AGRICULTURAL RESEARCH
Year:2007 | Volume:7 | Issue:1|Papers Count:9

Irrigation scheduling in agricultural lands needs to know time and amounts of irrigation. In agricultural lands at the Khoozestan, sugarcane is planted and time of irrigation was scheduled using a conventional method namely crop-logging method. This method is time consuming and expensive. In this study, feasibility of application of crop canopy - air temperature difference method for irrigation scheduling was investigated. This research was accomplished in sugarcane lands in Imam Khomainy cultivation and industry company, Shooshtar, Iran. Two treatments including "Plant" and "Ratoon 3" in six replication were selected. Crop water stress index and leaf sheath moisture before the irrigation was measured simultaneously. Lower base line equation was estimated using the measured crop canopy-air temperature difference and vapour pressure as: Tc - Ta=0.522-0.115 (VPD), in which Tc, Ta, and VPD are crop canopy temperature, air temperature, and vapor pressure deficit respectively. Upper base line was determined as 1oC. For the sugarcane lands which the time of irrigation was reached, leaf sheath moisture and crop water stress indexes (CWSIs) were measured simultaneously. The results showed crop water stress indexes varied between 0.1 to 0.3. Based on the average value of CWSI in the irrigation time, an equation was proposed using Idso method to determine the time of irrigation. The results showed this method can be replaced the crop-logging method.

The predaceous mites of the family Phytoseiidae were collected from Guilan Province during three years of faunistic surveys (2003-2006). A total of 14 speciel, from 7 genera belonging to the subfamilies Amblyseiinae Muma and Phytoseiinae Berlese were identified. An identification key was also provided for Guilan Province phytoseiid mites. The lists of identified species are as follows. One asterisk above the species name marks the species which have been recorded for the tirst time from Guilan Province. Subfamily Amblyseiinae including Transeius caspiansis, Euseius finlandicus, E. Amissibilis, Amblyseius herbicolus A. Rademacheri, Neoseiulus umbraticus, N. barkeri*, N. marginatus * and N. bicaudus *, Kampimodromus aberrans *, Proprioseiops is bregetovae and Subfamily Phytoseiinae including Phytoseius plumfer , P. ciliatus * and P. spooji.

In order to investigate the effect of weed infestation periods on light absorption capacity and use efficiency by canopy of potato in seed producing and commercial plant density, an experiment was conducted in the farm of Agricultural faculty of Bu-Ali Sina University in 2006. The study was cal Tied out in a factorial experiment based on a randomized complete bloke design with three replications. The factors were potato plant density at two levels, 5.33 (optimum commercial density) and 6.66 (optimum seed producing density) plants per m-2 and weed infestation periods at seven levels, in which, weeds were allowed to grow for 10, 20, 30, 40 and 50 days after potato plant emergence and then weeds were removed manually until harvest. Two control including full- season weeded and full- season infested were taken. The amount of light in the top and below the canopy was measured 10 days after potato plant emergence and repeated 8 times with 10 day intervals. Weeds were removed before light measurement in each infestation period treatments. Weed and potato sampling was done at the light measurement time to determine potato leaf area index and weeds total dry matter. The results showed that by increasing weed infestation periods, leaf area index, light absorption and use efficiency, light extinction coefficient and number of potato branches per area unit, decreased and weed total dry matter, increased. By increasing the infestation duration, potato tuber yield decreased significantly. The effects of weed infestation periods on the above trials in commercial plant density was more than that of seed producing plant density.

Prediction of crop yield such as wheat has always been an interesting topic for researchers because of its importance in economic planning. The main purpose of such studies is to estimate the crop production before harvesting. Recently, the application of Artificial Neural Network (ANN) has been developed as a powerful tool which enables to solve accurately the most complicated equations and to perform appropriate numerical analysis. The goal of this study is to develop and evaluate an ANN to predict the rate of dry farming wheat yield based on meteorological data in to Ghorveh Region, Kurdistan province. The meteorological data used in this study were: both minimum and maximum average of annual temperatures, mean dew point temperature, relative humidity, monthly and annual precipitation, the average of annual temperature, wind speed, number of frozen, rainy and cloudy days, maximum of daily precipitation and etc for an index period of 1989 - 2000. Different ANN models were developed and the optimum values of network parameters were determined to predict dryland wheat yield by trial and error procedures. Result of this study showed that wheat yield in Ghorveh plain has been affected by the amount and distribution of precipitation and the average maximum daily temperature, especially in the middle and ending months during the growth period. The performance of wheat yield was greatly affected by a slight change in the mentioned parameters. In addition the results showed that ANN model could be used to predict and evaluate the yield before harvesting with a good degree of accuracy. In dry farming as illustrated by results from multiple regression method with a regression coefficient of 94.3%; two factors namely annual precipitation and minimum relative humidity in June have an important bearing on the variation of performance of wheat yield production in Ghorveh plain.

Most of chickpea producing countries and Iran are located in arid and semi-arid zones and drought stress during pod formation and seed filling in this crop is one of the most important yield limiting factors. In order to study the effects of different irrigation levels on physiological characteristics including total dry weight (TDW), crop growth rate (CGR), leaf area index (LAI), leaf area duration (LAD), relative growth rate (RGR), net assimilation rate (NAR) and yield of chickpea cultivars, an experiment was conducted in agricultural farm of Bu-Ali Sina University in 2006. Three irrigation levels including irrigation at podding, irrigation at podding and seed filling, and no irrigation in addition five Kabuli chickpea cultivars (Arman, Jam, Hashem, Flip 93-93 and ILC 482) were compared in a split plot experiment on the basis of completely randomized block design with three replications. In all irrigation levels, maximum leaf area index, total dry weight, crop growth rate and yield were observed in Flip 93-93 cultivar. Application of one irrigation at podding, increased total dry weight and crop growth rate in Hashem and Arman in compare to the other cultivars. In two times irrigation at poddimg and seed filling the maximum increasing of mentioned factors was belonging to Hashem cultivar when compared with no irrigation. There was a significant difference between the yields under three irrigation levels. The highest yield obtained using two times irrigation. Irrigation at podding and no irrigation decreased the yield for the amounts of 17 and 37.5% respectively in compare to the two times irrigation at podding and seed filling. In both of one and two times irrigation the highest increase in the percentage of seed yield was observed in Flip 93-93 and jam cultivars respectively.

In arid climates, water is a limited resource, and turfgrass could be irrigated with wastewater. However, effect of irrigation with wastewater on nutrients and heavy metals uptake by plants needs to be evaluated. The objective of this research was to evaluate the effects of different percentages of advanced treated wastewater (TW) of Shahinshahr Wastewater Treatment Plant (100% water (control) with no TW, 50% water and 50% TW, and 100% TW with no water) on chemical elements uptake by four varieties of Zoysia grass (two varieties of Zoysia matrella and two varieties of Zoysiajaponica) in a loamy soil for a period of 10 months. A factorial experiment was carried out using a complete randomized block design with three replications. The results indicated that using TW for irrigating turfgrass increased plant uptake of Ni and Co. Maximum N, P, K, Fe, and Pb was measured in 50% TW irrigated soils. There was no significant variation in Pb uptake in these sources of irrigation water (drinking water of Isfahan and TW of Shahinshahr Wastewater Treatment Plant). Variation of K content was not significant. But varieties of Zoysia matrella (DALZM1 and DALZM2) absorbed more Ni and K than varieties of Zoysiajaponica (DALZJ1 and Mayko). Varieties of Zoysia japonica absorbed more Fe, Pb and Zn than varieties of Zoysia matrella. DALZM2 and DALZJ1 varieties absorbed the highest amount of Co and Ni. Interaction of percentages of TW and turfgrass variety indicated how the content of N, P, K, Fe, Zn, Co, Ni and Pb changed in different percentages of TW. The relation between elements uptake and increasing the percentage of wastewater in irrigation water was not linear.

A relatively high population density and a flourishing agriculture have increased the rate of water consumption. Since nearly 85.5% of the water is obtained from underground resources, over exploitation of these resources has resulted in a negative water balance. In 1381-82 cropping year, this negative balance reached 15.26% million cubic meters. Since 77.36% of the total extracted water is used in agricultural sector, conservation of water resources is one of the most important priorities in sustainable development of this sector. In this research it is assumed that changing the cropping pattern and irrigation method can help to control the volume of demand. So, the goal of this study to find a cropping pattern with a saving in water use of least agual to the figure of negative water balance and acceptable by farmers economically and administratively. It was attempted to make a mathematical model of existing cropping pattern and the allocation of factors of production and farmers' priorities. Then an analysis of sensitivities and tests based on the model was carried out. A linear programming model was constructed and 5 senarios with 5 models. The optimized cropping pattern introduced in this study has the following results: 1. Savings in the optimized pattern are: 21.37% in labor, 14.42% in current expenditure, 1.05% in investment in irrigation under pressure systems, 2.13% in land. And increase of 3.11% in income compared to the present situation. Thus, productivity of the factors of production increases.