Xavier, M. A. | Search bioRxiv

bioRxiv2025

Field-based prediction of sugarcane photosynthesis through environmental inputs

Sugarcane (Saccharum officinarum) is a highly productive C4 crop prevalent in tropical and subtropical areas. However, its photosynthetic efficiency is influenced by environmental factors such as light, moisture and temperature. Understanding these interactions is critical for optimizing yields and addressing climate-related challenges. This study investigated the effects of environmental variables on carbon assimilation in four Brazilian sugarcane varieties (SP79-1011, IAC94-2094, IACSP94-2101 and IACSP95-5000), addressing both optimal and limiting conditions for key parameters. Over a 530-day field experiment, data were collected every 30 days from 7:00 to 17:00, measuring diurnal CO2 assimilation (A), photosynthetically active radiation (PAR), vapor pressure deficit (VPD), and air temperature. Polynomial models and multiple linear regression were used to quantify the contributions of these variables in CO2 uptake, yielding robust model fits (p<0.05, R2 = 0.84-0.99). Herein, optimal photosynthetic performance occurred under PAR at 1800 mol m-2 s-1, VPD at 2.34 kPa, and air temperature close to 32.5{degrees}C. A strong correlation (r = 0.92, p<0.001) between observed and predicted photosynthesis and high model efficacy (R2=0.60, p<0.001) underscored the reliability of the approach, explaining 60% of the observed variation. While the results highlighted the models effectiveness in predicting sugarcane photosynthetic rates under varying diurnal and seasonal conditions, deviations indicated the influence of unmeasured parameters and complex interactions that need further investigation. These findings provide valuable insights to refine sugarcane management practices, enhance yield potential, and improve crop resilience under climate change scenarios.

plant biology↗

bioRxiv2024

Multiomic insights into sucrose accumulation in sugarcane

Sugarcane (Saccharum spp.) holds significant economic importance in sugar and biofuel production. Despite extensive research, understanding highly quantitative traits, such as sucrose content, remains challenging due to the complex genomic landscape of the crop. In this study, we conducted a multiomic investigation to elucidate the genetic architecture and molecular mechanisms governing sucrose accumulation in sugarcane. Using a biparental cross (IACSP95-3018 x IACSP93-3046) and a genetically diverse collection of sugarcane genotypes, we evaluated the soluble solids (Brix) and sucrose content (POL) across various years and environments. Both populations were genotyped using a genotyping-by-sequencing (GBS) approach, with single nucleotide polymorphisms (SNPs) identified via bioinformatics pipelines. Genotype-phenotype associations were established using a combination of traditional linear mixed-effect models and machine learning algorithms. Furthermore, we conducted an RNA sequencing (RNA-Seq) 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 a comprehensive gene coexpression network analysis. Strong correlations among the evaluated characteristics were observed, with estimates of modest to high heritabilities. By leveraging a broad set of 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 in genotypes with 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 in sugarcane, collectively contributing to the definition of this critical phenotype. 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.

genetics↗