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基于紫外线B辐射对羽衣甘蓝叶片三维结构中酚类物质含量的预测

Prediction of Phenolic Contents Based on Ultraviolet-B Radiation in Three-Dimensional Structure of Kale Leaves.

作者信息

Yoon Hyo In, Kim Jaewoo, Oh Myung-Min, Son Jung Eek

机构信息

Department of Agriculture, Forestry and Bioresources, Seoul National University, Seoul, South Korea.

Division of Animal, Horticultural and Food Sciences, Chungbuk National University, Cheongju, South Korea.

出版信息

Front Plant Sci. 2022 Jun 9;13:918170. doi: 10.3389/fpls.2022.918170. eCollection 2022.

Abstract

Ultraviolet-B (UV-B, 280-315 nm) radiation has been known as an elicitor to enhance bioactive compound contents in plants. However, unpredictable yield is an obstacle to the application of UV-B radiation to controlled environments such as plant factories. A typical three-dimensional (3D) plant structure causes uneven UV-B exposure with leaf position and age-dependent sensitivity to UV-B radiation. The purpose of this study was to develop a model for predicting phenolic accumulation in kale ( L. var. ) according to UV-B radiation interception and growth stage. The plants grown under a plant factory module were exposed to UV-B radiation from UV-B light-emitting diodes with a peak at 310 nm for 6 or 12 h at 23, 30, and 38 days after transplanting. The spatial distribution of UV-B radiation interception in the plants was quantified using ray-tracing simulation with a 3D-scanned plant model. Total phenolic content (TPC), total flavonoid content (TFC), total anthocyanin content (TAC), UV-B absorbing pigment content (UAPC), and the antioxidant capacity were significantly higher in UV-B-exposed leaves. Daily UV-B energy absorbed by leaves and developmental age was used to develop stepwise multiple linear regression models for the TPC, TFC, TAC, and UAPC at each growth stage. The newly developed models accurately predicted the TPC, TFC, TAC, and UAPC in individual leaves with > 0.78 and normalized root mean squared errors of approximately 30% in test data, across the three growth stages. The UV-B energy yields for TPC, TFC, and TAC were the highest in the intermediate leaves, while those for UAPC were the highest in young leaves at the last stage. To the best of our knowledge, this study proposed the first statistical models for estimating UV-B-induced phenolic contents in plant structure. These results provided the fundamental data and models required for the optimization process. This approach can save the experimental time and cost required to optimize the control of UV-B radiation.

摘要

紫外线B(UV-B,280 - 315纳米)辐射是一种可提高植物生物活性化合物含量的诱导因子。然而,产量不可预测是紫外线B辐射应用于植物工厂等可控环境的一个障碍。典型的三维(3D)植物结构会导致紫外线B照射不均匀,且叶片位置和年龄对紫外线B辐射的敏感性不同。本研究的目的是建立一个根据紫外线B辐射截获量和生长阶段预测羽衣甘蓝(L. var.)中酚类物质积累的模型。在植物工厂模块下生长的植株,在移栽后第23、30和38天,用峰值为310纳米的紫外线B发光二极管照射紫外线B辐射6或12小时。利用三维扫描植物模型的光线追踪模拟对植株中紫外线B辐射截获的空间分布进行了量化。暴露于紫外线B的叶片中总酚含量(TPC)、总黄酮含量(TFC)、总花青素含量(TAC)、紫外线B吸收色素含量(UAPC)和抗氧化能力显著更高。叶片每日吸收的紫外线B能量和发育年龄被用于建立每个生长阶段TPC、TFC、TAC和UAPC的逐步多元线性回归模型。新开发的模型在三个生长阶段的测试数据中,能准确预测单叶中的TPC、TFC、TAC和UAPC,相关系数>0.78,归一化均方根误差约为30%。TPC、TFC和TAC的紫外线B能量产量在中间叶片中最高,而UAPC的紫外线B能量产量在最后阶段的幼叶中最高。据我们所知,本研究提出了首个用于估计植物结构中紫外线B诱导酚类物质含量的统计模型。这些结果提供了优化过程所需的基础数据和模型。这种方法可以节省优化紫外线B辐射控制所需的实验时间和成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5bd/9228028/e7b33572e88a/fpls-13-918170-g001.jpg

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