عملکرد

Knowledge about the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. Accurate mapping of SOC’s spatial distribution is a key assumption for soil resource management and land use planning. During the last two decades, the utilization of data mining approaches in spatial modeling of SOC using machine learning algorithms have been widely taken into consideration. The digital environment needs to have soil continuous maps at local and regional scales. However, such information is always not available at the required scale. Therefore, DSM approach is a key solution for quantifying and assessing the variation of soil properties such as SOC using remotely sensed indices and digital elevation model (DEM) as the most commonly useful ancillary data for soil organic carbon prediction. In this way, the data mining techniques is the pathway to create digital soil maps. Therefore, this study was carried out to compare the two common machine learning algorithms including random forest and multiple linear regressions in digital mapping of surface SOC in the Semirom County, Isfahan province. The digital maps of SOC using the two above-mentioned algorithms were also created and the most important variables affecting the distribution of SOC in the study area reported.

A total number of 200 surface soil samples (0-10 cm) were collected from the Semirom area (51º 17' - 52º 3' E; 30º 42' - 31º 51' N), Isfahan, Iran. Based on the synoptic meteorological station reports, the annual average temperature was in the range of 7.5-12.5 ▫C, the annual precipitation ranged between 350-450 mm. Soil moisture and temperature regimes are Xeric and Mesic, respectively. Then, using the Global Positioning System (GPS), sampling was done from the soil surface layer (0-10 cm). The preparation of soil samples includes air drying, pounding and softening of the collected samples performed, and then the samples were passed through a 2 mm sieve. Then, the amount of organic carbon in the samples was determined utilizing the Walkley-Black method. Also, in order to evaluate the effect of other soil properties on the organic contents of the soils, laboratory analyzes including saturated soil moisture content, soil texture, soil pH in saturated pastes, electrical conductivity of the soil saturation extracts and the calcium carbonate equivalent of the soils were measured utilizing standard laboratory protocols.In this research, auxiliary variables including terrain parameters and vegetation indices were derived from digital elevation model (DEM) and the Landsat 8 OLI satellite images employing ArcMap version 10.4.10 and SAGAGIS version 6.0.4. Then, all auxiliary layers were converted to raster format using the “raster” package and merged with each other using the “Covstack” function. Afterwards, the values of the all environmental covariates at each sampling point were extracted in a single file using the “extract” function of the “sp” package in the RStudio environment. Then, using SPSS software v.19 and the principal component analysis (PCA) method, among the 29 auxiliary variables used in this research, the most important auxiliary covariates were used in the modeling process. The dataset were then split into two groups referred to as calibration (80%) and validation (20%) subsets. Finally, SOC contents of the soils were predicted and mapped using multiple linear regression (MLR) and random forest (RF) algorithms in RStudio environment. MLR and RF algorithms were run employing “lm” and “randomForest” packages, respectively. Five different statistics was used for evaluating the performance of each model including the coefficient of determination (R2), bias, root mean square error (RMSE), nRMSE, and mean bias error (MBE).

Based on the descriptive analysis of the soil samples, soils of the study area were characterized as non-saline, alkaline, and calcareous soils. The SOC contents of the soils ranged from 0.3 % to 2.2% with the mean value of 0.89 %. The coefficient of variation for the SOC contents was 21.7%, based on which soils of the study area are classified as soils with the moderate variability considering the values proposed by Wilding (1985). The results of PCA showed that the most important auxiliary variables could be used for the modeling process are slope aspect, channels network base level, catchment slope, total curvature, height, longitudinal curvature, mass balance index, modified catchment area, slope degree, slope length, topographic position index, vertical distance to channel network, soil adjusted vegetation index, transformed vegetation index, difference vegetation index, ratio vegetation index, and general curvature.These variables explained 80% of the total variance over the study area. The comparison of the two different SOC prediction models, demonstrated that the RF model (ntree =1000 and mtry =10) with the R2, RMSE, nRMSE, and bias values of 0.79, 0.12, 0.13, and 0.002 respectively, had a better performance rather than MLR model in this study. The first five very important variables detected by RF algorithm to predict SOC contents over the study area were transformed vegetation index, ration vegetation index, soil adjusted vegetation index, and slope degree. The final map of the surface SOC distribution over the study area shows that although the estimates made by the RF algorithm have provided better estimates compared with the MLR model, but caused overestimation and/or underestimation in predicting the minimum and maximum values of the surface SOC contents, respectively.

The results of this study showed the better performance of the RF regression algorithm due to its ability to take into account the nonlinear and complex relationships between SOC contents and the environmental covariates compared to the MLR method.

Conservation tillage reduces soil erosion, but there might be a concern it that for a few years it might reduce crop yield and increase plant diseases. In order to study the effects of different tillage methods on potato yield and the severity and rate of infection of the main soil-borne diseases of potato (Fusarium wilt, dry rot and common scab), an experiment was conducted in the form of a strip plot statistical design based on completely randomized blocks with three replications, where the horizontal factor were tillage methods 1- Plowing with a moldboard plow (Conventional method), 2- Reduced tillage with a chisel plow, 3- Plowing with a disc plow and 4- Reduced tillage with a chisel packer, and the vertical factor were: collection and preservation of plant residues. The results indicated that in the first year, the highest yield of potatoes related to conventional tillage method. However, in the third year of the experiment, the highest yield of potatoes was show in obtain from reduced tillage method with a chisel packer. The effects of tillage methods on potato soil-borne diseases (Fusarium wilt, dry rot and scab) was not significant. Reduced tillage comparing to the conventional tillage method, not only did not reduce the yield of the crop and didn’t increase the soil-borne diseases of potatoes, but also caused a decrease in the field traffic, operation time and fuel consumption. The suggestion is that the reduced tillage with a chisel packer can be replaced with the conventional tillage using moldboard plow.

Soil and water salinization is a worldwide problem, especially in irrigated areas, causing decrease in crop yield and the continuous loss of arable fields. Halophytes are the natural genetic source of salt tolerance traits and can be used for revegetation and remediation of salt-affected lands, and also as an alternative crop or biofuel. Due to the limited quality of water resources in the country and considering that the major regions of Iran's area are considered to be arid and semi-arid, it is important to cultivate plants with high tolerance to environmental stresses such as drought and salinity. The quinoa (Chenopodium quinoa Willd.) plant is important because of its ability to be cultivated in saline areas and irrigated with saline water. According to previous research, quinoa is an optional halophyte, and its irrigation is possible up to sea level salinity. Quinoa (Chenopodium quinoa Willd.) is one of the plants that has outstanding economic and agronomic advantages among the crops; it is particularly important in terms of forage production. There is no reliable and accurate information about the amount of water consumption by this plant in Iran. Considering the climatic characteristics and water shortages in the country, as well as the development plan for the cultivation of this plant due to its high nutritional value, attention to its water requirement becomes more important. For this reason, the importance of precise irrigation design and planning is needed in order to improve the performance of irrigation water usage in this region.

This research is conducted aim to determine the effects of different levels of moisture and salinity on the yield, some morphological traits, and some yield components of quinoa (Chenopodium quinoa Willd.) in field conditions during two growing seasons (2020-2022) in Yazd, Iran. The experiments were carried out in a factorial experiment in a randomized complete block design, which included two irrigation water salinity levels of 5 and 12 dS/m and four irrigation levels of 60, 80, 100, and 120% to provide the amount of allowable moisture depletion (MAD equal to 50%) in the root zone, in three replications. Experimental plots were designed with dimensions of 5×7 meters. Applying the amount of irrigation was done according to the determination of the field capacity levels and the permanent wilting point moisture measured (using a pressure plate device) before the start of the experiments. In this regard, according to this information, on the day of irrigation, the amount of soil moisture in each of the plots was measured at the root zone, and based on the treatments, the amount of water required was calculated, and irrigation was applied to the determined moisture level. Irrigation was carried out in the form of flooding, and the volume of irrigation water for each treatment was controlled by the volume contour and applied separately at each interval. At the end of the experiment, quinoa was harvested in a one-square-meter grid, and then plant height, panicle length and width, and stem diameter were measured. After the plant's drying, the weight of the seeds and the weight of the whole shoot were measured in different treatments.

The results showed that the different levels of salinity and soil moisture cause significant changes in biomass yield, seed yield, and harvest index. Also, the results indicated that changes in salinity levels and moisture levels caused significant differences in plant height, stem diameter and panicle length, panicle width, and 1000-seed weight (P<0.01), but their interaction was not significant. For two levels of salinity, the maximum biomass (9.28 tons/ha) was observed by supplying 100% of the depleted soil moisture based on MAD = 50%. According to the yield-water use function, the maximum seed yield for 5 and 12 dS/m irrigation water salinity was observed in treatments that supplied 115% and more than 120% of depleted soil moisture based on MAD = 50%, respectively. With the increase in salinity stress from 5 to 12 dS/m, biomass weight decreased by 23% and seed yield decreased by 17%. Based on the results, the average volume of applied water in fall cultivated quinoa under the 5 dS/m irrigation water salinity was 4900 m3/ha during the growth season (90 days).

In the autumn planting of the Titicaca variety of quinoa, with a planting period of about 90 days in arid and semi-arid regions like Yazd, water consumption is about 450 to 550 mm. But in conditions of moisture deficiency, it is possible to grow this plant. Because it has a lower yield reduction slope than other plants under drought and salt stress conditions. Furthermore, the results indicated that the salinity of the soil profile increased in deficit irrigation conditions (60% and 80% of depleted soil moisture based on MAD = 50%) due to the lack of leaching requirements.

The harvesting stage is the most crucial phase in peanut production. In other words, one of the critical stages in producing this product is the harvest stage. Although it has its difficulties, this stage is associated with significant losses, which experts attribute to the high economic value of peanuts. In recent years, farmers in the Moghan Plain have also started considering this product due to the special conditions of the Iranian economy. In 2020, this study investigated three methods of peanut harvesting in two stages: manual, tractor-mounted thresher (semi-mechanized), and harvesting with a pull-type combine. The first stage involves the complete removal of the plants from the soil, while the second stage involves drying and separating the peanut pod from the plant in Moghan.

The experiment followed a split-plot design in the form of randomized complete blocks with four replications. The main plot consisted of soil moisture levels at harvest time, which were tested at three different levels: a1- 21%, a2- 18%, and a3- 15%. The sub-plot involved testing the separation of peanut pods from the plant using three different methods b1- combine harvesting, b2- harvesting with a tractor-mounted thresher, and b3- manual harvesting. The study evaluated important harvest indicators such as quantitative loss (first and second-stage losses), actual field capacity, harvest time, and the number of required laborers. The results led to the identification of the best harvesting system.

The study revealed that the optimal soil moisture content for the initial stage of harvest was 18%. For most parameters, there was a significant difference observed among treatments at the 1% level. The pull-type combine method had the highest farm capacity with a maximum of 0.46 ha per hour, while the manual harvesting method had the lowest capacity with a minimum of 0.006 ha per hour. The total losses ranged between 5.95% and 10.58%, with the manual harvesting method exhibiting the lowest loss and the pull-type combine method showing the highest loss. Furthermore, the manual harvesting method required more labor compared to the other methods.

Based on the obtained results, it is recommended to use a pull-type combine for the early harvesting of peanuts and a manual method for obtaining high-quality peanuts in the Moghan region.

The decrease in yield and quality levels of button mushrooms during the cultivation period is one of the important challenges of the mushroom production industry, due to the reduction of substrate nutrients and the accumulation of undesirable compounds. One of the solutions to prevent the decrease in yield and qualitative characteristics of edible mushrooms during different flushes is to enrich compost with nutrient supplements.

In order to investigate the effect of supplementary nutrition at different times on the yield indicators of button mushroom, a factorial experiment based on completely randomized design was conducted. Experimental treatments included four concentrations (C) of supplementary nutrition (0 (C1), 20 (C2), 40 (C3) and 60 (C4) g/L) (combination of two phases, the liquid phase includes micro and macro elements and amino acids, and the solid phase includes sucrose and dextrin) and two application times (one day after harvesting the first flush (T1) and the beginning of the second flush and the formation of pin (T2).

The findings of this research indicated the highest number of button mushroom was observed in C3T2 treatment by 215.89, which demonstrated a 20.35% increase compared to C1T2 treatment. The lowest single mushroom weight was measured in the first time of foliar spraying in C1T1 treatment and the highest single mushroom weight was obtained in the second time of foliar spraying in C3T2 and C2T2 treatments, respectively. The maximum length of the mushroom base was obtained in C2T2 treatment by 1.36 cm. Along with the increase in the concentration of nutritional solutions; the diameter of the cap showed a significant increase at T1 time, while at T2 time, this value showed a decreasing trend after the treatment of 20 g/L of nutrient solution. In addition, no significant difference was observed between the cap diameter of mushrooms treated with 20 and 40 g/L in treatments of C2T2 and C3T2, and the maximum cap diameter of mushrooms in these treatments was 3.73 and 3.67 cm, respectively. Enrichment of button mushroom compost by nutritional supplements can prevent severe yield reduction during different flushes.
The number of mushrooms produced in two different times was not significant. It showed that the effect of using time of supplemental nutrition was more effective on the rapid growth of the formed pins than growth of new pins. The formation of pins and the number of mushrooms were under the influence of the amount of inoculation and used spawn in the compost. The positive results obtained from the foliar application of the nutrients showed that its compounds, including sucrose and dextrose and highly consumed elements such as nitrogen, phosphorus, potassium and amino acids, have played an important role on the number, single weight of mushrooms and the cap diameter of mushroom.
The use of nutrient solution in C3T2 treatment compared to C1T2 increased nitrogen percentage by 66.43%, protein by 66.22%, tissue firmness by 71.44% and biological efficiency of substrate by 66.32%, respectively. Pervious study showed that, the effect of different concentrations of three amino acids asparagine, glutamine and glycine on some quality indicators and performance components of white button mushroom was investigated and the results indicated that asparagine 150 ppm improved the yield and increased the protein content. High NPK content in mushroom substrates significantly shortens the rate of mycelium propagation and increases oyster mushroom growth. One of the basic criteria for a good mushroom substrate is the carbohydrate and nitrogen content to support mushroom growth.
Also, using a concentration of 40 g/L of nutrient solution at the time of emergence of the second pin, in comparison with C1T2 treatment, increased the yield of the second flush by 64.15%, the yield of the third flush by 71.17%, the yield of all flushes by 26.79% and the total yield of composted by 26.76%, respectively. Carbon, with its structural role and presence in most organic compounds and providing energy for metabolic reactions, plays a significant role in the growth of button mushrooms. On the other hand, button mushrooms are able to use amino acids as a source of nitrogen. Therefore, it seems that the use of the above compounds in the nutrient solution used in this research has been able to produce favorable results both quantitatively and qualitatively in the studied button mushrooms. On the other hand, it seems that the presence of widely used elements such as phosphorus and potassium in the nutrients used in this research and the positive role of these elements in the production of nucleic acid, adenosine triphosphate, membrane phospholipids and enzyme reactions has been able to play a key role in increasing the quantitative and qualitative properties of button mushrooms.

The use of 40 g/L concentration of nutritional supplement at the time of the appearance of the second flush by affecting the percentage of dry matter, protein and tissue firmness increased the quality level of button mushrooms and enhanced quantitative level by improving yield indicators such as the number of mushrooms, single weight of mushroom, total yield of flushes and percentage of total yield of compost.

The nut sunflower is usually cultivated in small farms and is harvested with a low capacity of harvester at high moisture content. For the rigid threshing components, impact and knead force are so large as it leads to crushing of the grain or inner stress. This reduces marketability and the germination rate of seeds. The mechanical damage degree of sunflower grain is influenced by the material of the threshing beaters, the velocity of impact, moisture contents, etc. Traditional manual methods, that separate grain from the sunflower head, take a lot of time, require large manpower, have high grain damage, and low efficiency. The objective of the present work was to develop and optimize a threshing unit for nutty sunflower that would combine safe impact velocities with appropriate adjusting of its variable to maximize threshing efficiency whilst minimizing grain damage resulting from shearing, cracking, or crushing.

The nutty Sunflower heads were procured from the Experimental Orchard of University of Tabriz, Iran at the moisture content of harvesting. Axial threshing units using kinematic equation and properties of the grain, designed and constructed that the variables of its components are adjustable. The beater of the thresher is flexible, which the deformation and vibration undergoing the overall rotation and impact process becomes larger with increasing speed and prevents grain damage. The power required for threshing and separation grain from heads was calculated at about 4.5 kW. Diameter and rotational drum speed value estimated using relation (V=  and study of other researches as considering critical impact velocity of sunflower grain. The length of the thresher was 1.2 m that estimated by determining the capacity and the number of beaters. Threshing efficiency (%), separation efficiency (%), and grain damage (%) were parameters of performance for study. The experimental design by the Response Surface Methodology in Design Expert software 11 with central composite experiment design developed and the affecting parameters on accuracy analyzed and optimized. The threshing unit was evaluated against three threshing drum speeds of 380, 280, and 180 (rpm), feed rates 4000, 3000, and 2000 (kg (head)h-1), moisture content of 60%, 45%, and 30 (%w.b).

The results showed that the models and effect of variables were statistically significant at the 95% confidence level. The moisture content on threshing efficiency and grain damage had the greatest effect followed by drum speed and feed rate. While for separation efficiency, the feed rate had the most influence. With reducing feed rate and moisture content the threshing efficiency increased, although the decrease in drum speed reduced it. This might be due to sunflower grains adhering loosely to the head at the low moisture contents. The maximum (99.81) and minimum (96.12) percentage of threshed heads was at the moisture content of 30 and 60, respectively. The separation efficiency increased with reducing of feed rate and moisture content. Though, drum speed had insignificant efficacy statistically. The sunflower heads with high moisture content are fragile and brittle, also at high feed rates, the number of impact forces and collisions of heads rises in the condition of threshing. Therefore, the extra MOG is produced and passed from the separator grille. The feed rate of 2000 kg h-1 and moisture content of 30% was the maximum point of separation efficiency that obtained 69.82%. The grain damage decreased significantly with reducing drum speed (380 to 180) and moisture content (60 to 30). This result may be due to the reasons that at higher moisture content the husk of grains becomes soft. The goal of optimization is maximizing threshing and separation efficiency and minimizing grain damage that the optimized values of variables were determined 292.134 rpm for drum speed, 2000 kg h-1 for feed rate, and 30.7406% (w.b) for moisture content.

A threshing unit of sunflower, using properties of grains and kinematic equation, was designed and constructed. The models and effect of the variable were statistically significant on performances. The moisture content had a greater effect than other factors on threshing efficiency (%) and grain damage (%). Also, the feed rate of crops in thresher had the most influence on separation efficiency (%). With decreasing the moisture content, threshing and separation efficiency increased and grain damage reduced. The threshing efficiency (%), separation efficiency (%), and grain damage (%) were reported in the range of 96.12 to 99.81, 57.34 to 68.55, and 0.49 to 1.25, respectively. The optimized points were determined at the drum speed of 292.134 m s-1, feed rate of 2000 kg h-1, and moisture content of 30.7406% (w.b).