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Soil suitability analysis and evaluation of pistachio orchard farming, using canonical multivariate analysis

机译:土壤适宜性分析与开心果园农业的评价,采用规范多变量分析

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Soil properties and crop yields are strongly interrelated. Identifying the relation can leads to better management of cultivation and land suitability evaluation. Some difficulties related to statistically analyzing the soil properties, especially in relation with the crops and water, arises from the fact of their high variability and inter correlation, which causes the multicollinearity problems. Adequate choice and use of multivariate statistical methods is appropriate to approach these areas of investigation. This study deals with the relations and interdependencies of soil physio-chemical attributes and pistachio (Pistacia vera L.) yield, as the most important commercial nut crop of Iran and one of the most worldwide. The study area is the pistachio orchard farms of Anar region in Rafsanjan County, Kerman, Iran; and the employed canonical multivariate methods are redundancy analysis (RDA) and discriminant analysis (DA). Six orchards were chosen with the same managerial procedures, pistachio cultivars (Owhadi) and tree ages. But, due to the aim of distinguishing influential soil properties, the vegetative growth and pistachio yields were different. Each orchard then was divided to two suitable and unsuitable parts, based on the actually measured yields. In each part, three replicates of soil sampling (in to depths of 0-50 and 50-100 cm) and three trees for eachever were considered in order to determining the pistachio yields. To explore the interrelationships between soil properties, orchard suitable/unsuitable parts and yields and distinguishing misclassified orchards based on the yield parameter and vegetative growth, the canonical multivariate RDA was employed. Results showed a relatively strong correspondence between yield and soil properties. Clay, EC, K and B were negatively related and sand and CaCO3 significantly positive correlated and altogether explained 100% of yield total variation. The multivariate DA then adopted to reclassify the orchard samples into two performance groups based on the variations of soil attributes. Results indicated two influential variables of clay and EC in distinguishing land suitability for pistachio farming, were able to classify 80.5% of orchards correctly (73.7% to suitable orchards and 88.2% to unsuitable ones). Overally, results showed a significant difference between soil properties in suitable and unsuitable areas, as well as a significant relationship between some soil properties and the yield of pistachio. Findings, applicably recommend that site suitability for optimal pistachio cultivation can satisfactorily be evaluated using only few and easy determining soil properties, throughout canonical discriminant functions of appropriate multivariate analysis.
机译:土壤性质和作物产量强烈相互关联。确定关系可以导致培养和土地适用性评估的更好管理。与统计分析土壤性质有关的一些困难,尤其是与作物和水有关,这是由于其高变异性和相关性的事实,这导致了多种性问题。足够的选择和使用多元统计方法是适合接近这些调查领域的。本研究涉及土壤物理化学属性和开心(Pistacia Vera L.)产量的关系和相互依赖性,作为伊朗最重要的商业螺母作物和最全球范围之一。该研究区是伊朗克尔曼·克尔曼·克拉曼郡的奥尔地区的开心园农场;并且所用的规范多元方法是冗余分析(RDA)和判别分析(DA)。选择了六个果园,并选择了同样的管理程序,开心素品种(Owhadi)和树龄。但是,由于具有不同的土壤性质的目的,营养生长和开心产量不同。然后基于实际测量的产量,每个果园分为两个合适的和不合适的部件。在每个部分中,考虑了三种土壤采样(深度为0-50和50-100cm)和三棵树以确定开孔产量。为了探讨土壤性质之间的相互关系,果园合适/不合适的零件和产量和区分错误分类的果园基于产量参数和营养生长,所用规范多元RDA。结果表明产量和土壤性质之间的对应性相对较强。粘土,欧氏,K和B是带负相关的,砂和CaCO3显着正相关,并且完全解释了100%的产量总变化。然后采用多变量DA根据土地属性的变化将果园样本重新分类为两个性能组。结果表明,粘土和欧共体的两个有影响力的变量在区别开心养殖的土地适用性,能够将80.5%的果园(73.7%到合适的果园和88.2%到不合适的果园分类)。过度地,结果在合适的和不合适的区域中的土壤性质和某些土壤性质与开心的产量之间存在显着差异。调查结果,适用于,在适当多变量分析的规范判别功能的情况下,可以仅使用少数且易于确定的土壤性能来评估最佳开心培养的现场适用性。

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