In this article, we establish a new approach for removing natural growth trends from tree-ring samples, also called detrending. We demonstrate this approach using Ocotea porosa (Nees & Mart) Barroso trees. Nondestructive samples were collected in General Carneiro city, located in the Brazilian southern region (Paraná state). To remove natural tree growth trends, principal components analysis (PCA) was applied on the tree-ring series as a new detrending method. From this, we obtained the tree-ring indices by reconstructing the tree-ring series without the first principal component (PC), which we expect to represent the natural growth trend. The performance of this PCA method was then compared to other detrending methods commonly used in dendrochronology, such as the cubic spline method, negative exponential or linear regression curve, and the regional curve standardization method. A comparison of these methods showed that the PCA detrending method can be used as an alternative to traditional methods since (1) it preserves the low-frequency variance in the 566-year chronology and (2) represents an automatic way to remove the natural growth trends of all individual measurement series at the same time. Moreover, when implemented using the alternating least squares (ALS) method, the PCA can deal with tree-ring series of different lengths.

在本文中，我们建立了一种从树轮样本中去除自然生长趋势的新方法，也称为去趋势。我们使用Ocotea porosa (Nees & Mart) Barroso演示了这种方法树木。在位于巴西南部地区（巴拉那州）的卡内罗将军市收集了无损样品。为了消除自然树木的生长趋势，主成分分析 (PCA) 被应用于树轮系列作为一种新的去趋势方法。由此，我们通过重建没有第一主成分 (PC) 的树轮系列获得了树轮指数，我们期望它代表自然增长趋势。然后将此 PCA 方法的性能与树年代学中常用的其他去趋势方法进行比较，例如三次样条方法、负指数或线性回归曲线以及区域曲线标准化方法。这些方法的比较表明 PCA 去趋势方法可以用作传统方法的替代方法，因为 (1) 它保留了 566 年年表中的低频方差，以及 (2) 代表了一种消除自然增长的自动方法同时显示所有单个测量系列的趋势。此外，当使用交替最小二乘 (ALS) 方法实现时，PCA 可以处理不同长度的树轮系列。