Wang Shusheng, Leus Leen, Van Labeke Marie-Christine, Van Huylenbroeck Johan
Plant Sciences Unit, Applied Genetics and Breeding, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Melle, Belgium.
Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Front Plant Sci. 2018 Oct 23;9:1538. doi: 10.3389/fpls.2018.01538. eCollection 2018.
Rhododendrons are typically known to be calcifuges that cannot grow well in lime soils. Data on lime tolerance of different taxa in are scarce. Habitats of naturally distributed specimens of genus were compiled as Chinese text-based locations from the Chinese Virtual Herbarium. The locations were then geocoded into latitude/longitude pairs and subsequently connected to soil characteristics including pH and CaCO from the Harmonized World Soil Database (HWSD). Using the upper quartile values of pH > 7.2 and CaCO > 2% weight in topsoil as threshold, we predicted the lime tolerant taxa. A dataset of 31,146 specimens including the information on taxonomy, GPS locations and soil parameters for both top- and subsoil was built. The majority of the specimens were distributed in soils with moderately acidic pH and without presence of CaCO. 76 taxa with potential lime tolerance were predicted out of 525 taxa. The large scale data analysis based on combined data of geocoded herbarium specimens and HWSD allows identification of valuable species, subspecies or botanical varieties with potential tolerance to lime soils with higher pH. The predicted tolerant taxa are valuable resources for an in-depth evaluation of lime tolerance or for further use in horticulture and breeding.
杜鹃花通常被认为是嫌钙植物，在石灰性土壤中生长不佳。关于不同分类群耐石灰性的数据很少。从中国虚拟植物标本馆收集了该属自然分布标本的栖息地信息，以基于中文的地点表示。然后将这些地点地理编码为经纬度对，并随后与来自全球土壤数据库（HWSD）的土壤特征（包括pH值和碳酸钙含量）相关联。以表土中pH值>7.2和碳酸钙含量>2%（重量）的上四分位数作为阈值，我们预测了耐石灰分类群。构建了一个包含31146个标本的数据集，其中包括分类学、GPS位置以及表土和底土土壤参数的信息。大多数标本分布在pH值为中等酸性且不存在碳酸钙的土壤中。在525个分类群中，预测出76个具有潜在耐石灰性的分类群。基于地理编码植物标本馆标本和HWSD的组合数据进行的大规模数据分析，能够识别出对高pH值石灰性土壤具有潜在耐受性的有价值的物种、亚种或植物变种。预测出的耐石灰分类群是深入评估耐石灰性或进一步用于园艺和育种的宝贵资源。
