JWSS - Journal of Water and Soil Science

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In order to find the critical period of weed control, the best time of weed control beginning (i.e. herbicide application time), and the length of weed control period (i.e. herbicide persistency) in corn, field experiments were conducted in Bajgah and Kooshkak in Fars Province in 1995 using a randomized complete block design with 14 treatments and four replications. Treatments consisted of different times of weed control beginnings (20, 30, 40, and 50 days after corn emergence), different duration of weed control periods (10, 20, and 30 days), a weedy check, and a weed-free check during the period of corn growth.

 In Kooshkak, a 10-day duration of weed control period had significantly lower corn yields than 20 and 30-day periods. In Bajgah, a 10-day weed control period had significantly lower corn yields than a 30-day period. Time of weed control beginning was not significant at both locations however, the interaction between beginning time and the duration period of weed control was significant. It appears in both locations that a minimum 20-day control period at the initial stages of corn and weed growth, and a minimum 30-day control period before corn pollination are necessary to prevent corn yield losses. In order to prevent corn leaf area decline at both locations, a 20-day weed control period until 40 days after crop emergence is necessary.

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Studies on benefits from innovations (technical change) have mostly been performed within the framework of competitive markets. These studies indicate that if the market structure under study is not competitive, determination of technical change benefits within a competitive framework may yield distorted or biased results for different groups. Considering the noncompetitive market structure of tomato in Khorasan Province, benefits from applying biological innovation for farmers, processors and the society as a whole were estimated. The results indicate that under noncompetitive conditions in the tomato market in Khorasan Province, and as a result of the processors’ market power in buying tomato, the potential benefits of utilizing hybrid varieties have reduced for both farmers and the society by about 58 and 12.5 percent, respectively. It may naturally be concluded that farmers’ incentives to adopt hybrid varieties are attenuated because of the tomato noncompetitive market.

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  The response of bread wheat genotypes to weed interference was evaluated under dryland conditions. An experiment was conducted with 26 genotypes of bread wheat and two known cultivars, Sardari and Azar2, as checks in a strip plot (Split block) arrangement based on Randomized Complete Block Design (RCBD) with four replications in 2002-03 at Dryland Agricultural Research Institute, Srarood, Kermanshah. Weed-free and weedyconditions were assigned to horizontal factor with genotypes as vertical factor. Plant height, number of seeds per spike, number of spikes per square meter, grain yield, weed density and dry matter, and indices of Weed Interference Tolelance Index (WITI) and Competition Index (CI) were recorded. Mean comparison showed that genotypes 13, 1, 26 and 8 had higher grain yield than those of checks under both weed-free and weedy conditions. These genotypes also had higher WITI in comparison with the checks. According to CI values, genotypes No. 1, 9, 13, 26 and 27 including checks had a high potential of weed competition. Results of stepwise regression analysis based on WITI as the dependent variable indicated that the number of spike, plant height and number of seed per spike had positive and significant effects on WITI. On the wole, considering WITI and grain yield as two main attributes, genotypes 13, 26, 1 and 8 were selected as appropriate since they showed a high weed competitive ability and also produced higher grain yields under both weedy and weed-free conditions.

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Non-linear Muskingum model is an efficient method for flood routing. However, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed in this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used to find an available criterion to verify ICA. In this regard, ICA was applied for Wilson flood routing then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood, the target function was considered as the sum of squared deviation (SSQ) of observed and calculated dischargem. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance however, ICA was in the first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be recommended as an appropriate method to evaluate the parameters of Muskingum non-linear model.