利用电子鼻和SPAD法测定番石榴叶片黄酮和氮含量

IF 1.1 Q3 AGRONOMY
Bambang Marhaenanto, Putri Wahyulian Aningtyas, Bayu Taruna Widjaja Putraa, Dedy Wirawan Soedibyo, Wahyu Nurkholis Hadi Syahputra
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引用次数: 0

摘要

类黄酮是一种抗氧化剂,广泛用于治疗各种人类疾病。除了番石榴果实,番石榴叶中也含有类黄酮。测定叶片类黄酮含量通常涉及化学分析,耗时且成本高。本研究旨在利用电子鼻(配备9个不同的MQ传感器)和SPAD-502叶绿素计捕获的两种不同现象(气体和视觉),快速估计新鲜和提取叶片中的类黄酮和氮含量。本研究还确定了番石榴中黄酮类化合物和氮的含量与叶片变异的选择之间的关系。总共应用了9种机器学习算法来评估从电子鼻和SPAD-502 m获得的数据作为10个输入特征。结果表明:(1)使用从新鲜叶片中获取的10个输入特征对番石榴类黄酮和氮含量的分类和估计比使用特征重要排序和提取的番石榴叶更准确。人工神经网络多层感知器(ANN MLP)是一种对类黄酮和氮含量进行分类和估计的机器学习算法,其决定系数(R2)在0.76 ~ 0.96之间;(2)实验室分析表明,番石榴叶中类黄酮含量与氮含量之间没有正相关关系;(3)选择叶数1 ~ 5可确定黄酮含量在最优-高范围内,选择已完全张开的芽叶数3可估计氮状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Estimating Flavonoid and Nitrogen Status of Guava Leaves Using E-Nose and SPAD Meter

Estimating Flavonoid and Nitrogen Status of Guava Leaves Using E-Nose and SPAD Meter

Estimating Flavonoid and Nitrogen Status of Guava Leaves Using E-Nose and SPAD Meter

Flavonoids are a type of antioxidants widely used to treat various human diseases. Apart from guava fruits, flavonoids are also found in the leaves. Determining the leaf flavonoid content generally involves chemical analysis, which is time-consuming and costly. This study aimed to estimate quickly the flavonoid and nitrogen contents in fresh and extracted leaves using two different phenomena: (gas and vision) captured by an e-nose (equipped with nine different MQ sensors) and a SPAD-502 chlorophyll meter. This study also determined the relationship between flavonoids and nitrogen in guava plants and the selection of leaf variations, which contained the maximum levels of these compounds. A total of nine machine learning algorithms were applied to evaluate the data obtained from both the e-nose and SPAD-502 m as ten input features. The results showed that: (1) using ten input features obtained from fresh leaf samples provided better accuracy in classifying and estimating both flavonoid and nitrogen contents rather than using feature important ranking and extracted guava leaves. An artificial neural network—multilayer perceptron (ANN MLP) is a machine learning algorithm that provided maximum accuracy in classifying and estimating flavonoid and nitrogen contents with coefficient determination (R2) ranging between 0.76 and 0.96; (2) laboratory analysis did not indicate a positive relationship between flavonoid and nitrogen contents in guava leaves; and (3) selection of leaf numbers 1–5 was appropriate to ascertain flavonoid content in the optimum–high range, while the leaf number 3 from shoots that have opened completely to estimate the N status can be selected.

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来源期刊
CiteScore
3.80
自引率
0.00%
发文量
24
期刊介绍: The main objective of this initiative is to promote agricultural research and development. The journal will publish high quality original research papers and critical reviews on emerging fields and concepts for providing future directions. The publications will include both applied and basic research covering the following disciplines of agricultural sciences: Genetic resources, genetics and breeding, biotechnology, physiology, biochemistry, management of biotic and abiotic stresses, and nutrition of field crops, horticultural crops, livestock and fishes; agricultural meteorology, environmental sciences, forestry and agro forestry, agronomy, soils and soil management, microbiology, water management, agricultural engineering and technology, agricultural policy, agricultural economics, food nutrition, agricultural statistics, and extension research; impact of climate change and the emerging technologies on agriculture, and the role of agricultural research and innovation for development.
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