The primary aim of this study is to conduct a comprehensive review of the existing literature to identify the most relevant environmental variables and other factors influencing the life cycle assessment of the wine industry. This research seeks to determine whether the type of wine significantly impacts the carbon footprint and to highlight the importance of production strategies over wine typology or grape variety in reducing greenhouse gas emissions. This review encompasses an extensive analysis of previous studies on the environmental impact of wine production. This method involves synthesizing findings from life cycle inventory assessments to identify key variables contributing to greenhouse gas emissions. This analysis also considers regional variations and the effectiveness of different production strategies in mitigating environmental impacts. This review indicates that wine typology (red or white) and grape variety are less significant in determining the carbon footprint than the production strategies employed. It identifies specific variables that contribute substantially to greenhouse gas emissions in wine production. The analysis highlights the need for standardized assessment methods to ensure accurate determination of influential factors in reducing emissions. This study concludes that achieving environmental sustainability in the wine industry requires a balanced approach that integrates environmental, economic, and social aspects. It emphasizes the necessity of developing standardized and universal strategies for assessing wine sustainability. The application of artificial intelligence is proposed as a crucial tool for improving data gathering, trend analysis, and formulating customized sustainability strategies for different wine regions. Addressing the challenges of sustainability in the wine industry is imperative for environmental preservation and the wellbeing of future generations.

Evaluation of nociceptive–antinociceptive balance during general anesthesia is still challenging and routinely based on clinical criteria. Analgesic drug delivered may be optimized with parasympathetic tone activity (PTA) monitor. This study compares ketorolac and ketorolac/tramadol balance analgesia using a PTA monitor. Pain intensity response was assessed using a 0–100 numerical state scale (PTA) after nociceptive stimuli in pigs under stable sevoflurane anesthesia. Bispectral index, heart rate, noninvasive blood pressure, and respiratory parameters were also measured. Animals were divided into 3 groups: without analgesia, ketorolac, and ketorolac/tramadol. Mean values or mean areas under the curve (AUC) in selected time periods were compared over time and between groups through a mixed-model repeated measures analysis of variance and nonparametric Kruskal-Wallis tests, followed by Bonferroni or Dunn’s multiple comparisons. It was observed a significant decrease in the PTA AUC mean value after application of the stimulus in animals treated without analgesia and only with ketorolac. The PTA AUC mean value in the control group was significantly lower than the corresponding mean in ketorolac group. The ketorolac/tramadol group showed the highest PTA AUC mean values, significantly different from those obtained for the other 2 groups, with no significant differences detected over time. Bispectral index means showed no statistically significant differences either over time periods or between different treatment groups. Heart rate showed only a statistically significant increase in AUC mean between without analgesia and ketorolac/tramadol group, in the time period after the stimulus application. Noninvasive blood pressure means showed no statistically significant differences over time and between treatment groups. This study shows that a low dose combination of ketorolac and tramadol is sufficient to block the pain responses induced with a needle holder in pigs 20 minutes after its administration. The PTA monitor was able to clearly recognize the analgesic level between treatments and may be used to optimize analgesic drug delivered.