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Table grape is one of the most important horticultural crops in China. However, quality and safety have become major constraints for the further development of the Chinese table grape industry, which is dominated by small‐scale vinegrowers. Strategic partnership has been regarded as an effective mechanism to manage the supply chain. The purpose of this paper is to examine the impact of a supply chain model based on different strategic partnerships on the effect of safety and quality control and small‐scale vinegrowers' performance.

The field survey was performed in seven representative districts in China, including Inner Mongolia, Gansu, Tianjin, Liaoning, Shandong, Jiangsu and Zhejiang Provinces. A semi‐structured interview was adopted as the data collection method. Both quantitative and qualitative data were generated and analyzed in this research. All quantitative analyses were conducted using EXCEL 2003 version and a comparative analysis was conducted to test the hypotheses.

The results show that modern supply chains are more efficient than the traditional one in improving the effect of safety and quality control and small‐scale vinegrowers' performance.

This paper first identified different models of table grape supply chain based on different strategic partnerships, and then analyzed the impact of supply chain model on the effect of quality and safety control and small‐scale vinegrowers' performance. It concludes with some policy suggestions relative to further development of the table grape industry in China.

The purpose of this paper is to estimate the technical efficiency of Chinese table grape wholesalers and subsequently to examine the degree to which the calculated efficiency correlates with a set of explanatory variables.

A two-stage procedure is applied in this paper. First, a non-parametric data envelopment analysis (DEA) technique is applied to investigate the degree of technical efficiency for Chinese table grape wholesalers. Second, Tobit regression is used to analyze the factors influencing technical efficiency.

Research results reveal that the mean technical efficiency of the sample is 0.544 and 0.860 under constant returns scale (CRS) and VRS assumptions, respectively, and the scale efficiency (SE) is 0.620. The variables of experiences, number of grape varieties on sale, daily selling volumes and fixed sale ratio have a significant effect on technical efficiency, while the other exogenous variables do not affect the efficiency in any significant way.

The findings of this research are specific to table grape wholesalers in China, however, the method used in this study is transferrable and applicable to the study of similar problems in others countries.

This research has yielded some interesting and original insights into the efficiency level of Chinese grape wholesalers and the factors that influence the level of efficiency. The findings have practical implications for Chinese agriculture policy makers, and are able to stimulate further research of a similar type in the international agricultural research community.

The purpose of this paper is to develop a common remaining shelf life prediction model that is generally applicable for postharvest table grape using an optimized radial basis function (RBF) neural network to achieve more accurate prediction than the current shelf life (SL) prediction methods.

First, the final indicators (storage temperature, relative humidity, sensory average score, peel hardness, soluble solids content, weight loss rate, rotting rate, fragmentation rate and color difference) affecting SL were determined by the correlation and significance analysis. Then using the analytic hierarchy process (AHP) to calculate the weight of each indicator and determine the end of SL under different storage conditions. Subsequently, the structure of the RBF network redesigned was 9-11-1. Ultimately, the membership degree of Fuzzy clustering (fuzzy c-means) was adopted to optimize the center and width of the RBF network by using the training data.

The results show that this method has the highest prediction accuracy compared to the current the kinetic–Arrhenius model, back propagation (BP) network and RBF network. The maximum absolute error is 1.877, the maximum relative error (RE) is 0.184, and the adjusted R² is 0.911. The prediction accuracy of the kinetic–Arrhenius model is the worst. The RBF network has a better prediction accuracy than the BP network. For robustness, the adjusted R² are 0.853 and 0.886 of Italian grape and Red Globe grape, respectively, and the fitting degree are the highest among all methods, which proves that the optimized method is applicable for accurate SL prediction of different table grape varieties.

This study not only provides a new way for the prediction of SL of different grape varieties, but also provides a reference for the quality and safety management of table grape during storage. Maybe it has a further research significance for the application of RBF neural network in the SL prediction of other fresh foods.

To address the challenges of the agricultural sector, innovation is necessary. This study aims to focus on knowledge circulation as a basis to facilitate innovation in viticulture in the context of climate change.

We have conducted interviews with viticulture stakeholders in Central Spain (Madrid region) on their perceptions and concerns about climate change, knowledge on practices to mitigate its effects on this crop and their relationship with each other for knowledge exchange. A map showing the knowledge nodes and their relationships with other stakeholders has been drawn based on the answers obtained.

Winegrowers have already noticed the effects of climate change, and they are changing some agricultural practices. Drip irrigation was the most frequently mentioned option to minimize these effects. The map of knowledge identifies the main nodes in the information flow. Results also highlight different approaches to climate change and interesting nuances in the maps of knowledge among winegrowers with and without winery.

This paper is focused on the Madrid region, a territory that is still consolidating its wine sector at the economic and marketing levels. We understand that regions with more consolidated or stronger sectors involve maps of knowledge more complex than that obtained in this study.

Showing the nodes of knowledge, as well as the weaknesses and strengths of the information circuit in the wine sector in the Madrid region, is very relevant to developing strategies aimed at supporting innovation in this sector. From a practical point of view, strategies for knowledge generation and circulation are only one part of the innovation process – policies for financial and technical support are key complementary measures.

Identification of key agents in the innovation process in the wine sector is essential to foster innovation processes. Ultimately, this will lead to more efficient adaptation to new challenges in the sector.

The Agriculture Knowledge and Innovation Systems (AKIS) approach has a consolidated theoretical framework that pays great attention to knowledge flows, but specific studies are needed to capture the reality of AKIS by sector and by region.