BACKGROUND Sugar loss due to storage rot has a substantial economic impact on the sugar industry. The gradual spread of saprophytic fungi such as Fusarium and Penicillium spp. during storage in beet clamps is an ongoing challenge for postharvest processing. Early detection of shifts in microbial communities in beet clamps is a promising approach for the initiation of targeted countermeasures during developing storage rot. In a combined approach, high-throughput sequencing of bacterial and fungal genetic markers was complemented with cultivation-dependent methods and provided detailed insights into microbial communities colonizing stored roots. These data were used to develop a multi-target qPCR technique for early detection of postharvest diseases. RESULTS The comparison of beet microbiomes from six clamps in Austria and Germany highlighted regional differences; nevertheless, universal indicators of the health status were identified. Apart from a significant decrease in microbial diversity in decaying sugar beets (p ≤ 0.01), a distinctive shift in the taxonomic composition of the overall microbiome was found. Fungal taxa such as Candida and Penicillium together with the gram-positive Lactobacillus were the main disease indicators in the microbiome of decaying sugar beets. In contrast, the genera Plectosphaerella and Vishniacozyma as well as a higher microbial diversity in general were found to reflect the microbiome of healthy beets. Based on these findings, a qPCR-based early detection technique was developed and confirmed a twofold decrease of health indicators and an up to 10,000-fold increase of disease indicators in beet clamps. This was further verified with analyses of the sugar content in storage samples. CONCLUSION By conducting a detailed assessment of temporal microbiome changes during the storage of sugar beets, distinct indicator species were identified that reflect progressing rot and losses in sugar content. The insights generated in this study provide a novel basis to improve current or develop next-generation postharvest management techniques by tracking disease indicators during storage.

中文翻译：

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由微生物组驱动的甜菜收获后疾病的微生物指标鉴定。

背景技术由于贮藏腐烂引起的糖损失对制糖业具有重大的经济影响。腐生真菌如镰刀菌和青霉菌的逐渐传播。在甜菜钳中存储期间，对于收获后的加工来说是一个持续的挑战。对甜菜夹中微生物群落的变化进行早期检测是一种在发展腐烂腐烂过程中启动针对性对策的有前途的方法。通过结合的方法，细菌和真菌遗传标记的高通量测序与依赖培养的方法相辅相成，并为深入研究定居于根部的微生物群落提供了详细的见识。这些数据用于开发多目标qPCR技术，用于早期检测收获后的疾病。结果对来自奥地利和德国的六个钳位的甜菜微生物组进行的比较突出了区域差异。但是，已经确定了健康状况的通用指标。除了腐烂甜菜中微生物多样性的显着降低（p≤0.01）外，还发现了整个微生物组的生物分类组成发生了明显变化。真菌类群如念珠菌和青霉菌以及革兰氏阳性乳杆菌是腐烂甜菜微生物组中的主要疾病指标。相比之下，一般发现Plectosphaerella和Vishniacozyma属以及较高的微生物多样性反映了健康甜菜的微生物组。基于这些发现，开发了一种基于qPCR的早期检测技术，并证实了健康指标下降了两倍，最多可降低10倍，甜菜夹中的疾病指标增加了000倍。通过分析存储样品中的糖含量进一步证实了这一点。结论通过对甜菜贮藏期间微生物组的时间变化进行详细评估，可以鉴定出反映腐烂和糖分损失的不同指示剂种类。本研究中产生的见识为跟踪当前存储过程中的疾病指标提供了新的基础，以改善当前或开发下一代采后管理技术。确定了反映腐烂和糖含量下降的不同指示剂种类。本研究中产生的见识为跟踪当前存储过程中的疾病指标提供了新的基础，以改善当前或开发下一代采后管理技术。确定了反映腐烂和含糖量减少的不同指示剂种类。本研究中产生的见识为跟踪当前存储过程中的疾病指标提供了新的基础，以改善当前或开发下一代采后管理技术。