Agricultural Engineering
Year:2018 | Volume:41 | Issue:3 |Papers Count:9

Introduction Soil salinity and alkalization are recognized worldwide as a major threat to agriculture, particularly in arid and semi-arid regions. To manage these soils a lot of data are needed and laboratory measurement is costly and time-consuming. Therefore, indirect methods that are cheap, fast and easy to access are one of the research priorities. One of these methods is visible near infrared diffuse reflectance spectroscopy. Visible and near infrared diffuse reflectance spectroscopy is a time and cost-effective approach that has been successfully used for characterizing soil properties. Materials and Methods The study area is located in Kurdistan Province, about 20 km northeast of Ghorveh city, west of Iran, and covers 260 km2. Average annual precipitation and temperature are 369. 8mm and 10. 8 ° C, respectively. Soil moisture and temperature regimes are Xeric and Mesic, respectively. In the study area, 100 soil samples were collected (0– 30 cm depth). The main land use types consist of cropland and rangeland. The soil samples were air-dried at room temperature and then, passed through a 2mm sieve. EC, pH, SAR, OC, CaCO3 and Δ MWD were measured. Sodium Adsorption Ratio (SAR) was calculated using results from the saturated paste extracts of sodium, calcium, and magnesium. The stability aggregate was measured using the difference between distributions of particle size in dry and wet sieve methods. Spectral analysis of soil samples was done using a spectrophotometric instrument with a wavelength of 350 to 2500 nm and recorded using RS3 software. After recording the spectra, different preprocessing methods were evaluated. Two models of multiple linear regression and artificial neural network were used to predict soil properties using spectral data. Results and Discussion The soil salinity of the study area ranged between low and high. The highest amount of salinity was observed in the center, south and southwest of the study area and the least amount of salinity was observed in northwest, southeast, northeast and north. The maximum amounts of acidity and sodium adsorption ratio showed that the central part of the study area has saline and sodium soils. The results showed that the best method for preprocessing of spectral data is the 1st Derivative + Savitzky-Golay filter + Mean center + SNV. The Pearson correlation coefficient between the soil properties and the spectral reflection values for each wavelength in the range of 2450-400 nm showed that there is a relatively high correlation between the measured characteristics and the spectral values of the soil. The results showed that the correlation coefficient can be positive or negative. The maximum positive correlation coefficients for electrical conductivity, soil acidity, sodium adsorption, organic carbon, calcium carbonate and aggregate stability at the wavelengths 1229, 2397, 2399, 1298, 2090, 2014, and two spectra 2257 and 660 were 0. 45**, 0. 43**, 0. 46**, 0. 61**, 0. 53** and 0. 40**, respectively. The maximum negative correlation coefficients for electrical conductivity, soil acidity, sodium adsorption ratio, organic carbon, calcium carbonate and aggregate stability at the wavelengths 630, 2289, 630, 1904, 1379 and 2107 were-0. 47**,-0. 42**,-0. 44**,-0. 46**,-0. 55** and-0. 44**, respectively. Based on the determination coefficient statistic, artificial neural network model (0. 88, 0. 25, 0. 59, 0. 68, 0. 52 and 0. 48 to electrical conductivity, PH, SAR, calcium carbonate and aggregate stability, respectively) had better results compared to the multiple linear regression model (0. 45, 0. 13, 0. 23, 0. 66, 0. 48 and 0. 28 to electrical conductivity, PH, SAR, calcium carbonate and aggregate stability, respectively). Conclusion In this study, visible near infrared diffuse reflectance spectroscopy was evaluated to estimate some properties of salt-affected soils. After recording the spectral data, the continuity curve and pre-processing of spectral data were performed. The results showed that the best method for pre-processing of spectral data is the first derivative + Savitzky filter and Glair + Mid filter + Normal standard variable. Multiple linear regression and artificial neural network models were used to estimate some properties of salt-affected soils (EC, pH, SAR, OC, CaCO3 and Δ MWD) using spectral data. Based on the statistics of mean error, root mean squared error, and correlation coefficient, the artificial neural network model had better results in estimateing the properties of salt-affected soils compared to the multiple linear regression model. Therefore, based on these findings it is suggested that soil spectral data be used as an indirect method to the estimate soil properties.

Introduction Due to the difficulties in observing root growth in soil, our knowledge regarding soil-root system is limited. The roots are the hidden half of the plants but our knowledge of root’ s growing is limited. Now, there are some methods and devices that have been used to analyze and monitoring roots architecture and growth and their relation with soil. The assessment of the root growth of plants is possible with some photographic techniques such as neutron radiography and tomography, as well X-Ray imaging, but the use of these methods for root studies is very costly especially in Iran. The use of the rhizotron can also be one of the most practical and cost effective methods. The rhizotron is a box with a transparent side and uses to study the roots growing by photography or drawing roots on transparent acetate sheets. Here we aimed to introduce the rhizotron as a technique for studying plant roots, and conducted this study to investigate the effects of heterogeneous petroleum pollution in soil and endophytic fungus on growth and distribution of maize root. Materials and Methods In order to bring rhizotron forward as a method for in situ assessment of growth, establishment and distribution of plant roots a greenhouse experiment was performed. The effect of Piriformospora indica and soil petroleum polluted layers on the growth and distribution of maize (Zea mays L. ) roots was studied. The rhizotrons had a wooden frame and back plate, and a removable front cover made of a 4 mm thick glass plate. The inner space was 30 cm high, 20. 5 cm wide, and 1. 5 cm thick (Figure 1a). The rhizotrons were placed on a rack with a 45˚ inclination to induce roots growing along the front glass to enable visual growth monitoring. The front glass plate was covered with an opaque black plastic to prevent light entering except for the times of observation. Two different patterns of soil-petroleum contamination layering were generated in the packings of the rhizotrons. 1) a shallow layer of 2. 5 cm thick petroleum-contaminated soil, underlying of a 2. 5 cm and above a 22. 5 cm layer of uncontaminated soil (NSC), and 2) 27. 5 cm of uncontaminated soil (‘ control’ ). The packing procedure was layer by layer using uniform filling in all three cases. The contaminated soil layers were covered with a 2. 5 cm layer of uncontaminated soil in order to facilitate plant establishment. The experiment with three replications was included as the packing methods each for growing maize plants inoculated with and without P. indica, and plant-free controls. The root development was recorded 12, 16, 22, 26, 33, and 45 days after transplanting by tracing all roots that were visible through the front glass on acetate transparencies, then were scanned at 300 dpi and analyzed for parameters such as root length, number of root tips and depth of rooting using the SmartRoot plugin of the software package ImageJ. After the last recording, the experiment was terminated. Roots and shoots were separated after harvesting, weighed and oven-dried. Rhizosphere soil samples were taken from the layer 2. 5– 5. 0 cm below the soil surface for total petroleum hydrocarbons analysis. Results and Discussion The results well showed that root length, root depth and number of root tips could be monitored by this method. The presence of petroleum pollution in the soil significantly decreased the growth and distribution of roots but inoculated plants had more root length and root depth than uninoculated plants. The number of root tips which representing lateral distribution of roots had similar trend with root the length and they were significantly increased in the inoculated plants as compared with uninoculated ones. Results showed that inoculation of maize by P. indica increases root biomass more than the aboveground biomass. Conclusion Despite the limitation in the study of the effect of soil treatments on the growth and distribution of plant roots, the use of rhizotron could be a technique to solve this limitation. Our study proved that by using of rhizotron we can show the growth and 2-dimension distribution of plant roots, while the effects of treatment and root-soil interaction could also be assessing by this device.

Introduction Salinity is the most important challenge in arid and semi-arid regions. Salt stress, ionic and osmotic components, like other abiotic stresses, lead to oxidative stress that damage cellular membranes, nucleic acids, oxidizing proteins, and causing lipid peroxidation through overproduction of reactive oxygen species (ROS). Antioxidant capacities and osmolytes play a vital role in protecting plants from salinity that causes oxidative damages. Applying biological methods such as using of halotolerant plant growth promoting rhizobacteria (PGPR) is very important to reducing the harmful effects of salinity on plants. Also exopolysaccharide production by plant growth-promoting strains helps in binding cations, including Na+, and thus decreases the content of Na+ available for plant uptake. This is especially useful for alleviating saline stress in plants. Biochar can also alleviate the negative impacts of salt stress in crops. Biochar can enhance plant growth either by its direct or indirect mechanisms of actions. The direct growth promotion relates to supplying mineral nutrients, such as Ca, Mg, P, K and S etc., to the plant, whereas, indirect mechanisms involve improving soil physical, chemical and biological characteristics. Materials and Methods In this research, the effect of halotolerant plant growth promoting bacteria, biochar and gypsum was investigated on enzymatic and non-enzymatic defense mechanisms of barley such as Catalase, Superoxide Dismutase, Proline and Membrane stability under salinity stress. The experiments were carried out as a factoria with a completely randomize design in greenhouse conditions for 2016-2017. The factors included: bacteria (without inoculation (T0), bacterial isolate T5 (megateriumBacillus), bacterial isolate T17 (licheniformis Bacillus ), biochar (0 and 5percent w/w), gypsum ( 0and 50 percent gypsum requirement ) and soil leaching (without and leaching with) with three replications. The activity of catalase (CAT) was determined by changes in absorbance at 240 nm (IUg− 1FW) (Aeby, 1984). Superoxide dismutase (SOD) activity was determined by nitroblue tetrazolium (NBT) reduction, according to Minami and Yoshikawa (1979) and the enzyme activity was expressed as (IUg− 1FW). Proline content was estimated according to Bates et al., (1973) and expressed as µ mol g− 1 fresh weight (FW). Membrane stability was estimated according to Sairam and. Saxena (2001). All statistical analyses were performed using SAS software. The means of different treatments were compared using LSD (P ≤ 0. 05) test. Results and Discussion The results showed that using halotolerant bacteria and biochar reduced the activity of antioxidant enzymes in barley plants. This reduction was higher in the treatment containing bacteria T17 (Bacillus licheniformis) biochar and with leaching. Also, inoculated plants with both bacteria had the highest concentration of proline, which was significantly higher in the treatment containing bacteria T17 (Bacillus licheniformis) biochar and gypsum. Also, application of halotolerant bacteria, biochar and gypsum improved the membrane stability of plant. This increase has been remarkable in inoculated treatments with T17 bacteria (Bacillus licheniformi) in saline soil with leaching associated with 50 percent gypsum requirement Conclusion Generally, results showed that halotolerant bacteria, biochar and gypsum can be used as a tool for reducing adverse effects of salt stress. Inoculation of soil with these bacteria has helped in alleviating saline stress by changing several physiological, enzymatic, and biochemical agents in plant. Bio-remediation of salt affected soils is one of the cheap and eco-friendly approaches for remediation of salt affected lands as the traditional physical and chemical techniques are becoming costly. The plant growth promoting halotolerant bacteria helps in Bio-remediation of salt affected soils and thereby improving the agricultural crop yields. Incorporation of biochar into salt-aff ected soil could diminish salinity stress by decreasing soil bulk density, increasing in soil cation exchange capacity, potassium and calcium concentrations, water holding capacity and nutrient and water availability in soil. Also, bichar due to high organic matter content can play a dramatic role in salt affected soil with organic compound defficiency. According to these amended features of biochar in soil, we suggest, more experiments conducted by biochar with diff erent material and ratios under saline-sodic soils.

Introduction Drying is one of the important stages after harvesting of plants and agricultural products, which plays an important role in the quantity and quality of the active ingredients. The purpose of drying is to reduce water to a certain level for low and stop the microbial activity. Therefore, in laboratories the effects of different levels of temperature and time are investigated on different plant properties during drying operations with laboratory dryers and ovens. It can be said that the principled and thorough drying of medicinal plants is necessary in order to reduce moisture, increase the shelf-life and increase the quantity and quality of the active ingredients. Today, many control algorithms are used to control temperature, which is much more efficient than the on-off. Fuzzy control is suitable for fast control and high accuracy of proper nonlinear processes. Likewise, the type of ventilation and the placement of thermal elements are also very influential on the heating system and the temperature of the chamber. Today as foreign companies, in addition to focusing on the type of control system and intelligence ovens, many studies have been done on how the element is placed, on its type, the shape of the fan, its type, and the design of the air channels. Materials and Methods The dryer was designed with software Solid Works and constructed in manufacturing workshop of the Bio-System Mechanics Engineering Department of the Natural Resources and the Agricultural Sciences University of Gorgan, Iran. The device has a fuzzy control system, a ventilation, and fan system. The built-in dryer has two mechanical and electrical parts. This dryer has an external chamber with dimensions of 74 × 50 × 60 cm and internal chamber dimensions of 40 × 35 × 50 cm. The device was insulated with thermal spray foam. The electronic circuit was designed using Proteus simulation software and implemented on the board. The main piece of information processing and controlling the algorithm in the dryer control system is the microcontroller. The microcontroller programming was written by C software and transmitted to the microcontroller with the Code Vision software. The tests were performed at three levels of 60, 80, 90 ° C. The programmability of the device was also evaluated simultaneously for four different temperatures and times. The device was evaluated at 4 levels of 90, 70, 50 and 30 ° C and four levels of the time were done respectively 10, 10, 10, and 20 min. Also, in the process of increasing temperature, the temperatures of 40, 60, 80 and 90 ° C respectively were tested. Also, the stability function and the time to reach the temperature were compared with two samples of the laboratory dryer (oven) imported Memmert and Bender models which had a fuzzy control system and a ventilation system and a built-in oven model in the interior. Results and Discussion Because exactly as wasted, the temperature of the chamber walls is applied to the chamber, the device is capable of maintaining the temperature of the chamber at the set point. The result of the evaluation in the energy waste from the wall of the device showed that after about 200 min, the temperature of the internal chamber (which was at 80 ° C) was equal to the outside temperature of the chamber. The results showed that during temperature stability, the difference in temperature between different points of the compartment (places where laboratory samples are placed) is less than ± 0. 5. The programmability of the device was evaluated at 4 levels of 90, 70, 50 and 30 ° C; after reaching the temperature of 90 ° C, and at the end of the scheduled time, the temperature is reduced to a minimum, reaching the next temperature. Reducing the temperature for other temperatures was also done according to the program. The results of the programmability of the device were shown in the incremental step of the temperature; in the incremental process, as the temperature decreases, the temperature difference between the points is very small and reaches the temperature stability as soon as it reaches the regulated temperature. The control system used can properly maintain the temperature in a stable state. The results of the comparison of the performance of the dryer control system made with other experimental dryers at a temperature of 80 ° C showed that the dryer was able to stabilize the inside of the compartment at the desired point, in comparison with other ovens. The built-in dryer function is compatible with the Memmert UFE500 and the Binder FE53 ovens. Due to the cost of the device, its use will be very useful for conducting research in research centers. Conclusion The fuzzy control system used in the dryer was able to properly control the temperature of the chamber according to the program. The control system of the device was able to control the temperature of the chamber at a regulated point with a minimum temperature variation (less than half a ° C). The built-in dryer was able to reduce and increase the temperature step by step in a given temperature range according to the given program. The performance of the dryer, compared with other ovens, showed that it could match the best of imported ovens.

Introduction Under natural conditions, intensive and erosive storms commonly associate with high-speed winds. In fact, wind velocity affects water erosion rate through enforcing falling drops and enhancing rainfall erosivity. Therefore, knowledge of interaction between wind and rain as erosive agents on interrill erosion is of prime importance. However, no comprehensive study has been done on this topic under controlled laboratory conditions. This study was conducted to investigate interrill erosion affected by different rain intensities and wind velocities on several soils with different aggregate size distributions using the Simultaneous Wind-Rainfall-Runoff Simulator (SWRRS). For this purpose, a multisystem was constructed for the first time in Iran to investigate the simultaneous effects of wind and rain erosivity agents on soil erosion under laboratory conditions. Materials and Methods The simulator was calibrated in two cases. First, the intensity and uniformity of the simulated rains were assessed for each nozzle, separately. Second, the calibration procedure was performed for different combinations of the selected nozzles to achieve the best performance. For each case, different water pressures were generated to introduce several water discharges and make initial raindrop velocities. Afterwards, the interrill erosion experiment was done using four constant wind speeds including 0, 6, 9 and 12 m s-1at the height of 40 cm which were applied in combination with three rain intensities of 30, 50 and 75 mm h-1 on three soil samples with different aggregate size distributions (D2mm, D4. 75mm and D8mm). Each treatment was conducted at three replicates under laboratory controlled conditions. By using different wind speeds, rain intensities and soil aggregate sizes, interrill erosion rate was measured under steady state conditions. Results and Discussion Results showed that wind velocity has a significant effect on interrill erosion rate and the interaction between wind and rain on interrill erosion was significant, as well. Although, there was no significant difference between the erosion rate at wind velocity of 0 and 6 m s-1, the wind velocity of 9 and 12 m s-1 showed significant difference with and higher erosion rates than the velocity of 6 m s-1. The mean erosion rate at wind velocities of 0, 6, 9, 12 m s-1 was 0. 43 × 10-4, 0. 54 × 10-4, 0. 97 × 10-4 and 1. 46 × 10-4 kg m-2 s-1, respectively. With increasing rain intensity from 30 to 75 mm h-1, the erosion rate increased from 0. 52 × 10-4 to 1. 16 × 10-4 kg m-2 s-1. On average, the erosion rate of the soil containing larges aggregates i. e. D8mm (0. 73 × 10-4 kg m-2 s-1) was less than that with the finest aggregates i. e. D2mm (0. 99 × 10-4 kg m-2 s-1). The findings of this study highlighted the importance and necessity of more attention to wind speed particularly those velocities faster than a threshold velocity in the study of interrill erosion. Conclusion In arid and semi-arid regions such as most parts of Iran, rainstorms are usually accompanied by strong winds. Despite the undeniable influence of wind on the erosive power of rain, a host of research has investigated water and wind erosion processes, separately. Therefore, this study was done to investigate the simultaneous effect of wind velocity and rain intensity on interrill erosion rate in three soil samples. The results indicated that wind velocity has a remarkable influence on interrill erosion rate due to wind-driven rain. Wind velocities faster than 6 m s-1 increased interrill soil erosion rate, particularly those combined with higher rain intensities. This is due to an increase in the velocity of falling raindrops on the soil surface which results in greater kinetic energy. Also, the findings showed that the soil containing coarser aggregates due to greater random roughness exhibited less sensitivity and interrill erosion rates as compared with the soil having finer aggregates, especially at faster wind velocities. The rate of interrill erosion in soil D2mm was 1. 35 times higher than soil D8mm indicating the importance of random roughness. In addition, there was no significant difference between the measured erosion rates at wind speeds of 0 and 6 m s-1, in all cases. However, with increasing wind speed from 6 to 9 and also to 12 m s-1, significant increases in soil erosion rates were observed. Accordingly, a threshold wind velocity can be considered in wind-driven interrill erosion. The findings of the present study can be applied for better understanding and modeling of water and wind erosion mechanisms and dominant processes.

Introduction Date fruit is a strategic horticultural product in the Middle East that plays an important role as an economic product to develop exports. Iran is the second world producer that contains 14% production of date fruit in the world and has a high potential in order to ideally exploit this valuable product. Condidering the low price of Iran's exported dates due to poor preparation and packaging process it is necessary to use new technologies for classification and grading of them. The application of machine vision in agriculture has increased considerably in recent years. There are many fields in which computer vision is involved in order to develop precision agriculture. Machine vision systems by elimination of manual inspection in the field of postharvest technologies improve accurate and uniform quality control of agricultural products. In most of these applications, the method of image analysis for product categories, with the determination of some external features such as color, size, shape, and surface texture has been used (Blasco et al., 2012). Alohali used RGB images taken from Date fruits and defined a set of qualitative external features of dates and categorized them into three categories in terms of quality. One of the characteristics of the soft tissue was detected using color intensity distribution. The final precision of carefully designed system using a propagation neural network was 80% (Alohali, 2011). The size is a particular aspect of external appearance of fruits and vegetables; the price of agricultural products is usually related with their size; therefore, grading of fruits and vegetables into different size groups of size is always necessary in the postharvest handling and processing stages (Zhang et al., 2014). Texture is the other significant sensory quality attribute that has been frequently used in the external quality inspecting and grading systems for the agricultural product quality evaluation. Texture is closely related to some internal quality of fruits and vegetables, such as maturity and sugar content. Therefore, texture is one of the widely used indicators the consumer uses for quality assessment of fruits and vegetables. Texture analysis can also play an important role in defect recognition and segmentation in grading systems due to its powerful discriminating ability (Lee et al. 2008). Materials and Methods The current study examined image processing technology for grading Zahedi cultivar dates in Khuzestan province. Each date fruit was placed under the camera and imaged. At the same time, the samples were classified by an experienced grader. Imaging was conducted in a lighting box to avoid the effects of ambient light. Capturing images was done by a digital camera using CCD sensor. External features of dates such as color, size, shape and surface texture were extracted by image processing methods using MATLAB software (Version R2013a, The Mathworks Inc., Natick, MA, USA). Eleven size and shape features, nine color features, and six external texture features were extracted. The features which led to better separablity for classification were selected using stepwise discriminant analysis (SDA). Selecting the best features is effective to increase accuracy and speed of the algorithm. Two methods of learning machine were used for final classification: discriminant analysis that is a statistical technique and neural networks (ANN). Discriminant analysis method and Neural networks were implemented in SPSS 22. 0 and neurosolution 7. 0 software respectively. Results and Discussion The best channel to separate dates from background was identified by comparison of the histogram of 9 channels from RGB, HSI and Lab color spaces. The histogram graph, which has more breakdown in the range of intensities, is more suitable to apply thresholding operation because it has a good contrast with the background. Channel B from RGB color space was chosen to segment dates from background. Channel of B has a better contrast between the color channels and also its corresponding histogram intensity values led to the best separability. Five features of size and shape, three features of color and three features of external texture were selected by SDA method to reduce dimension of features space. Degrees marked from 1 to 3 for qualitative grading and sorting by size define levels of quality and determine size from big to small dates respectively. According to table 4, accuracy of classifications for grading, sorting by size and inspection of wrinkled date fruits from healthy ones were 93. 6%, 94. 4% and 90% respectively. Classifications by MLP neural networks were done. The most important factor for evaluation of neural networks is Correct classification rate (CCR%). The results based on CCR from Confusion matrix is reported in table 5. Accuracy of classifications for grading, sorting by size and inspection of wrinkled date fruits from healthy ones using ANN were 95. 7%, 92. 3% and 93. 8% respectively. Conclusion Final accuracy of classification using discriminant analysis and neural network was achieved 92. 7% and 93. 9% respectively. Results show relative superiority of neural networks over statistical methods due to its accuracy. According to high accuracy of classification using learning machine methods, it can be concluded that using image processing algorithm was successful in extracting external features for sorting and grading of dates.

Introduction Wheat is the main food commodity of Iranian population and major cultivating crop, grown on nearly half of the country’ s rain-fed area as well as one-third of the irrigated area. Despite the availability of high yielding cultivars for different climates, the average wheat grain yield in the country is around 3527 kg ha-1. Lower wheat grain yield could be due to unavailability of recommended varieties seed, delay in planting, inappropriate planting methods, excess use of fertilizers and inefficient water management. Irrigated wheat production in arid and semi-arid regions of Iran is generally practiced under conventional tillage systems. Crop producers in southwestern part of Iran are traditionally using conventional tillage (plowing with moldboard plow followed by double disking) for cultivating various crops. Most of the farmers use grain drills for sowing wheat because of uniformity of planting depth as compared to seed spreaders. The aims of the study were to determine whether different methods of sowing, such as grain drills (followed by flooding irrigation), row crop planting, and combination of furrowers (75 and 60 cm) and seeders (12 cm of sowing space) alter the agronomic performance of winter wheat. Therefore, selection of suitable sowing method plays an important role in the placement of seed at proper depth, which ensures better emergence and subsequent crop growth. Material and methods The study was conducted on a silt clay loam soil (Carbonatic Typic Torrifluvent) in research farms of Ramin Agriculture and Natural Resources University, Ahvaz, Iran, with wheat-wheat-corn crop rotation. The soil was representative of a large area of arable land in the Khuzestan province. Conventional tillage was practiced by moldboard plow ( 25 cm depth) followed by disc harrow twice (nearly 10 cm depth). The two year experiment was conducted based on completely randomized block design in four replicates. 140 kg/ha of wheat (Triticum aestivum L), Chenab cultivar was sown at 50 mm depth for all treatments. The experimental treatments were 20 furrow opener rain drill with 12 cm line space (P), combination of grain drill-furrower (PF60 and PF75) with 60 and 75 cm furrow spaces, also furrower-grain drill (FP60 and FP75 cm) and furrower – grain drill with 3 planted rows on beds (FP3_60 and FP3_75 cm). Soil conductivity of the experimental field (plots) ranged from 1. 2 to 3. 3 ds mG. The soil texture was silty clay loam with the range of clay content from 34 to36%, and N, P and K contents of the soil were 0. 8 to 1, 6. 1 to 16. 2 and 117 to 192 mg kgG, respectively. Results and discussion Wheat grain yield obtained from all treatments was different; however, harvested grain after FP_75 was the highest compared to others. The highest amount of yield was 5966. 7 kg/ha for the first year and 5070 kg/ha for the second year compared to simple planting (P) which was the lowest (4883 and 4271 kg/ha respectively for 2 interval years). Analysis of variance for grain yield indicated that FP-75 had a significant difference (p<0. 01) as compared to others, but grain yield for furrow spaces from 60 to 75 cm was not significantly different. However, the use of furrowers showed significant effects on wheat grain yield. Crop yield and biomass were shown to be different where the furrow was made before sowing. The use of grain drills without furrowers had a great negative effect on crop biomass and grain yield. The results obtained from the second year were similar to the first year. The application of furrow before sowing showed maximum crop yield and biomass, so that the highest and the lowest biomass belonged to FP-75 with 14817 kg ha-1 and P with 11731 kg ha-1, respectively. The harvest index was not significantly different among treatments. Similar results were obtained in wheat plots after harvesting. Conclusion The overall results from this study indicated that the values of crop yield and biomass were maximum where the furrow was made before sowing, as FP-75 treatment had the highest yield. So regarding non-problem of soil salinity in the north of Khuzestan, the use of furrow before sowing can be considered as an appropriate tillage and sowing system for wheat production in the semi-arid region.

Background and objective Unlike engineering materials, apples are living tissues which survive after harvesting. Thus, post-harvest processes such as transporting and packaging should be carried out in a way that makes them less vulnerable. Among the agricultural products, fruits and vegetables are the commodities that due to their low resistance to the shell and high humidity, have a high sensitivity against mechanical damages that occur when processing them. In order to minimize waste, proper post-harvest management and convenient techniques for transport and storage are required. Mechanical damages can occur in three major ways, including pressure, impact, and abrasion. The pressure during the harvest may impose on the fruits by pickers or occur when fruits are stored in the bottom of the box. External damages may happen due to the weight of picked apples in the baskets in deep boxes or when transporting the boxes by hooks. In fruit packaging stations, pressure, impact, and vibration can occur when packaging of fruits in boxes, as well as the washing and waxing fruits. Pressure forces usually happen during transport and storage of the fruit. This study was undertaken to study the impact on sugar, phenol, acidity and fatigue area that play a major role in the final quality of the product. Materials and methods Static and dynamic impacts and storage time were considered as the independent factors in this study and their effects were analyzed on the chemical parameters including sugar, phenol, acidity and fatigue area. The static impact was conducted by Instron Sntam with three loading speed 5, 7, and 10 mm/min for 1min. The dynamic impact was conducted by a pendulum that simulated the energy applied to apples that dropped. The amount of energy was equivalent to 2. 25, 3 and 3. 75 J. Apples that underwent impacts, were kept for 20, 40 and 60 days to measure the impact on changes of chemical parameters and determine the area of fatigue. After each storage period, the samples were photographed. The area of fatigue was measured using image processing techniques and Image J software. The image processing consists of two parts: hardware and software. The hardware of computers, cameras and imaging chamber is formed. The camera was connected by cable to a computer and the images were stored on a computer's permanent memory. Used computers used running windows seven, five-core central processing unit, and RAM was 4 Giga bytes. Computer is the processing of the data and the image acquisition step to the final step, the output data is the most important role. The used camera was a Canon, made in Japan, was mounted vertically inside the box. Shooting box was used just because all the photos must be taken in a constant condition of light regarding light intensity of surroundings and distance of apples from the camera. The Chamber was made of wood and shaped like a cube with dimensions of 45 × 45 × 45 cm, which is just an open area. Three eight-watt fluorescent lamps for lighting inside the box was fixed to the ceiling box around the triangle mounted camera. Image J analyzer is a powerful software with various uses. This software can calculate the area and pixel value statistics of user-selected portions of the image. Factorial experiments were carried out in a completely randomized design with three replications. Results Results revealed that acidity changes and fatigue area during the storage under static and dynamic impacts were significant at 0. 01 and 0. 05% and for phenol and sugar were significant at 1 and 5%. Also, in this test, sugar content and acidity were generally reduced over time, and phenol and fatigue area increased. Conclusion In order to avoid excessive reduction in sugar and fruit quality, maintenance time should be reduced as much as possible. Phenol increased during storage, after applying impact; its oxidation when contacting air results in toxic compounds that are harmful to humans. Therefore, packaging using the pads and increasing the quality of the harvesting and transporting is necessary in order to reduce the damages to the fruit. Fruit acidity during storage after the impacts showed the significant changes that could negatively affect the taste of the fruit and as a result, its marketability.

IntroductionWheat is one of the key cereals that provides a nutrition source to millions of people around the world. By conducting applied studies, the limitations of soil and climate that reduce the yield per unit area must be understood and solutions should be provided to address these limitations. One of these strategies is a detailed study and spatial prediction of yield at points with different soil and climate characteristics. Models that predict crop yield can estimate the yield regarding climate, landscape, soil and management constraints. Considering the arid and semi-arid climate of Iran, the shortage of yield per unit area and the growing population, the country needs new research and strategies to increase yield per unit area. For this purpose, the first step is to examine the spatial variations of the yield. In the present study, the factors affecting the rainfed wheat yield in order of importance and efficiency of different methods of estimating spatial variations were investigated and the predicted yield of this crop was mapped digitally. Materials and MethodsThe study area, with an area of 6700 hectares is located in Badr watershed, around Ghorveh city, Kurdistan province, west of Iran. The mean annual air temperature is 12. 1oC and the average annual precipitation is 345. 8 mm. The soils of the area were classified in the orders of Entisols, Inceptisols and Mollisols and in 32 soil families, according to the last version of Keys to Soil Taxonomy. Based on hypercube technique, 125 observation points were selected, soil profiles were dug and described at these points and soil samples were collected from horizons of the profiles. Some physical and chemical characteristics of the soils were determined according to the standard laboratory methods. Rainfed wheat yield was measured at each side of one soil profile in a 1m×1m quadrangle. In the present study, in addition to geomorphological data, different types of auxiliary variables such as some of the primary and secondary derivatives of digital elevation model (DEM) and Landsat satellite image data were used. To find out the affecting auxiliary topographic and plantcover data on rainfed wheat yield prediction in order of importance, ReliefAttributeEval algorithm of WEKA software was used. Artificial neural network, decision tree Analysis, discriminant analysis, and averaging k-nearest neighbors are the models that were used in this research for prediction of rainfed wheat yield. Results and Discussion Calcium carbonate, organic carbon and coarse fragments, respectively with variability coefficients of 174. 4, 62. 4 and 61. 3%, had the highest variation and pH, CEC and sand, respectively with 3. 6, 16. 9 and 20. 3% variability coefficients showed the least variability in the soils of the studied area. In addition to geomorphological data, the parameters that were taken from the digital elevation model include elevation, slope percentage, slope aspect, slope curvature, slope surface curvature, longitudinal curvature, slope relative position, wetness index, multiresolution valley bottom flatness index, multiresolution ridge top flatness index, valley depth, channel network base level, modified catchment area, catchment slope, catchment slope aspect and catchment height. The environmental parameters that were taken from the Landsat 8 satellite imagery, include the normalized differential vegetation and the soil-adjusted vegetation indices. The ReliefAttributeEval algorithm in Weka software, in order of decreasing importance, identified geomorphology, relative slope position, longitudinal curvature, multi-resolution ridge top flatness index, slope, normalized differential vegetation index and soil-adjusted vegetation index as the most important factors affecting rainfed wheat production in the studied area. The amount of rainfed wheat yield was predicted by the models of artificial neural network, decision tree analysis, discriminant analysis, and averaging k-nearest neighbors. The error criteria for this prediction and a significant correlation between measured and estimated values of the rainfed wheat yield, indicate a higher accuracy for the averaging k-nearest neighbors model, compared to other models. The spatial distribution of the rainfed wheat yield, predicted by the averaging k-nearest neighbors model, was mapped. In the Badr watershed, the yields are continuously reduced towards the mountains. In this landscape, as the slope increases, depth and water storage capacity of the soil decrease mainly in the presence of Entisols. These soils are seen in the eastern, southern and western parts of the watershed. At lower elevations, the soils are deeper and are mainly Inceptisols. Rainfed wheat yield increases in the piedmont landscape, including hill, glacie and alluvial fan. Conclusion In order of decreasing importance, geomorphology, relative slope position, longitudinal curvature, multi-resolution ridge top flatness index, slope, normalized differential vegetation index and soil-adjusted vegetation index are the most important factors affecting rainfed wheat production in the studied area. The averaging k-nearest neighbors model has a higher accuracy for rainfed wheat yield prediction, compared to other models. In the Badr watershed, the rainfed wheat yield is continuously reduced towards the mountains in the eastern, southern and western parts, where mainly Entisols are present. The yield increases in the Inceptisols, located on the piedmont landscape.