No abstract

Abscisic acid (ABA) and auxin are important hormones controlling the ripening progression of grape berry, and both the initiation and duration of ripening can dramatically affect the berry quality. However, the responses of flavor compounds to the hormones are inadequately understood. In this study, ABA and synthetic auxin α-naphthaleneacetic acid (NAA) were sprayed on Cabernet Sauvignon berries before véraison, and comparative transcriptomic and metabolic analysis were conducted to investigate the influence on berry quality-related metabolites. The 1000 mg/L ABA (ABA1000) and 200 mg/L NAA (NAA200) treated grapes exhibited shorter and longer phenological intervals compared to the control, respectively. The transcriptomic comparison between pre-véraison and véraison revealed that the varied ripening initiation and duration significantly affected the expression of genes related to specific metabolism, particularly in the biosynthetic metabolism of anthocyanin and volatile compounds. The up-regulated VviF3’H in both ABA1000-treated and NAA200-treated berries increased the proportion of 3′-substituted anthocyanins, and the 3′5′-substituted anthocyanins were largely reduced in the NAA200-treated berries. Concurrently, VviCCD4a and VviCCD4b were up-regulated, and the norisoprenoids were correspondingly elevated in the NAA200-treated berries. These data suggest that ABA and NAA applications may be useful in controlling the ripening and improving the flavor of the grape berry.

Purpose The purpose of this paper is to provide further insight into Chinese wine consumers’ preference, grasp the regional sensory preference differences of China and build up a predictive model for wine consumers’ sensory preferences. Design/methodology/approach The study involved 3,421 Chinese wine consumers in the survey. Classified statistics were conducted to excavate regional differences of wine consumers’ sensory preferences. By analyzing influencing factors, prediction models for consumers’ sensory attribute preferences were constructed on the basis of multivariate disorder logistic regression method. Findings Empirical research showed that the wine with the following sensory attributes was the most preferred by Chinese consumers: dry red, refreshing and soft taste, still type, moderate aroma degree and mellow aroma, and sweet wine was also popular. Consumers’ preference varied from region to region. The proposed predicting method of the study realized more than 70 percent accuracy when conducting prediction for color, sweetness, aroma type and flavor preferences. Social implications By shedding light on the latest sensory attribute preferences of Chinese wine consumers, this study will help wine industry participants conduct market segmentation based on the diversification of consumers’ preferences. The wine enterprises can gain guidance from the results to conduct market positioning, adjust strategies and provide specific production for target wine consumers. Originality/value Based on the actual situation of Chinese wine market, this study defines sensory attribute indexes of wine from the perspective of wine consumers and presents the most recent comprehensive research on the sensory preferences of Chinese wine consumers through a nationwide survey.

Small-scale farms represent about 80% of the farming area of China, in a context where they need to produce economic and environmentally sustainable food. The objective of this work was to define management zone (MZs) for a village by comparing the use of crop yield proxies derived from historical satellite images with soil information derived from remote sensing, and the integration of these two data sources. The village chosen for the study was Wangzhuang village in Quzhou County in the North China Plain (NCP) (30°51′55″ N; 115°02′06″ E). The village was comprised of 540 fields covering approximately 177 ha. The subdivision of the village into three or four zones was considered to be the most practical for the NCP villages because it is easier to manage many fields within a few zones rather than individually in situations where low mechanization is the norm. Management zones defined using Landsat satellite data for estimation of the Green Normalized Vegetation Index (GNDVI) was a reasonable predictor (up to 45%) of measured variation in soil nitrogen (N) and organic carbon (OC). The approach used in this study works reasonably well with minimum data but, in order to improve crop management (e.g., sowing dates, fertilization), a simple decision support system (DSS) should be developed in order to integrate MZs and agronomic prescriptions.