Agriculture

As we know that organic farming is the need of hour to feed the present population without eroding the health of soil and environment also to give sustainable agriculture this is one of best method for farming that’s why we should go for Organic Farming.

Although the mean of combine losses is about 4-5% in advanced countries, unfortunately in Iran is about 20% and higher. In order to obtain little loss it is necessary that product process such as cutting, convayting, threshing, separating, etc., would be optimized. Threshing is one of these processes which has more effect on combine performance. Reduction of MOG passing concave could reduce the load on shoes that would increase cleaning system efficiency and decrease foreign materials in the bin. In order to evaluate effecting parameters on MOG passing concave, experiments were conducted in 4×3×3 factorial pattern with Randomized Blocks design. Independent variables in this experiment were, stem height, feed rate, threshing clearance ratio and rotational speed of threshing cylinder. To offer an intelligent model to forecasting of MOG passing concave and evaluating of these parameters’ effects on MOG passing, Neurosolution was used. Multilayer Perceptron (MLP) network with four inputs and one output was used to analysise. Results showed that the amount of MOG passing concave had dependent to rotational velocity of threshing cylinder, stem height, feed rate and threshing clearance ratio, respectively. The amount of MOG passing has increased with reduction in stem height, feed rate, threshing clearance ratio and speed up of threshing cylinder.

The current global challenges of ensuring the availability of and access to food, in both quantity and quality, require deliberate and far-reaching solutions. Historically, research for development in agriculture and extension services has been a strong driving force for meeting food supply around the world. Agriculture is changing, and with it, a revised set of skills is needed to address new challenges in agriculture. As attitudes, expectations and employment in agriculture have changed, there is evidence that the skills and competencies of graduates do not meet the needs of today’s agricultural sector. Industrial development is not possible without agricultural development so, maximum people must live in the villages and help in the agricultural development, there is vast difference between rural and urban life and this should be lessened. The standard of living of rural people can be uplifted permanently only when they themselves make an effort in this direction and encourage people to take initiative; it is prerequisite that the change in the field of knowledge, understanding, skill and attitude should be brought about. Extension Education is primarily for the rural development. Its main objective is to bring necessary change in the beliefs or views of people. Extension education is an educational process by which capabilities among people are developed to understand their problems and resources. It is utilized to make scientific methods available to the rural people, so that they can raise their agricultural production and their standard of living. The aim of extension education is community development, which is possible only by bringing change in the behaviour complex of rural people. Extension education plays major role in bringing desirable change in rural people.

The experiment was conducted to evaluate the effect furrow opener (ridge), operation speed and samples depth from furrow on soil physical properties and maize yield during the summer growing season of 2013 in the experimental at fields of Faculty Agricultural University of Baghdad in silt clay soil. The experimental treatments were arranged in Randomize Complete Block Design with three replicates. The main plots were assigned to the machinery unit speeds (3.69, 4.23, 6.27 and11.17 km h-1), whereas sample depth of furrows was assigned to the sub plots included top of furrow (0.00-0.15 m) and bottom of furrow (0.00-0.25 m). Grains of corn (synthetic cv. Maize 5018) were sowing was done on August 18th; harvest was done on December 10th. Irrigation were scheduled when soil water content in the root zone was depleted by the crop to specific fraction of available water (irrigation was imposed at 55% depletion of available water). Soil samples from furrow were taken from each experimental unit of depth 0.0 -0.15 and 0.0 -0.25 m after month of planting, middle season and after harvest to determine soil bulk density and the same samples measured saturated hydraulic conductivity and calculated mean weight diameter (MWD), geo-metric diameter (GMD). At harvest time, two central rows in each plot were harvested to determining grain yield and then; grain yield per hectare was calculated. The results the operating speeds significantly affected the soil bulk density and hydraulic conductivity values. As the operating speed increased, soil bulk density increased and hydraulic conductivity decreased. An increase operating speeds from 3.69 t0 4.23 and 11.17 km.h-1 decreased hydraulic conductivity and increased soil bulk density values for all planting growth stages (after month of planting, middle season and after harvest) except the speed 6.27 km.h-1. Different operating speeds and depth were significantly for mean weight diameter (MWD) and geo metric diameter (GMD) for all planting growth stages.

Assessment of climate variability at local level, where the driver of the economy is agriculture, has enormous advantage in Ethiopia, . This study was then initiated to analyze the variability of rainfall features and their likely implications on long season growing crop; sorghum in Alamata Wereda. Daily climate data was obtained from the National Meteorological Agency of Ethiopia (NMA) and the historical temporal variability of the rainfall features was assessed using Instat and Mann-Kendall statistical softwares. Apart from the interannual variability (26.2%), the annual rainfall has also revealed a decreasing trend. Similarly, the Belg (FMAM) rainfall demonstrated a significant decreasing trend with a very high seasonal variability (53.1%). The Markov chain first order model indicates that the probability of 15 and 20 days consecutive dry spell occurrence on May (90%) and June (75%) were very high signaling that sowing on these months could possibly lead to complete or partial failure of seedling establishments. Even though the correlations between yield and monthly rainfalls was positive, only April (r=0.48) and September (r=0.55) rainfall was statistically significant. This indicates that for sorghum production, rainfall during April (for seedling establishment) and September (grain filling) appears to be particularly important (sensitive). Hence, as there is early cessation and high rainfall variability during the Belg season (part of sowing period for sorghum), different adaptation strategies such as soil moisture conservation and early maturing cultivars should be practiced to minimize the impact of rainfall variability on sorghum production.

In recent years most of countries particularly pay attention on soil’s salinity because reducing water quality,reducing efficient of agronomy products and extension of desertification are come from that phenomenon.Iran is one of only three countries where is encountered to soil’s salinity.one of ways to control salinity is investigation range and addition of it in an area, and in the next step prevention and elimination of problem will be considered.The research has been done in Zahedan’s area in order to examination of soil’s salinity(electricity transfer) with exploitation of geostatistical procedure. Geostatistical factors are used by Kriching, Cokriching, inverse distance weight method and Kriching regression. The 300 points have been done in order to determination of amount of electricity transfer in horizontal and vertical state by electromagnetic inductor device.Three depths of 0-30,30-60 and 60-90 cm have been investigated.According to obtained results the least sum of error in three depths in Kriging regression than three others method illustrate how the method is high benefit and accurate and the method has been chosen to determination of soil’s salinity.Coefficient of soil salinity in regression model in 0-30,30-60 and 60-90 depths have been obtained 0.22,0.27 and 0.32 respectively.According to obtained map, whatever we go down from surface to depth of soil, salinity becomes lower soit has to be more considered to harvest and cultivate.According to low cost and high accuracy of the Kriging regression method, it can be used for zoning of soil’s salinity.