The extensive use of synthetic fertilizers and pesticides has negative consequences in terms of soil microbial biodiversity and environmental contamination. Faced with this growing concern, a proposed alternative agricultural method is the use of microorganisms as biofertilizers. Many works have been focused on bacteria, but the limited literature on yeasts and their potential ability to safely promote plant growth is gaining particular attention in recent years. Thus, the objective of this review is to highlight the application of yeasts as biological agents in different sectors of sustainable agricultural practices through direct or indirect mechanisms of action. Direct mechanisms include the ability of yeasts to provide soluble nutrients to plants, produce organic acids and phytohormones (indole-3-acetic acid). Indirect mechanisms involve the ability for yeasts to act as biocontrol agents through their high antifungal activity and lower insecticidal and herbicidal activity, and as soil bioremediating agents. They also act as protective agents against extreme environmental factors by activating defense mechanisms. It is evident that all the aspects that yeasts offer could be useful in the creation of quality biofertilizers and biopesticides. Hence, extensive research on yeasts could be promising and potentially provide an environmentally friendly solution to the increased crop production that will be required with a growing population.

The relative importance of gross chromosomal rearrangements to adaptive evolution has not been precisely defined. The Saccharomyces cerevisiae flor yeast strains offer significant advantages for the study of molecular evolution since they have recently evolved to a high degree of specialization in a very restrictive environment. Using DNA microarray technology, we have compared the genomes of two prominent variants of S. cerevisiae flor yeast strains. The strains differ from one another in the DNA copy number of 116 genomic regions that comprise 38% of the genome. In most cases, these regions are amplicons flanked by repeated sequences or other recombination hotspots previously described as regions where double-strand breaks occur. The presence of genes that confer specific characteristics to the flor yeast within the amplicons supports the role of chromosomal rearrangements as a major mechanism of adaptive evolution in S. cerevisiae. We propose that nonallelic interactions are enhanced by ethanol- and acetaldehyde-induced double-strand breaks in the chromosomal DNA, which are repaired by pathways that yield gross chromosomal rearrangements. This mechanism of chromosomal evolution could also account for the sexual isolation shown among the flor yeast.

The acyl coenzyme A (CoA):6-aminopenicillanic acid (6-APA) acyltransferase of Penicillium chrysogenum AS-P-78 was purified to homogeneity, as concluded by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and isoelectric focusing. The enzyme is a monomer with a molecular weight of 30,000 +/- 1,000 and a pI of about 5.5. The optimal pH and temperature were 8.0 and 25 degrees C, respectively. This enzyme converts 6-APA into penicillin by using phenylacetyl CoA or phenoxyacetyl CoA as acyl donors. The pure enzyme showed a high specificity and affinity for 6-APA and did not accept benzylpenicillin, 7-aminocephalosporanic acid, cephalosporin C, or isocephalosporin C as substrates. The enzyme converted isopenicillin N into penicillin G, although with a lower efficiency than when 6-APA was used as the substrate. It did not show penicillin G acylase activity. The acyl CoA:6-APA acyltransferase required dithiothreitol or other thiol-containing compounds, and it was protected by thiol-containing reagents against thermal inactivation. The acyltransferase was inhibited by several divalent and trivalent cations and by p-chloromercuribenzoate and N-ethylmaleimide. The activity was absent in four different mutants that were blocked in penicillin biosynthesis.

In view of the growing concern about the impact of synthetic fungicides on human health and the environment, several government bodies have decided to ban them. As a result, a great number of studies have been carried out in recent decades with the aim of finding a biological alternative to inhibit the growth of fungal pathogens. In order to avoid the large losses of fruit and vegetables that these pathogens cause every year, the biological alternative’s efficacy should be the same as that of a chemical pesticide. In this review, the main studies discussed concern Saccharomyces and non-Saccharomyces yeasts as potential antagonists against phytopathogenic fungi of the genera Penicillium and Aspergillus and the species Botrytis cinerea on table grapes, wine grapes, and raisins.

Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phytopathological research. This review analyzes current applications and future directions of AI in addressing evolving agricultural challenges. Plant diseases annually cause 10–16% yield losses in major crops, prompting urgent innovations. Artificial intelligence (AI) shows an aptitude for automated disease detection and diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% and surpassing human visual assessment. Forecasting models integrating weather, soil, and crop data enable preemptive interventions by predicting spatial-temporal outbreak risks weeks in advance at 81–95% precision, minimizing pesticide usage. Precision agriculture powered by AI optimizes data-driven, tailored crop protection strategies boosting resilience. Real-time monitoring leveraging AI discerns pre-symptomatic anomalies from plant and environmental data for early alerts. These applications highlight AI’s proficiency in illuminating opaque disease patterns within increasingly complex agricultural data. Machine learning techniques overcome human cognitive constraints by discovering multivariate correlations unnoticed before. AI is poised to transform in-field decision-making around disease prevention and precision management. Overall, AI constitutes a strategic innovation pathway to strengthen ecological plant health management amidst climate change, globalization, and agricultural intensification pressures. With prudent and ethical implementation, AI-enabled tools promise to enable next-generation phytopathology, enhancing crop resilience worldwide.