Sugarcane (Saccharum spp.), a C4 plant, is a vital renewable biofuel and sugar source for industries worldwide. However, synchronizing flowering between parental lines often poses challenges for breeders, hindering effective crossbreeding efforts. This study aimed to develop a high-throughput phenotyping (HTP) strategy to evaluate flowering-related traits using vegetation indices (VIs) and other metrics alongside artificial intelligence (AI)-based prediction methods. A total of 154 genotypes were planted in an augmented block design at the IAC sugarcane breeding station in Serra Grande-BA, Brazil. Raw RGB (Red, Green, Blue) images were captured using a DJI Mavic 3 Enterprise drone during the plant cane (PC) and first ratoon (FR) crop seasons. These images were processed to create orthomosaics and compute metrics/vegetation index; subsequently, machine learning (ML) and deep learning pipelines for systematic analysis were developed. A convolutional neural network (CNN) model achieved promising results, with an accuracy rate of up to 84% in the flowering detection task. Additionally, flower counts from the CNN model showed a moderate correlation with field data, evidenced by an R 2 value of 0.72 at the onset and an R 2 value of 0.29 at the conclusion of the flowering season for the PC. This resulted in an overall average regression R 2 of 0.46 with a root mean square error (RMSE) of 13.80. Furthermore, an artificial neural network classification model reached a notable accuracy of 0.87 in differentiating genotypes based on their flowering response (early-flowering vs. late-flowering), utilizing VIs and digital model-based metrics as input parameters. The ML regression model demonstrated performance levels of R 2 = 0.51 and RMSE = 8.06 for days to flag leaf emergence in PC and R 2 = 0.52 and RMSE = 7.93 for days to flowering in FR. These results highlight the potential of HTP strategies, utilizing orthomosaics and AI, to accelerate data collection and analysis, offering significant insights for breeding programs in sugarcane.

Sugarcane holds significant economic importance in sugar and biofuel production. Despite extensive research, understanding highly quantitative traits remains challenging due to its complex genomic landscape. We conducted a multiomic investigation to elucidate the genetic architecture and molecular mechanisms governing sugarcane sucrose accumulation. Using a biparental cross and a genetically diverse collection of sugarcane genotypes, we evaluated the soluble solids (Brix) and sucrose content (POL) across various years. Both populations were genotyped using a genotyping-by-sequencing approach. Genotype‒phenotype associations were established using a combination of traditional linear mixed-effect models and machine learning algorithms. Furthermore, we conducted an RNA sequencing experiment on genotypes exhibiting distinct Brix and POL profiles across different developmental stages. Differentially expressed genes (DEGs) potentially associated with variations in sucrose accumulation were identified. All findings were integrated through gene coexpression network analyses. Strong correlations among the evaluated characteristics were observed, with estimates of modest to high heritabilities. By leveraging a broad set of single-nucleotide polymorphisms (SNPs) identified for both populations, we identified several SNPs potentially linked to phenotypic variance. Our examination of genes close to these markers facilitated the association of such SNPs with DEGs for contrasting sucrose levels. Through the integration of these results with a gene coexpression network, we delineated a set of genes potentially involved in the regulatory mechanisms of sucrose accumulation. Our findings constitute a significant resource for biotechnology and plant breeding initiatives. Furthermore, our genotype‒phenotype association models hold promise for application in genomic selection, offering valuable insights into the molecular underpinnings governing sucrose accumulation in sugarcane. Our multiomic investigation of sugarcane reveals significant genetic markers and regulatory genes linked to sucrose accumulation, providing valuable resources for biotechnology and plant breeding to enhance sugar production.

The progression dynamics of sugarcane smut, caused by Sporisorium scitamineum, remain underexplored despite their considerable impact on sugarcane crop productivity. The comprehension of these dynamics contributes to the development of breeding strategies for selection of resistant genotypes and effective disease management. This study analyzed disease progress curves in sugarcane genotypes inoculated with S. scitamineum under controlled greenhouse conditions. Eight genotypes, selected based on Expected Difference from the Parent and classified by their Relative Area Under the Disease Progress Curve (rAUDPC) as susceptible or moderately susceptible, were evaluated for model fit using four epidemiological models (monomolecular, Gompertz, logistic, and exponential) via linear and nonlinear regression analyses. Overall, the disease progress curves showed good fit with the tested models, with the monomolecular and Gompertz standing out as the best fit. These findings are consistent with previous field-based epidemiological studies of sugarcane smut, reinforcing their applicability in greenhouse assessments.

Sugarcane is one of the most economically important crops, particularly in Brazil, which is the largest sugarcane producer globally. Sugarcane smut, caused by the fungus Sporisorium scitamineum (Syd.), is a major disease of this crop. This study investigated the response of 165 sugarcane genotypes to smut infection under greenhouse conditions using the needle-bud puncture method. The disease incidence, the Area Under the Disease Progress Curve (AUDPC), and the relative Area Under the Disease Progress Curve (rAUDPC) were calculated, along with broad-sense heritability (h2) and the genotype’s effects. Spearman’s correlation coefficient (r2) was used to determine the correlation between the number of corresponding genotypes with smut incidence in both the greenhouse and the field. The incidence of smut ranged from 0% to 88%, and AUDPC values varied from 0 to 500 for 131 of the 165 genotypes. Based on the rAUDPC, 54 genotypes were classified as highly resistant. The correlation between greenhouse and field disease expression was positive and moderately strong (r² = 61%), and the h2 value in greenhouse conditions was 74%. The needle-bud puncture method combined with the rAUDPC values was promising for identifying susceptible genotypes and highlighting potential smut-resistant genotypes.

Abstract The choice of the statistical method for estimating genomic breeding values in genome-wide selection (GWS) studies is essential to obtain high predictive accuracies. The goal of this study was to evaluate and compare the performance of parametric models containing Additive (rrBLUP) and Additive-Dominant (BL) effects, in addition to a non-parametric model based on Machine Learning (LightGBM). Such models were applied to the genomic selection of corn hybrids evaluated in three locations (Jataí-GO, Rolândia-PR and Sorriso-MT) for two important traits, grain yield and moisture. Through the results it was demonstrated that the BL model presents excellent stability in terms of predictive capacity, however its computational performance in model training is considerably lower than the rrBLUP and LightGBM methods. If computational time is a bottleneck for the development of the genomic selection study, the LightGBM model, which has high computational efficiency, can be used, however this use may imply a significant loss of predictive accuracy. Furthermore, it was observed that the heritability of traits affects model prediction accuracy, and that genetic effects arising from smaller heritabilities can be captured more efficiently with the use of models that incorporate additive-dominant effects or Machine learning models.

Sugarcane yellow leaf disease (YLD) caused by sugarcane yellow leaf virus (ScYLV) is a major threat for the sugarcane industry worldwide, and the aphid Melanaphis sacchari is its main vector. Breeding programs in Brazil have provided cultivars with intermediate resistance to ScYLV, whereas the incidence of ScYLV has been underestimated partly due to the complexity of YLD symptom expression and identification. Here, we evaluated YLD symptoms in a field assay using eight sugarcane genotypes comprising six well-established commercial high-sucrose cultivars, one biomass yield cultivar, and a susceptible reference under greenhouse conditions, along with estimation of virus titer through RT-qPCR from leaf samples. Additionally, a free-choice bioassay was used to determine the number of aphids feeding on the SCYLV-infected cultivars. Most of the cultivars showed some degree of resistance to YLD, while also revealing positive RT-qPCR results for ScYLV and virus titers with non-significant correlation with YLD severity. The cultivars IACSP01-5503 and IACBIO-266 were similar in terms of aphid preference and ScYLV resistance traits, whereas the least preferred cultivar by M. sacchari, IACSP96-7569, showed intermediate symptoms but similar virus titer to the susceptible reference, SP71-6163. We conclude that current genetic resistance incorporated into sugarcane commercial cultivars does not effectively prevent the spread of ScYLV by its main aphid vector.

Sugarcane mosaic disease (SMD) caused by sugarcane mosaic virus, is one of the main diseases in sugarcane production areas in Brazil. Thus, the identification of new sources of resistance for use in future introgression crosses is key for reliable economic gains. Here, we aimed to screen a diversity panel of 98 sugarcane genotypes for SMD under natural infection conditions, to investigate virus-specific amplicons from SCMV coat protein gene (CP), and identify marker-trait associations via association mapping using Amplified Fragment Length Polymorphism (AFLP) and Simple Sequence Repeats (SSR). The highest SMD incidence (26.53%) was observed eight months after planting, with significant differences (p<0.01) among genotypes and a means-based broad-sense heritability of 62.49% with a noticeable contribution of Saccharum spontaneum to SMD resistance. The CP sequence analysis revealed no variation among the four selected plant samples, which phylogenetic analysis revealed clustering with the RIB-1 strain while putative amino acid substitutions indicate a new SCMV isolate. From a subset of 135 SSR and 663 AFLP markers, selected after quality control, 91 markers were associated with response to SCMV ( p <0.05) by simple linear regression, and 24 were significant at p <0.01. Four out these 24 fit in a stepwise regression at p <0.05, all contributing for the resistance to SMD, and are present in thirteen genotypes showing no SMD symptoms. These four markers collectively explain 29.95% of trait variation, while individually explain from 5.51 to 14.02%, and may correspond to new genomic regions conferring genetic resistance to SMD which investigation is worthwhile.

ABSTRACT Soil tillage is a high-cost operation in the replanting of sugarcane fields. Thus, measures to reduce this cost are desirable, provided that they promote good physical conditions for sugarcane development. The objective of this study was to evaluate the effect of chiseling in total area and in the planting row on the physical attributes of Oxisol and Ultisol after soil tillage and after sugarcane planting. The experimental design was in large and uniform plots, with two treatments and ten replicates. The Oxisol and Ultisol had clay contents of 590 and 168 g kg−1 in the 0.00–0.40 cm layer. Treatments consisted of soil tillage with chiseling in the planting row and with chiseling in total area. After soil chiseling and after planting, undisturbed soil samples were collected in each experimental plot, in three layers (0.00–0.10; 0.10–0.20 and 0.20–0.40 m) and at two sampling sites (row and interrow). In both soils, chiseling in total area was efficient to reduce soil density and increase macroporosity in sugarcane interrows, compared to chiseling in the row. The values of the physical attributes of the soils evaluated, in rows and interrows, were similar in the areas with chiseling in total area and row chiseling after sugarcane planting. Changes in Oxisol and Ultisol structure due to chiseling did not persist after sugarcane planting. The soil under row chiseling system has physical quality similar to that of the soil under total area chiseling system, regardless of texture.

Drought is the most detrimental abiotic stress to sugarcane production. Nevertheless, transcriptomic analyses remain scarce for field-grown plants. Here we performed comparative transcriptional profiling of two contrasting sugarcane genotypes, ‘IACSP97-7065’ (drought-sensitive) and ‘IACSP94-2094’ (drought-tolerant) grown in a drought-prone environment. Physiological parameters and expression profiles were analyzed at 42 (May) and 117 (August) days after the last rainfall. The first sampling was done under mild drought (soil water potential of −60 kPa), while the second one was under severe drought (soil water potential of −75 kPa). Microarray analysis revealed a total of 622 differentially expressed genes in both sugarcane genotypes under mild and severe drought stress, uncovering about 250 exclusive transcripts to ‘IACSP94-2094’ involved in oxidoreductase activity, transcriptional regulation, metabolism of amino acids, and translation. Interestingly, the enhanced antioxidant system of ‘IACSP94-2094’ may protect photosystem II from oxidative damage, which partially ensures stable photochemical activity even after 117 days of water shortage. Moreover, the tolerant genotype shows a more extensive set of responsive transcription factors, promoting the fine-tuning of drought-related molecular pathways. These results help elucidate the intrinsic molecular mechanisms of a drought-tolerant sugarcane genotype to cope with ever-changing environments, including prolonged water deficit, and may be useful for plant breeding programs.

Due to the large increase in the area cultivated with genetically modified soybean in Brazil, it has become necessary to determine methods that are fast and efficient for detecting these cultivars. The aim of this work was to test the efficiency of the toothpick method in the detection of RR soybean plants, as well as to distinguish between cultivars, for sensitivity caused by herbicide. Ten transgenic soybean cultivars, resistant to the active ingredient glyphosate, and ten conventional soybean cultivars were used. Toothpicks soaked in glyphosate were applied to all the plants at stage V6 and evaluations were made at 2, 4, 6, 8 and 10 days after application (DAA). The effects of the glyphosate on the cultivars, and the symptoms of phytotoxicity caused in the transgenic plants were evaluated by means of grading scales. The toothpick test is effective in identifying RR soybean cultivars and also in separating them into groups by sensitivity to the symptoms caused by the glyphosate.

Yellow leaf disease (YLD), caused by sugarcane yellow leaf virus (SCYLV), has been reported to infect sugarcane worldwide causing significant yield losses and is considered a major disease of this crop. A panel composed of 98 genotypes encompassing basic germplasm, commercial cultivars, and elite clones was assayed in the nursery and a replicated field for resistance to SCYLV, combining symptom expression and virus quantification. Virus symptom intensity was evaluated using a diagrammatic scale while virus titer was estimated by DAS-ELISA (Double Antibody Sandwich-ELISA) and RT-qPCR (Reverse Transcription Quantitative PCR) in the nursery and field trials, respectively. Resistance was evaluated alongside symptom development kinetics. Based on the symptom intensity, 52 (53.06%) genotypes were classified as resistant in the nursery and 42 (42.86%) in the field. Twenty-nine (29.59%) genotypes showed no symptoms in the nursery and field trial. Moderately resistant genotypes showed a low correlation between virus titer and symptom intensity. The kinetics of symptom development increased over time in moderately susceptible and susceptible genotypes. The SCYLV incidence assessed by RT-qPCR was 92.55%, which was detected in 83% of the asymptomatic genotypes. The broad-sense heritability based on symptom expression and relative quantification was 52.62% and 68%, respectively. The virus quantification assays allowed for the identification of potential genotypes immune to SCYLV.

Sugarcane is a major crop cultivated globally for sugar and bioenergy production, with increasing relevance as a biomass source. Association mapping studies, in turn, identify markers associated with target traits that may assist genotype selection. Here, we used a diversity panel comprising 100 sugarcane genotypes to investigate the clustering patterns using phenotypic data, i.e., sugar content (Pol%Cane) and fiber, and Amplified Fragment Length Polymorphism (AFLP) markers, and perform association mapping to identify marker–trait associations (MTAs) that are consistent across harvesting times, i.e., autumn, winter and spring harvest, and across 2 years for the spring harvest. The K-means clustering of phenotypic and genotypic data revealed discontinuities among genotypes, indicating a distribution into two groups with high intra- and inter-group diversity. A subset of 640 AFLP markers across 93 genotypes was selected after quality control and subjected to association analysis via the Bayes C method. Different sets of MTAs were detected across harvest times for each trait, with each set collectively explaining 68.44–99.75% of the phenotypic variation (R2). The detection in more than one harvest time was observed for 32 and 12 MTAs for Pol%Cane and fiber, respectively, while none was detected in all the harvest times. The most important markers selected by the stepwise process individually explained 1.61–67.55% of the phenotypic variation, with highlights for the MTAs with high individual R2 values and/or detection in two or more harvest times with consistent positive effects, which may correspond to new genomic regions associated with Pol%Cane and fiber and should be further investigated.

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.

The pre-sprouted sugarcane plantlets (PSP) system aims the production of healthy and vigorous plants in reduced time, reducing the number of stalks needed for planting. Irrigation is used in all PSP system stages and water management plays an important role. Stage 1 acclimation follows the budding stage and lasts for approximately 21 days. At this stage the plantlets are grown within an agricultural greenhouse to improve initial development. The objectives of this trial were: to identify the irrigation management which results in highest plantlet growth; to evaluate if responses to irrigation management depends on the cultivar; to evaluate water consumption and water use efficiency at early stage under PSP system; and to assess the water management effect on substrate water matrix potential and stomatal conductance in the cultivar IACSP95-5000. The experimental design was a split-plot randomized block design with four replications. Treatments applied in the plots were different irrigation depths based on daily reference evapotranspiration (ETo): 96, 80, 64 and 48%, estimated by Penman-Monteith method. In the subplots, there were sugarcane cultivars IAC91-1099, IACSP95-5000 and IACSP97-4039. Irrigation management based on 80% ETo resulted in higher growth, dry mass accumulation and greater leaf area. Water use efficiency was not influenced by irrigation management. IAC91-1099 presented higher overall growth, leaf area and dry mass accumulation. Water consumption was cultivar-dependent in irrigation managements using 80 and 96% of ETo. Water use efficiency was higher in IAC91-1099 and lower in IACSP95-5000. Lower substrate water matrix potential reduced leaves stomatal conductance, impairing IACSP95-5000 plantlet growth.

A sugarcane gene encoding a dirigent-jacalin, ShDJ, was induced under drought stress. To elucidate its biological function, we integrated a ShDJ-overexpression construction into the rice Nipponbare genome via Agrobacterium-mediated transformation. Two transgenic lines with a single copy gene in T0 were selected and evaluated in both the T1 and T4 generations. Transgenic lines had drastically improved survival rate under water deficit conditions, at rates close to 100%, while WT did not survive. Besides, transgenic lines had improved biomass production and higher tillering under water deficit conditions compared with WT plants. Reduced pectin and hemicellulose contents were observed in transgenic lines compared with wild-type plants under both well-watered and water deficit conditions, whereas cellulose content was unchanged in line #17 and reduced in line #29 under conditions of low water availability. Changes in lignin content under water deficit were only observed in line #17. However, improvements in saccharification were found in both transgenic lines along with changes in the expression of OsNTS1/2 and OsMYB58/63 secondary cell wall biosynthesis genes. ShDJ-overexpression up-regulated the expression of the OsbZIP23, OsGRAS23, OsP5CS, and OsLea3 genes in rice stems under well-watered conditions. Taken together, our data suggest that ShDJ has the potential for improving drought tolerance, plant biomass accumulation, and saccharification efficiency.

The spittlebug Mohanarva filmbriofolato (Stal)(Hemiptera: Cercopidael is one of the roost important pest of sugarcane in Brazil, Population control measures are currently restricted to the use of chemical insecticides and the fungus Metorhizurn rqsopilue, in part because very little information exists regarding the resistance of sugarcane cultivars, Therefore, the aim of this study was to evaluate the resistance mechanisms of 18 sugarcane cultivars to AT fimbrOloto to provide in formation for growers hoping to manage this pest, Isolated buds of each cultivar were planted in pots and maintained in a greenhouse for approximately three months. The pots were then moved to climate-controlled chambers (26 +/- 1 degrees C; 70 10% RH, 12 h photoperiod) to carry out laboratory tests to evaluate adult feeding and female oviposition preferences (using both free-choice and no-choice tests) as well as the effects of the cultivars on nymph development and the cultivars tolerance to the pest attack, The least attractive cultivar for adult feeding and oviposition in free-choice test was P13867515, which was also one of those that received the fewest eggs in the no-choice oviposition tests. Cultivar CTC9 showed the highest level of antibiosis resistance, with a root nymph survival rate of 52.5%, Finally, cultivar 00966928 was the most tolerant to fimbriolata, but it showed 19% reduction in aboveground biomass weight due to the pest.

ABSTRACT: This research aimed at studying herbicides selectivity on individuals from three sugarcane families after different chemical managements in primary selection fields (F1). On the field, a randomized block design with five replications in a split plot scheme was used. Twelve herbicide treatments were allocated in the plots and the three seedlings families were allocated in the sub-plots. The herbicides treatments were T1- tebuthiuron POST-i + ametryn POST-t; T2- (diuron + hexazinone) POST-i + ametryn POST-t; T3- sulfentrazone POST-i + ametryn POST-t; T4- (diuron + hexazinone) POST-i + metribuzin POST-t; T5- sulfentrazone POST-i + metribuzin POST-t; T6- imazapyr IPP; T7- imazapyr IPP + ametryn POST-t; T8- imazapyr IPP + metribuzin POST-t; T9- imazapyr IPP + tebuthiuron POST-i; T10- imazapyr PPI + (diuron + hexazinone) POST-i; T11- imazapyr IPP + sulfentrazone POST-i and T12- weeded control. Families were F400 (IAC086155 x ?), F43 (IACBIO264 x IAC911099) and F14 (IACSP991305 x GlagaH). For each individual, the intoxication symptoms and the chlorophyll content on the leaves (40 and 120 DAApós-i), the percentage of live seedlings and selected seedlings (240 DAApós-i) were evauated. The chemical management with alternative treatments (T2 to T11) was selective to the three seedlings families because it caused slight intoxication symptoms and interference in the chlorophyll content, in addition to the high percentage of survival that allowed the plants selection for the later stage (F2). The management with herbicide applied in incorporated pre-planting (IPP) was highlighted as selective even when supplemented after the establishment phase of seedlings (POST-t).

In recent years, the use of presprouted setts (MPB, which stands for "mudas pre-brotadas" in Portuguese) to establish commercial sugarcane nurseries has grown in Brazil. MPB and single-bud setts (SBS) have the advantage of requiring less planting material and enabling a higher multiplication rate of the source material as compared with the conventional multibud sett (MBS) planting system. Sugarcane breeding programs could also potentially benefit from the precise spacing afforded by MPB or SBS planting materials, by reducing trial variability. However, the effect of planting material type on the performance ranking and consequent selection of sugarcane clones in a breeding program has not been previously investigated. We present results on possible interactions between genotype and the type of planting material (MPB, MBS, or SBS) on key performance parameters, like sugar content, cane yield, and sugar yield, in the context of the intermediate phase of a sugarcane breeding program. Our results indicate that trial quality does not necessarily improve with the use of MPB or SBS planting materials and that type of planting material has a significant effect on the ranking of sugarcane genotypes, and this needs to be taken into consideration when considering the use of new planting technologies in breeding trials of vegetatively propagated crops such as sugarcane.

The success of breeding programs depends on selection procedures and on the breeding methods adopted for selecting segregating populations. The objective of this study was to evaluate the efficiency of the Bulk method with selection in the F3 generation (BulkF3) compared to that of Bulk method as well as determine the most effective selection strategy in terms of genetic gain. Twenty segregating populations were selected by two methods. The 60 best families of each method were selected according to their average agronomic performance. An augmented block design was used. The following agronomic traits were evaluated: insertion height of first pod, plant height at maturity, number of branches and of pods per plant, 100-seed weight, and grain yield. For comparison of the methods, genetic component estimates, genetic gain and predicted breeding values were calculated using mixed models (REML and BLUP). The results showed the families obtained with the BulkF3 method were more productive, showed suitable plant height, a larger number of branches and pods, and higher 100-seed weight. The BulkF3 method was found to be an effective selection strategy for soybean improvement.