Broccoli has been consumed around the world in various ways; either raw, blanched, frozen, dehydrated or fermented; however, functional foods and nutraceuticals are currently being designed and marketed from broccoli, through the extraction of compounds such as sulforaphane, which according to several studies and depending on its bioavailability has a protective effect on some types of cancer. Likewise, several food technologies are reported to seek to offer innovative foods to increasingly careful and critical consumers, ensuring that they retain their nutritional and sensory attributes even after processing and that they are also safe. In this sense, studies on the effect of processing on compounds of interest to health are of great relevance. Therefore, this article presents an overview on the study of traditionally consumed broccoli and the design of new products from the use of agro-industrial residues that, due to their high content of fiber and fitochemical compounds, can benefit the quality of life of the human population.

Some developmental projects are created by people-private partnerships (PPP), particularly where recovery is acquirable by levying the users. Such PPPs are successful for construction of roads, bridges, running toilet facilities and conveyance facility in mode of use and pay. Likewise, public-scientist partnerships (PSPs) will be successful, where monitored impacts can be used to derive benefit. But such example cases are not so popular in utilizing new research results and derive benefits from natural resources and enhance productivity. There is a demand for similar partnership projects in research area. In this study modality of the PSP to create boost engine for natural resource conservation and bring economic prosperity is established. A novel PSP launch was synthesized on useful food crop viz. finger millet (Elusiane corcona (l)), which has been known since long past, and now is regaining popularity. It was possible to enhance additional annual production of 5.755 million tonnes of finger millet grain, equivalent to additional income of Rs 11,510 crores. Against this the scientist partnership share was 0.49x million tonnes grain and economic equivalency of Rs 992 crores, which was just 7–8%, with same level of input in agriculture. Additional benefits were sustainability of production and resources consecration, reduction of greenhouse gas emission (GHGs), particularly nitrous oxide (N₂O), largely emanating from agriculture and responsible for depletion of ozone layer. The finger millet stiff stem will be useable for production of ply-board filling material that will be innovative building material for housing and infrastructure developments and making furniture.

This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.