We took distribution visualization of chlorophyll content in apple leaves to estimate the nutrient content and growth levels of apple leaves. 130 mature and non-destructive apple leaves were collected, and imaging spe...We took distribution visualization of chlorophyll content in apple leaves to estimate the nutrient content and growth levels of apple leaves. 130 mature and non-destructive apple leaves were collected, and imaging spectroscopy data were collected by SOC710VP hyperspectral imager. The chlorophyll content of the leaves was determined on the spectral information of the leaves. After pre-processing, we took linear wavelength stepwise regression method to choose the sensitive wavelength of chlorophyll content. And then we established partial least squares, principal component analysis and stepwise regression model. Finally, the chlorophyll content distribution visualization was realized. The results showed that the sensitive wavelengths of the chlorophyll content were 712.50 nm, 509.95 nm, 561.22 nm, 840.62 nm, 696.67 nm and 987.91 nm. The R2, RMSE, RE of the optical chlorophyll content estimation model, and the principal component analysis regression model, were 0.800, 0.319 and 26.4%. The chlorophyll content of each pixel on the hyperspectral image of apple leaves was calculated by the best estimation model and we completed the visualization distribution of chlorophyll content, which provided a technical support for the rapid detection of nutrient distribution.展开更多
市场营销领域对数据的研究正在逐渐地从传统的单模态数据向信息更加丰富的多模态数据过渡,回顾和展望市场营销研究经历的多模态数据形塑过程具有学术价值和实践意义。笔者基于Web of Science与中国知网数据库资源(2005—2025),运用CiteS...市场营销领域对数据的研究正在逐渐地从传统的单模态数据向信息更加丰富的多模态数据过渡,回顾和展望市场营销研究经历的多模态数据形塑过程具有学术价值和实践意义。笔者基于Web of Science与中国知网数据库资源(2005—2025),运用CiteSpace和内容分析两种研究工具,从研究主题、理论基础及研究方法等维度,对筛选自核心期刊的407篇相关研究样本文献进行了系统梳理和深度解构,呈现出多模态数据对市场营销研究的形塑:研究主题的演进主轴为“静态内容呈现”—“动态互动参与”—“长期价值转化”;理论基础展现由市场营销学扩展到信息科学、传播学、心理学等多学科的相互交叉融合;研究方法趋向以人工智能计算为主导,辅之定性阐释的多元化格局;基于样本文献研究构建的多模态数据形塑市场营销研究的整合性理论框架,系统揭示多模态信息影响力的完整作用机制;涵盖理论深化、方法创新、应用拓展等一系列拓展预景均可宏观勾勒。研究结论为该领域的理论深化与实践创新提供了整合性的认知框架与前瞻性指引。展开更多
文摘We took distribution visualization of chlorophyll content in apple leaves to estimate the nutrient content and growth levels of apple leaves. 130 mature and non-destructive apple leaves were collected, and imaging spectroscopy data were collected by SOC710VP hyperspectral imager. The chlorophyll content of the leaves was determined on the spectral information of the leaves. After pre-processing, we took linear wavelength stepwise regression method to choose the sensitive wavelength of chlorophyll content. And then we established partial least squares, principal component analysis and stepwise regression model. Finally, the chlorophyll content distribution visualization was realized. The results showed that the sensitive wavelengths of the chlorophyll content were 712.50 nm, 509.95 nm, 561.22 nm, 840.62 nm, 696.67 nm and 987.91 nm. The R2, RMSE, RE of the optical chlorophyll content estimation model, and the principal component analysis regression model, were 0.800, 0.319 and 26.4%. The chlorophyll content of each pixel on the hyperspectral image of apple leaves was calculated by the best estimation model and we completed the visualization distribution of chlorophyll content, which provided a technical support for the rapid detection of nutrient distribution.
文摘市场营销领域对数据的研究正在逐渐地从传统的单模态数据向信息更加丰富的多模态数据过渡,回顾和展望市场营销研究经历的多模态数据形塑过程具有学术价值和实践意义。笔者基于Web of Science与中国知网数据库资源(2005—2025),运用CiteSpace和内容分析两种研究工具,从研究主题、理论基础及研究方法等维度,对筛选自核心期刊的407篇相关研究样本文献进行了系统梳理和深度解构,呈现出多模态数据对市场营销研究的形塑:研究主题的演进主轴为“静态内容呈现”—“动态互动参与”—“长期价值转化”;理论基础展现由市场营销学扩展到信息科学、传播学、心理学等多学科的相互交叉融合;研究方法趋向以人工智能计算为主导,辅之定性阐释的多元化格局;基于样本文献研究构建的多模态数据形塑市场营销研究的整合性理论框架,系统揭示多模态信息影响力的完整作用机制;涵盖理论深化、方法创新、应用拓展等一系列拓展预景均可宏观勾勒。研究结论为该领域的理论深化与实践创新提供了整合性的认知框架与前瞻性指引。
