to January 2015. Treatments consisted of four biochar levels (0, 1.25, 2.5 and 5% wt of initial soil) and three soil moisture levels (FC (without stress), 0.7FC, and 0.55FC). To compensate the water losses via evapotranspiration, the pots were weighted every day and water stress was imposed by adding the water required in each treatment. Total water consumption during the growing season was also determined. Results indicated that application of both soil water stress levels resulted in significant reduction in leaf area, stomatal conductance, water consumption, and fresh and dry weight as compared to those of the controls (without water stress and biochar application). The greenness index significantly increased by 14%, 14%, and 11 % as compared to that of the control when soil moisture level of 0.55 FC was applied at the first, second, and third growth stages (40, 55 and 70 days after planting), respectively. Application of biochar also significantly increased greenness index, leaf area, and stomatal conductance as compared to that of the control. Soil moisture stress up to 0.7FC decreased the plant water consumption; however, it did not affect the water use efficiency, significantly; while water stress level of 0.55 FC decreased water use efficiency significantly. In general, application of 1.25 biochar (25 ton/ha) as compared to the control decreased the negative effects of water stress on plant (reducing leaf area, fresh and dry weight, etc.) and improved plant growth indices and increased the growth of plant at all of the applied water stress levels. Therefore, in order to reduce water consumption and improve the growth and yield of plants, biochar application, especially under drought stress conditions or in greenhouse conditions, is recommended. Meanwhile, performing such an experiment under field conditions is also suggested.

The 0.4 ° C increment in earth’s average temperature from 1975 to 2000 has certified the researchers that the earth global warming has been started. Atmosphere will enable to hold water vapor up to 6 percent, just by 1 ° C rising in the temperature. This matter provides more deficiency of available fresh water for earth residents. These changes and climate system instability make the widespread and unexpected changes in the earth’s environment. The increment of El Niño events from the mid-eighties of the twentieth century and the occurrence of “heat island effect” in many urban areas, will follow by increasing 4 to 5 ° C in heat temperature. Any changes in the world’s climate can create a wide range of human health. The involvement of large human populations in abnormal situations by extreme weather events, and their encounter with risk of heat stress, lack of water and improper nutrition lead them to adverse changes in physiological condition and increased risk of chronic and serious diseases such as diabetes. The need to avoid from adverse conditions has been caused the influx of rural to urban and their adoption of modern industrial life. Cities high population, the formation of crowded slums and suburbs without suitable facilities, inadequate or improper nutrition, lack of urban infrastructure such as adequate green space, public transport systems, health facilities, direct and indirect contamination of air, water and resources, lack of physical mobility considered as the consequence events of this inauspicious migration. These are all destructive factors for activation of undesirable biological pathways and potential diabetes formation. In this paper, these factors and their impact on the population of diabetic patient were surveyed and discussed in details.

The present study investigated the possibility of replacing salamon with modified shotor diluent (MSD) and egg yolk (EY) with low density lipoprotein (LDL) for chilled storage of ram semen. Good quality semen (>80% progressive forward motility (PFM) of sperm) from 3 fertile rams was collected using an artificial vagina and pooled for each experiment. Low density lipoprotein was extracted from fresh EY. In experiment 1, semen was divided into 2 fractions and extended in MSD or salamon. In experiment 2, semen was assigned into 5 fractions and extended in MSD supplemented with 12 and 15% EY or 3, 5 and 8% LDL. In experiment 3, semen was divided into 2 fractions and extended in MSD supplemented with 12% EY or 5% LDL. Viability of sperm was assessed at times 0 (immediately after semen dilution), 2 or 4 (at 4°C) and up to 72 h after semen dilution. Data was analyzed using General Linear Model (GLM) procedure, including repeated measures. In experiment 1, the viability of sperm was similar in two diluents (P>0.05). In experiment 2, PFM of sperm was similar among groups at the time of dilution (P>0.05); but remained elevated in 5 and 8% LDL compared to other groups afterward (P<0.05). In experiment 3, PFM of sperm was superior at 48 and 72 h after dilution in 5% LDL compared to 12% EY (P<0.05). In conclusion, MSD supplemented with 5% LDL is a suitable diluent for ram fresh semen preserved at 4°C for 72 h.

Convergence of knowledge and studies carried-out in different fields including those of methods and research findings constitute the nature of science. Interdisciplinary studies refer to those that are done in subject matters that make use of a number of distinctive scientific fields toward solving a common problem that also leads to development in science and introduction of new theories. To improve the quality as well as the level of our scientific knowledge, researchers must propose logical models combined with comprehensive rational that can be used towards advancement of research and scientific knowledge. The most successful methods applied in numerous scientific fields as well as in integrative sciences, have been those that deal with the natural phenomena. God has created the nature along with realm of knowledge, science and wisdom that are aimed to meet the real needs of humans and other creatures. Therefore, a good model is the one that would be aimed towards convergence of sciences and for knowledge development, leading to identification of natural phenomena and their subsequent mapping into real-world observations, that is called biomimetic science. Knowledge of basic and cognitive sciences as well as wisdom are required to identify the underlying laws of nature and the pattern of natural phenomena. The interdisciplinary sciences and worldwide knowledge are needed in order to be able to identify the unknown phenomena in nature and the world around us using intellectual tools, measurement devices, differentiable tests and various scientific methods. This would then lead to defining concepts and mechanisms of creation as well as development and understanding the laws governing the observed or discovered phenomena. Basic and cognitive sciences discuss questions such as “why” and “how” of phenomena and their relations whereby we discover the secrets and observe invisible life forces using different analysis and advanced scientific tools. As a result, theories, hypothesis, and equations can be innovated by which secrets and the complexity of natural phenomena and relations between them can be formulated and offered to the society. Advanced technologies can be generated by means of accurate identification of natural phenomena and the relations that may exist among them and finally by correctly mapping such relationships into our observations. This issue is rooted in the processes of basic and cognitive sciences and today a great share of advanced technologies is devoted towards advanced science. Hence for advancement and the growth of the country in science, innovation and technology, we need to invest in interdisciplinary sciences and wisdom knowledge as well discovery of new structures, so that we can achieve a level of high standard in science and technology in coming years. Thus, it is suggested that a nucleus of biomimetic science and technology research be formed by inviting scientists, researchers, entrepreneurs, policy makers, investors as well as the sponsors in order to plan and devise policies for the advancement of integrative science and wisdom that would be in line with natural phenomena where we can plan ways for the advancement in this science that is coherent with science and wisdom innovation system.

Organic food, the food without any drug residues and poisonous materials with therapeutic properties, has been of considerable interest by consumers worldwide. In this context, camel milk is not only considered as a food with high nutritive values but also as a food with therapeutic elements that could be used to assist the patients with some of diseases. These include, the presence of peculiar antibodies that can penetrate into the cancer tissues and the presence of insulin like molecules that could be used to treat diabetes, bioactive peptides that are produced from camel milk protein having antioxidant, antimicrobial and anti hypertension activity as well as similarity of camel milk to human milk. Bovine’s milk allergy is by far the most prevalent food allergy especially in children because of the presence of β-lactoglobulin. Camel milk lacks this protein and is enriched with α lactalbumin such as human milk. These are only a partial list of properties embodied in camel milk which is to truly a divine food.

The share of research and scientific productions in the field of life sciences in developed countries are about 55 percent which highly reflects the importance of biological sciences in the present world. Based on information extracted from «Web of Science», This paper has compared the scientific papers and the citation rate of Iran science productions with Turkey, Egypt and Germany in the field of biological sciences. This research also focuses on five scientific assessment indicators including: production of research papers and international contributions of science products in the field of life sciences, the share of research of countries from GDP, the amount of scientific documents produced by the 10 top universities, quality of publications and citations of research papers in research journals and also top subjects in the field of biological sciences. Documents analyzed form life science researches show the higher impact factors relative to any other science researches in Iran and the world. The results indicate the number of 3. 92 citations per paper in the field of science and the figure of 4. 305 citations per paper in the field of biological sciences in Iran that clearly reflects the growth of quality in biological sciences.

Science and wisdom are the two essential elements for gaining a deep and basic understanding of the phenomenon. Science and wisdom have a common window. Science opens up a way to the wisdom and wisdom makes the science blossom.To fully understand and recognize the characteristics of the things, three kinds of education are needed: general education, scientific education, and wisdom or spiritual education. In the area of scientific education, the phenomena are mostly recognized by visible forces while they are perceived and discovered by invisible forces in the area of wisdom and spiritual education. Wisdom and spiritual education is achievable through piety, purity, and innocence. An innocent self owns a light by which it can see inside the entities and discover them. Because of solidarity exists between science and wisdom, these two realms should tightly imitate to each other. For example, it is expected that a person who works in the field of pharmacy with a special focus on cognitive sciences, would first go to Biomimetics. It means that he diagnoses, in the first phase, the origin of the drug in nature, then uses that knowledge as a pattern and in the next step synthesizes the drug by imitating the nature and finally creates the natural technology. Inanimate, plant, animal, and prayer do exist in nature and they can be made into drugs and molecules. Nowadays, the science is integrating with wisdom and spiritual, it is feasible to enter them together into the realm of experimental sciences and construct advanced, molecular and natural technologies out of them.