University of Wisconsin-Madison, Department of Horticulture, Madison, Wisconsin, United States of America.
Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Aguascalientes, México.
PLoS One. 2019 Sep 25;14(9):e0222451. doi: 10.1371/journal.pone.0222451. eCollection 2019.
Cranberry (Vaccinium macrocarpon L.) fruit quality traits encompass many properties. Although visual appearance and fruit nutritional constitution have usually been the most important attributes, cranberry textural properties such as firmness have recently gained importance in the industry. Fruit firmness has become a quality standard due to the recent demand increase for sweetened and dried cranberries (SDC), which are currently the most profitable cranberry product. Traditionally, this trait has been measured by the cranberry industry using compression tests; however, it is poorly understood how fruit firmness is influenced by other characteristics.
In this study, we developed a high-throughput computer-vision method to measure the internal structure of cranberry fruit, which may in turn influence cranberry fruit firmness. We measured the internal structure of 16 cranberry cultivars measured over a 40-day period, representing more than 3000 individual fruit evaluated for 10 different traits. The internal structure data paired with fruit firmness values at each evaluation period allowed us to explore the correlations between firmness and internal morphological characteristics.
Our study highlights the potential use of internal structure and firmness data as a decision-making tool for cranberry processing, especially to determine optimal harvest times and ensure high quality fruit. In particular, this study introduces novel methods to define key parameters of cranberry fruit that have not been characterized in cranberry yet. This project will aid in the future evaluation of cranberry cultivars for in SDC production.
蔓越莓（Vaccinium macrocarpon L.）的果实品质特性涵盖了许多属性。尽管外观和果实营养成分通常是最重要的属性，但蔓越莓的质地特性，如硬度，最近在行业中变得越来越重要。由于对加糖和干燥蔓越莓（SDC）的需求增加，果实硬度已成为质量标准，SDC 目前是最盈利的蔓越莓产品。传统上，该行业通过压缩测试来测量该特性；然而，人们对其他特性如何影响果实硬度知之甚少。
在这项研究中，我们开发了一种高通量的计算机视觉方法来测量蔓越莓果实的内部结构，这可能反过来影响蔓越莓果实的硬度。我们测量了 16 个蔓越莓品种的内部结构，在 40 天的时间内进行了测量，代表了超过 3000 个单个果实，评估了 10 个不同的特性。内部结构数据与每个评估期的果实硬度值相结合，使我们能够探索硬度与内部形态特征之间的相关性。
我们的研究强调了内部结构和硬度数据作为蔓越莓加工决策工具的潜力，特别是确定最佳收获时间和确保高质量果实。特别是，本研究介绍了定义蔓越莓果实关键参数的新方法，这些参数在蔓越莓中尚未得到描述。该项目将有助于未来对 SDC 生产中蔓越莓品种的评估。
