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The integration of grapes into canned food processing not only effectively extends their shelf life but also preserves their rich nutrition and delightful flavor. This marks a significant advancement toward value-added products and sustainability in the grape industry. This study aims to evaluate the appropriateness of different grape varieties for canned grape production, with a focus on peeling characteristics, sensory quality, and storage properties. Our findings reveal that Kyoho, Takatsuma, and Zuijinxiang grapes stand out as promising candidates, characterized by their ease of peeling, minimal peeling loss, and efficient peeling time. Subsequently, a fuzzy mathematical sensory evaluation approach was employed to assess the taste, flavor, texture, appearance, and size of the peeled grapes from nine grape varieties. Notably, Kyoho (3.87), Takatsuma (3.70), and Zuijinxiang (3.57) grapes exhibited superior sensory scores compared with the other varieties. Regarding storage quality, after 180 days of storage, Kyoho grapes exhibited lower color difference by 12.97–23.50%, higher brittleness by 13.77–19.17%, total phenolic content by 15.73–29.29%, total flavonoid content by 28.54–39.31%, anthocyanin content by 23.81–35.66%, and stronger antioxidant capacity (IC50 DPPH: 24.42–69.55%; IC50 ABTS: 13.27–57.43%) compared with Takatsuma and Zuijinxiang grapes. This comprehensive assessment highlights Kyoho grapes as the most suitable variety for canned grape production, followed by Takatsuma and Zuijinxiang grapes. Their exceptional peeling characteristics, sensory qualities, and notable storage resilience position them as promising candidates for commercialization, presenting substantial potential for widespread acceptance among consumers.
Promoting high-quality development of logistics industry (LHQD) becomes imperative to decrease logistics costs in real economy and intensify endogenous power of economic development. In this paper, we construct an evaluation system consisting of 21 indicators in four dimensions: output scale, operation quality, social contribution and green development. Thereafter, we apply improved entropy weight method, kernel density estimation and Dagum Gini coefficient to carve out spatial and temporal distribution, dynamic evolution and regional differences of LHQD. Finally, we adopt geographical and temporal weighted regression (GTWR) model to reveal heterogeneous effect of each selected factor on LHQD. Outcome indicates: (1) The level of LHQD rose at average annual growth rate of 2.776% between 2004 and 2018, however with significant regional and inter-provincial differences. (2) The LHQD in the whole nation and the three major regions were bipolar or multipolar, with distinctive gradient characteristics. (3) The overall difference of LHQD primarily came from deviation in growth among three major regions, and this difference kept expanding. (4) The impact of various factors on LHQD was characterized by spatial and temporal heterogeneity. Specifically, the positive impact of innovation capacity, digitalization level, foreign direct investment, transportation infrastructure and environmental regulation on development of logistics industry gradually increased with time. It was stronger for eastern region than western region. In contrast, industrial agglomeration's stimulus to LHQD had diminished, and the high-value region of its positive impact had shifted from east to center.
Order acceptance and scheduling (OAS) problems are realistic for enterprises. They have to select the appropriate orders according to their capacity limitations and profit consideration, and then complete these orders by their due dates or no later than their deadlines. OAS problems have attracted significant attention in supply chain management. However, there is an issue that has not been studied well. To our best knowledge, no prior research examines the carbon emission cost and the time-of-use electricity cost in the OAS problems. The carbon emission during the on-peak hours is lower than the one in mid-peak and off-peak hours. However, the electricity cost during the on-peak hours is higher than the one during mid-peak and off-peak hours when time-of-use electricity (TOU) tariff is used. There is a trade-off between sustainable scheduling and the electricity cost. To calculate the objective value, a carbon tax and carbon dioxide emission factor are included when we evaluate the carbon emission cost. The objective function is to maximize the total revenue of the accepted orders and then subtract the carbon emission cost and the electricity cost under different time intervals on a single machine with sequence-dependent setup times and release date. This research proposes a mixed-integer linear programming model (MILP) and a relaxation method of MILP model to solve this problem. It is of importance because the OAS problems are practical in industry. This paper could attract the attention of academic researchers as well as the practitioners.
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