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首页> 外文期刊>Alexandria Journal of Agricultural Research >Mathematical Models for Determination of The Critical Period of Weed Competition In Sunflower {Helianthus annuus L.)
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Mathematical Models for Determination of The Critical Period of Weed Competition In Sunflower {Helianthus annuus L.)

机译:确定向日葵杂草竞争关键期的数学模型(Helianthus annuus L.)

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摘要

Two field experiments on sunflower were conducted during 2013 and 2014 summer seasons at EL-Serw Station, Damietta Governorate, Egypt. Each experiment included ten weed competition and weed removal treatments either at early or late times after sowingwhich were: - weed competition for the whole season, weed competition for 2, 4, 6 and 8 weeks from sowing, weed free for 2, 4, 6 and 8 weeks from sowing and weed free for the whole season, to determine when a natural infestation of weeds start to reducesunflower yield and when to control without yield losses in sunflower. Dominant major weeds in experimental fields were Portulaca oleraceae, L.; Corchorus olitorius, L.; Amaranthus caudatus, L.; Echinochloa colonum, L. and Chenopodium album, L.The obtained results revealed that which weed infestation rate under sunflower field was 5.885 and 6.527 ton fresh weight / fad., which reduced drastically seed yield of sunflower per faddan by 55.3 to 55.2% under weed competition treatment of sunflowerfor the whole season in 2013 and 2014 summer season, respectively, as compared with weed free for whole season treatment. The use of response curves with weed free or weed competition period showed that seed yield and oil yield of sunflower were the highest with the field free from weeds until 6 weeks after sowing , and the critical period of weed / sunflower competition was between lie 2- 6 weeks after sowing. In regression approach for sunflower seed yield, oil yield and weed free or weed competitionperiod the polynomials (linear and quadratic) and logistic functions were tested and quadratic function was fitted to estimate the expected yields which had the high significant with the data recorded and have the highest values of R2 than the other models (linear or logistic model.) for this reason it is used to estimate critical periods of weed competition with sunflower. Also, results showed that the quadratic equations were significant and had the highest R2 (0.989, 0.982) and (0.989, 0.984) for weed free period, and (0.899, 0.992) and (0.919, 0.994) for weed competition durations in 2013 and 2014 summer seasons, respectively.According to these results, the critical period of weed competition to sunflower is the first six weeks period from sowing was required to be weed free showed that to maintain 95% of maximum seed and oil yield of sunflower and one week of weeds infestation can be allowed after sunflower sowing without seed and oil yield sunflower reduction. The information should be taken in consideration for sunflower growers to plan their strategies of integrated weed management for this important crop.
机译:在2013年和2014年夏季,在埃及达米埃塔省EL-Serw站进行了两次向日葵实地试验。每个实验在播种后的早期或晚期进行十次杂草竞争和除草处理,它们是:-整个季节的杂草竞争,播种后2、4、6和8周的杂草竞争,2、4、6的杂草释放播种和整个季节除草后的8周内,以确定什么时候杂草自然受到侵染,开始降低未开花的产量,何时进行控制而又不损失向日葵的产量。实验田中主要的主要杂草是马齿Port科。桔梗Corcorus mar菜得到的结果表明,向日葵田下杂草的侵染率分别为5.885和6.527吨鲜重/ fad。这使杂草在向日葵下的每种子的向日葵种子产量大幅降低55.3%至55.2%。 2013年和2014年夏季整个季节的向日葵竞争性处理,相比之下,整个季节的免费杂草处理。杂草无竞争或杂草竞争时期的响应曲线的使用表明,直到播种后6周,向日葵的种子产量和含油量最高,田间没有杂草,杂草/向日葵竞争的关键期在第2至5天之间。播种后6周。在向日葵种子产量,油产量以及无杂草或杂草竞争期间的回归方法中,测试了多项式(线性和二次)和逻辑函数,并拟合了二次函数以估计预期产量,该预期产量与记录的数据相比具有很高的显着性并具有因此,R2的值比其他模型(线性或逻辑模型)的R2最高。它可用于估计杂草与向日葵竞争的关键时期。此外,结果表明,二次方程很重要,并且在2013年和2011年的杂草竞争持续时间中,杂草自由期的R2最高(0.989,0.982)和(0.989,0.984),最高(0.899,0.992)和(0.919,0.994)。根据这些结果,杂草竞争向日葵的关键时期是从播种开始的前六周必须除草,这表明要保持向日葵最大种子和油脂产量的95%和一个星期向日葵播种后可以允许一定数量的杂草侵染,而不会降低种子和油的产量。向日葵种植者应考虑这些信息,以计划针对这一重要作物的杂草综合治理策略。

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