The identification of tomato maturity is significant to extend the fruit shelf life and generate the scientific processing strategy. Tomato maturation is a gradual process, and the internal physicochemical characteristics are most related to maturity states. Merely choosing visual features to identify maturity would cause discriminant errors. This study designed a simple and effective identification method for tomato maturity by integrating color moments and physicochemical indices. The color moments were extracted by an adaptive K-means clustering image processing program, and firmness, soluble solid content and sensory evaluation were measured by professional techniques. The optimal multidimensional index set was formulated according to color moments and physicochemical indices simultaneously. To reduce the confusion between adjacent stages, a novel multinomial logistic regression with kernel clustering (MLRKC) method was designed to identify maturity, and the accuracy was 95.83% for tomato testing set. Moreover, the traditional image features set and some classic methods were applied to verify the performance of proposed method, respectively. Finally, the proposed method was applied to identify the tomatoes in the realistic circumstance. The identification results demonstrated satisfactory performances and promising applications of MLRKC method integrating color moments and physicochemical indices. Practical Applications Tomato is a climacteric fruit which could mature after harvesting. Identification tomato maturity stage is significant to decide the optimal transportation modes, inventory strategies and processing technology. Traditional methods for identifying tomato maturity were high-cost and complicated, which were inefficient for small-scale production. The method proposed in this study could simply the identification steps and reduce the operating cost, and also provide more accurate and valuable information. The investigated theoretical basis could be incorporated into the small farmers and small-scale food processing companies to achieve tomato precision processing with low additional costs. 1 | INTRODUCTION Tomato is rich in nutrients such as vitamins, carotenes, dietary fiber, and is an essential part of human daily diets (Feng, Zhang, Adhikari, & Guo, 2019). As one of the climacteric fruits, tomato has the postharvest maturity characteristics, that is, maturing after harvesting

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Agriproducts have the characteristics of short lifespan and quality decay due to the maturity factor. With the development of e-commerce, high timelines and quality have become a new pursuit for agriproduct online retailing. To satisfy the new demands of customers, reducing the time from receiving orders to distribution and improving agriproduct quality are significantly needed advancements. In this study, we focus on the joint optimization of the fulfillment of online tomato orders that integrates picking and distribution simultaneously within the context of the farm-to-door model. A tomato maturity model with a firmness indicator is proposed firstly. Then, we incorporate the tomato maturity model function into the integrated picking and distribution schedule and formulate a multiple-vehicle routing problem with time windows. Next, to solve the model, an improved genetic algorithm (the sweep-adaptive genetic algorithm, S-AGA) is addressed. Finally, we prove the validity of the proposed model and the superiority of S-AGA with different numerical experiments. The results show that significant improvements are obtained in the overall tomato supply chain efficiency and quality. For instance, tomato quality and customer satisfaction increased by 5% when considering the joint optimization, and the order processing speed increased over 90% compared with traditional GA. This study could provide scientific tomato picking and distribution scheduling to satisfy the multiple requirements of consumers and improve agricultural and logistics sustainability.

Fruit maturity is an essential factor for fresh retailers to make economical distribution scheduling and scientific market strategies. In the context of farm-to-door mode, the fresh retailers could incorporate the postharvest maturity time, picking time and distribution time to deliver high-quality fruits to consumers. This study selects climacteric tomato fruits and formulates a postharvest maturity model by capturing the firmness and soluble solid content (SSC) data during maturing. A joint picking and distribution model is proposed to ensure tomatoes could arrive at consumers within expected maturity time windows. To improve the feasibility of proposed model, an improved genetic algorithm (IGA) is designed to obtain solutions. The results demonstrate that the joint model could optimize the distribution routing to improve consumer satisfaction and reduce the order fulfillment costs. The proposed method provides precise guidance for tomato online retailers by taking advantage of postharvest maturity data, which is conducive to sustainable development of fresh e-ecommerce.

With the rise of vegetable online retailing in recent years, the fulfillment of vegetable online orders has been receiving more and more attention. This paper addresses an integrated optimization model for harvest and farm-to-door distribution scheduling for vegetable online retailing. Firstly, we capture the perishable property of vegetables, and model it as a quadratic postharvest quality deterioration function. Then, we incorporate the postharvest quality deterioration function into the integrated harvest and farm-to-door distribution scheduling and formulate it as a quadratic vehicle routing programming model with time windows. Next, we propose a genetic algorithm with adaptive operators (GAAO) to solve the model. Finally, we carry out numerical experiments to verify the performance of the proposed model and algorithm, and report the results of numerical experiments and sensitivity analyses.

The voice of new energy is increasing with environment pollution growing problem. Wind energy regards as a new energy with no pollution and wide-getting, so it gets full attentions from all the world, and, installed capacity is increasing. In 2014, China promulgated "opinions on further deepening the reform of electric power system" ,opened power-sold side and made higher requirements in electric price management .This article is based on Wind Electricity's Present Situation under the Electric Power Reform ,has searched the problem in wind power and put forward measures. Research BackgroundTo build a beautiful China, this four aspects of the energy revolution in Energy consumption, energy supply, energy technology and energy system mean that Chinese energy stages need fundamental changes and have to take the road of sustainable development. Modern, high-quality, high-effect wind-electric equipment manufacturing industry is a guarantee in sustainable development of wind power industry.April 18, 2014, Premier Li Keqiang who hosted the meeting of the new National Energy Commission, required to step on current and foresight.Promise positively to promote energy production and consumption change, going a clean, efficient, safe and sustainable energy development way. Central Committee of the CPC, the State Council thought highly of scientific establishment of energy strategic planning, promoting efficient, safe and sustainable energy development.In 13th Five-Year the national energy planning meeting, Wu Xinxiong emphasized the sharp increase in the proportion of renewable energy. Insisting on both centralization and distribution, centralizationally place sending with consumptive combining.in the rich resource region, Plan the construction of large wind power base and photovoltaic base, n other region, accelerate the exploitation of wind dispersed and distributed photovoltaic power generation. By 2020, wind power and photovoltaic power generation capacity is getting Kw to over 200 million and 100 million. The price of wind power is equipped with Coal's and the photovoltaic power generation's is as the Grid sales price.Chinese power reform firstly broke the vertical integration mode, into a single buyer mode, then to the wholesale competition mode and finally realized the retail competition mode. In2002 Chinese power market was going to a new strategy to split, state power company power plant and power grid separated, split, restructuring as the two power grid companies, five national power corporation and four FuYe group company. Research SignificanceAdjust Energy Structure Improve the Environment Quality. China's energy consumption accounts for more than 10% of the world. In the meantime, the primary energy consumption accounts for about 70%, more than 40 percentage points higher than the world average. Sulfur dioxide and soot emissions caused by coal accounted for about 70% of the total emissions -70%,