[Food matching based on herbal properties of formulas in "Treatise on Febrile Diseases"].

Based on databases for herbal properties of formulas and foods recorded in "Treatise on Febrile Diseases", a case study was conducted for the food matching method according to herbal properties of formulas in "Treatise on Febrile Diseases". The result show that the method was technically feasible once the herbal properties of foods were determined. Moreover, according to herbal properties of target formulas, the compositions of foods were effectively defined.

[Design method of constitution regulating and healthcare foods based on medicinal property combination mode].

Currently, the herbal prescription therapy for corresponding constitutional diseases is a common constitution regulating method. This method has an obvious effect in treating and regulating constitution-related diseases. However, for people who do not have disease, they prefer to regulate constitution with dietary therapy.

[Formula method of medicated diet based on medicinal property combination patterns].

To propose a formula method of medicated diet based on medicinal property combination patterns in this paper under the context of lack of innovation in medicated diets. By analyzing the property combination patterns of traditional Chinese medicine and commonly used foods recorded in the pharmacopoeia, medicated diet formulae were optimized by using the greedy algorithm, with the property combination patterns of classical formulae based on the syndrome differentiation and treatment. In this paper, the Baihu Rensheng decoction, which is a classical formula for treating lung and stomach heat-derived diabetes, was taken for example in the formula design.

[Design of traditional Chinese medicines with antihypertensive components based on medicinal property combination modes].

Multi-component traditional Chinese medicines are an innovative research mode for traditional Chinese medicines. Currently, there are many design methods for developing multi-component traditional Chinese medicines, but their common feature is the lack of effective connection of the traditional Chinese medicine theory. In this paper, the authors discussed the multi-component traditional Chinese medicine design methods based on medicinal property combination modes, provided the combination methods with the characteristics of traditional Chinese medicine for the prescription combinations, and proved its feasibly with hypertension cases.

[Study on self-similarity of property combination mode of traditional Chinese medicines].

The combination of medicinal properties refers to expression forms of elements with active properties combined according to a specific sequence. The mode of medicinal property combination refers to the compatible relationship multiple medicinal property combinations. In this paper, based on the mode, safflower, Taohong Siwu decoction, Xuefu Zhuyu decoction and Buyang Huanwu decoction were taken for example to study the characteristics of the compatibility among single herb, herbal pairs and prescriptions.

Rapid Identification of Asteraceae Plants with Improved RBF-ANN Classification Models Based on MOS Sensor E-Nose.

Plants from Asteraceae family are widely used as herbal medicines and food ingredients, especially in Asian area. Therefore, authentication and quality control of these different Asteraceae plants are important for ensuring consumers' safety and efficacy. In recent decades, electronic nose (E-nose) has been studied as an alternative approach.

Identification of chinese herbal medicines from zingiberaceae family using feature extraction and cascade classifier based on response signals from e-nose.

Identification of Chinese herbal medicines (CHMs) by human experience is often inaccurate because individual ability and external factors may influence the outcome. However, it might be promising to employ an electronic nose (E-nose) to identify them. This paper presents a rapid and reliable method for identification of ten different species of CHMs from Zingiberaceae family based on their response signals from E-nose.