Resumo -O objetivo deste trabalho foi avaliar as respostas biométricas e fi siológicas de cana-de-açúcar (Saccharum spp.) ao defi cit hídrico (DH), em diferentes fases fenológicas. Os genótipos IACSP 94-2094 e IACSP 96-2042 foram submetidos a DH nas fases de crescimento inicial, crescimento máximo e de acúmulo de sacarose no colmo. O delineamento experimental foi inteiramente casualizado. A suscetibilidade ao DH foi determinada pela redução de matéria seca do colmo e do conteúdo de sólidos solúveis no caldo. O defi cit hídrico causou redução nas trocas gasosas, nas três fases fenológicas, em ambos os genótipos. Foi observada menor altura das plantas, menor acúmulo de matéria seca do colmo e de sólidos solúveis, e redução no número e comprimento de entrenós, apenas na fase de crescimento inicial, no clone IACSP 96-2042. Na fase de crescimento inicial, observou-se tolerância ao DH no genótipo IACSP 94-2094, com evidências de aclimatação fi siológica, e redução na produção de fi tomassa e de sólidos solúveis no genótipo IACSP 96-2042, como resposta à menor condutância estomática e à menor efi ciência aparente de carboxilação da fotossíntese. Independentemente da fase fenológica, o genótipo IACSP 94-2094 foi tolerante ao defi cit hídrico, pois manteve a produção de fi tomassa mesmo com redução das trocas gasosas.Termos para indexação: Saccharum, crescimento, fotossíntese, seca. Biometric and physiological responses to water defi cit in sugarcane at different phenological stagesAbstract -The aim of this work was to evaluate the biometric and physiological responses of sugarcane (Saccharum spp.) to water defi cit (WD), during different phenological phases. Genotypes IACSP 94-2094 and IACSP 96-2042 were subjected to WD conditions during the initial, maximum and sucrose accumulation phases. The experiment was carried out in a completely randomized design. Susceptibility to WD was established by reduction in stalk dry matter and soluble solids. Water defi cit reduced leaf gas exchange in all phenological phases of both genotypes. Lower plant height, less stalk dry matter and soluble solids, and reduction in number and length of internodes were only observed during the initial growth phase of the IACSP 96-2042 clone. In the initial growth phase, tolerance to WD was observed for IACSP 94-2094, with evidence of physiological acclimation, and for IACSP 96-2042 in reduction phytomass production and its soluble solid content, caused by lower stomatal conductance and lower apparent carboxylation effi ciency which limit photosynthesis. Regardless of the phenological phase, genotype IACSP 94-2094 was tolerant to WD, since its phytomass production was maintained even with impairment of leaf gas exchange.

Our results contribute directly to the improvement of linkage mapping in complex polyploids and improve the integration of physical and genetic data for sugarcane breeding programs. Thus, we describe the complexity involved in sugarcane genetics and genomics and allelic dynamics, which can be useful for understanding complex polyploid genomes.

Drought stress can imprint marks in plants after a previous exposure, leading to plant acclimation and a permissive state that facilitates a more effective response to subsequent stress events. Such stress imprints would benefit plants obtained through vegetative propagation (propagules). Herein, our hypothesis was that the propagules obtained from plants previously exposed to water deficit would perform better under water deficit as compared to those obtained from plants that did not face stressful conditions. Sugarcane plants were grown under well-hydrated conditions or subjected to three cycles of water deficit by water withholding. Then, the propagules were subjected to water deficit. Leaf gas exchange was reduced under water deficit and the propagules from plants that experienced water deficit presented a faster recovery of CO2 assimilation and higher instantaneous carboxylation efficiency after rehydration as compared to the propagules from plants that never faced water deficit. The propagules from plants that faced water deficit also showed the highest leaf proline concentration under water deficit as well as higher leaf H2O2 concentration and leaf ascorbate peroxidase activity regardless of water regime. Under well-watered conditions, the propagules from plants that faced stressful conditions presented higher root H2O2 concentration and higher activity of catalase in roots as compared to the ones from plants that did not experience water shortage. Such physiological changes were associated with improvements in leaf area and shoot and root dry matter accumulation in propagules obtained from stressed plants. Our results suggest that root H2O2 concentration is a chemical signal associated with improved sugarcane performance under water deficit. Taken together, our findings bring a new perspective to the sugarcane production systems, in which plant acclimation can be explored for improving drought tolerance in rainfed areas.

Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in different cross-validation scenarios. By combining classification and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains.

Sugarcane yellow leaf (SCYL), caused by the sugarcane yellow leaf virus (SCYLV) is a major disease affecting sugarcane, a leading sugar and energy crop. Despite damages caused by SCYLV, the genetic base of resistance to this virus remains largely unknown. Several methodologies have arisen to identify molecular markers associated with SCYLV resistance, which are crucial for marker-assisted selection and understanding response mechanisms to this virus. We investigated the genetic base of SCYLV resistance using dominant and codominant markers and genotypes of interest for sugarcane breeding. A sugarcane panel inoculated with SCYLV was analyzed for SCYL symptoms, and viral titer was estimated by RT-qPCR. This panel was genotyped with 662 dominant markers and 70,888 SNPs and indels with allele proportion information. We used polyploid-adapted genome-wide association analyses and machine-learning algorithms coupled with feature selection methods to establish marker-trait associations. While each approach identified unique marker sets associated with phenotypes, convergences were observed between them and demonstrated their complementarity. Lastly, we annotated these markers, identifying genes encoding emblematic participants in virus resistance mechanisms and previously unreported candidates involved in viral responses. Our approach could accelerate sugarcane breeding targeting SCYLV resistance and facilitate studies on biological processes leading to this trait.