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“Prata”香蕉(Musa spp.)叶片营养稳健诊断的平衡设计。

Balance design for robust foliar nutrient diagnosis of "Prata" banana (Musa spp.).

机构信息

Federal University of Ceará, Department of Soil Science, Fortaleza, 60440-554, Ceará, Brazil.

Federal University of Viçosa, Department of Soils, Viçosa, 35670-900, Minas Gerais, Brazil.

出版信息

Sci Rep. 2018 Oct 9;8(1):15040. doi: 10.1038/s41598-018-32328-y.

Abstract

The "Cavendish" and "Prata" subgroups represent respectively 47% and 24% of the world banana production. Compared to world average progressing from 10.6 to 20.6 t ha between 1961 and 2016, and despite sustained domestic demand and the introduction of new cultivars, banana yield in Brazil has stagnated around 14.5 t ha mainly due to nutrient and water mismanagement. "Prata" is now the dominant subgroup in N-E Brazil and is fertigated at high costs. Nutrient balances computed as isometric log-ratios (ilr) provide a comprehensive understanding of nutrient relationships in the diagnostic leaf at high yield level by combining raw concentration data. Although the most appropriate method for multivariate analysis of compositional balances may be less efficient due to non-normal data distribution and limited nutrient mobility in the plant, robustness of the nutrient balance approach could be improved using Box-Cox exponents assigned to raw foliar concentrations. Our objective was to evaluate the accuracy of nutrient balances to diagnose fertigated "Prata" orchards. The dataset comprised 609 observations on fruit yields and leaf tissue compositions collected from 2010 to 2016 in Ceará state, N-E Brazil. Raw nutrient concentration ranges were ineffective as diagnostic tool due to considerable overlapping of concentration ranges for low- and high-yielding subpopulations at cutoff yield of 40 Mg ha. Nutrient concentrations were combined into isometric log-ratios (ilr) and normalized by Box-Cox corrections between 0 and 1 which may also account for restricted nutrient transfer from leaf to fruit. Despite reduced ilr skewness, Box-Cox coefficients did not improve model robustness measured as the accuracy of the Cate-Nelson partition between yield and the multivariate distance across ilr values. Sensitivity was 94%, indicating that low yields are attributable primarily to nutrient imbalance. There were 148 false-positive specimens (high yield despite nutrient imbalance) likely due to suboptimal nutrition, contamination, or luxury consumption. The profitability of "Prata" orchards could be enhanced by rebalancing nutrients using ilr standards with no need for Box-Cox correction.

摘要

“Cavendish”和“Prata”亚组分别代表世界香蕉产量的 47%和 24%。与 1961 年至 2016 年期间世界平均水平从 10.6 吨/公顷增长到 20.6 吨/公顷相比,尽管国内需求持续增长且引入了新的品种,但巴西的香蕉产量仍停滞在 14.5 吨/公顷左右,主要原因是养分和水分管理不当。“Prata”现在是巴西东北部的主要亚组,其施肥成本很高。养分平衡以等比对数(ilr)的形式计算,可以通过将原始浓度数据组合起来,全面了解高产水平下诊断叶片中的养分关系。尽管最适合多元分析组成平衡的方法可能由于数据分布非正态和植物中养分迁移有限而效率较低,但通过为原始叶片浓度分配 Box-Cox 指数,可以提高养分平衡方法的稳健性。我们的目标是评估养分平衡诊断施肥“Prata”果园的准确性。该数据集包含 2010 年至 2016 年在巴西东北部塞阿拉州收集的 609 个果实产量和叶片组织成分观测值。由于在 40 Mg ha 的临界产量下,低产和高产亚群的浓度范围有很大重叠,因此原始养分浓度范围作为诊断工具效果不佳。养分浓度被组合成等比对数(ilr),并通过 Box-Cox 校正在 0 到 1 之间归一化,这也可能解释了从叶片到果实的养分转移受限。尽管 ilr 偏度降低,但 Box-Cox 系数并没有提高模型稳健性,以 Cate-Nelson 分区的准确性衡量,该分区表示产量和 ilr 值之间的多元距离。敏感性为 94%,表明低产量主要归因于养分失衡。有 148 个假阳性标本(尽管养分失衡但产量高),可能是由于营养不足、污染或奢侈消费。使用 ilr 标准并无需 Box-Cox 校正来重新平衡养分,可以提高“Prata”果园的盈利能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e756/6177482/1db38f07d788/41598_2018_32328_Fig1_HTML.jpg

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