Sugar Tech最新文献

The increasing global demand for Stevia rebaudiana Bertoni, as a natural non-calorie sweetener has driven concentrated breeding efforts towards its genetic improvement for large-scale commercialization. Steviol glycosides responsible for sweetness in stevia leaves include stevioside, rebaudiosides and dulcoside. Inadequate genetic resources, characterization and the lack of high yielding, superior varieties pose major challenge in stevia production. Developing stevia varieties for high dry leaf yield, high steviol glycosides content particularly rebaudioside-A, optimum leaf-to-stem ratio, enhanced growth and photosynthetic activity, combating biotic and abiotic stresses is being targeted in genetic improvement programmes. Stevia exhibits considerable genetic diversity and in order to elucidate the genetics of steviol glycosides; the pattern of diversity has been assessed for achieving desired improvement. Recent advancements in biotechnological tools such as marker-assisted selection, genomics-assisted breeding, transcriptomics, metabolomics and genetic engineering have further accelerated the breeding progress. Marker-assisted and genomics-assisted breeding facilitate targeted improvements by identifying key genes linked to steviol glycosides biosynthesis. Genome sequencing of stevia revealed a 1416 Mb genome with over 80 per cent repetitive elements and transcriptomic analyses have identified critical glycosyltransferase genes involved in glycosylation, a critical process in steviol glycosides biosynthesis. Functional genomics and Agrobacterium-mediated transformation techniques have demonstrated the potential of metabolic engineering for enhancing steviol glycosides yield. This review highlights the progress made in stevia genetic improvement, emphasizing the integration of conventional breeding with advanced genomic tools to develop superior varieties and meet the rising demand for this natural sweetener.

The present study was an attempt to optimize the regeneration protocols of Stevia rebaudiana (Bert.). Leaf and nodal explants were inoculated in MS medium supplemented with various plant growth regulators in different combinations and concentrations in order to attain direct and indirect regeneration. Among the treatments used, 2 mg/L of indole-3-acetic acid (IAA) + 1 mg/L of 6-Benzylaminopurine (BAP) displayed better results in stevia for callus induction when leaf and nodal explants were used, but in the case of nodal explants, it took more days for callus initiation compared to leaf segment. Among the treatments, 2.0 mg/L of IAA + 1.0 mg/L of BAP were found to be better for callus induction and subsequent plantlets regeneration (66.15%) from leaf explant of stevia. MS medium fortified with 0.5 mg/L of kinetin produced a high regeneration response (46.92%), the highest number of plantlets (40.67%) per explant, and the maximum number of roots (5.00) per plantlet in case of direct in vitro regeneration. While the MS medium fortified with 1.0 mg/L of BAP + 2.0 mg/L of IAA was found to be the best indirect in vitro regeneration of stevia plantlets from nodal explants concerning the highest regeneration response (68.10%), number of plantlets per explant and shoot length. MS medium added with 1.0 mg/L of BAP + 2.0 mg/L of IAA was reported to have the highest root regeneration ability (67.41%) and considerable length of roots for rooting of in vitro derived plantlets of stevia. The Soilrite was the best for acclimatizing in vitro regenerated plantlets of stevia. This is the first successful report on micropropagation in Stevia rebaudiana from sub-Himalayan region of West Bengal, India. A combination of IAA and BAP proved better for direct and indirect organogenesis. The Soilrite media was the best for acclimatization of in vitro regenerated plantlets with the highest (68.57%) survival rate in field conditions. Results of the present study will be useful for mass multiplication of Stevia rebaudiana using direct and indirect in vitro approaches. Moreover, direct in vitro shoot formation from leaves of Stevia rarely reported may open up possibilities of more successful large-scale cultivation of Stevia in the region and elsewhere.

In this study, the electrically driven sugarcane seeding system configures the desired plant spacing via the touchscreen human–computer interaction. The operating speed of the implement is acquired through the GNSS-RTK receiver in real-time during operation. In contrast, the instantaneous rotational speed of the motor is measured using a rotary encoder. Subsequently, the rotational speed of the sowing motor is regulated using a control system based on linear active disturbance rejection control. The parameters of this control system are optimized through the simulated annealing particle swarm optimization algorithm. A mechanism for monitoring misplaced sugarcane seeding is designed to detect seed misplacement instances and store the misplacement locations’ coordinates. The results of simulated seeding experiments indicate that, under various seeding operation speeds and plant spacing settings, the seeding motor’s theoretical and actual rotational speed discrepancy falls within the range of 4.03–6.61%. The average coefficient of variation for qualified plant spacing is 12.62%. The average error for seeding plant spacing is 8.44%. Compared to a similar type of ground wheel-driven sugarcane planting mechanism, the sugarcane planting system with electric drive exhibits an increase of 1.44% in the accuracy of planting spacing and a reduction of 6.72% in the average coefficient of variation for qualified plant spacing. The average positioning error for missing cane seeding is 84.11 mm, which can meet the sugarcane seedling shortage replanting operation requirements. The electric-driven sugarcane seeding system designed in this study overcomes the inflexibility of ground wheel-driven systems, effectively improving planting accuracy and flexibility. Additionally, it enables precise positioning of missed seeding spots, supporting efficient replanting operations. This study has reference significance for sugarcane precision planting technology.

To identify high-yielding, adaptable, and regionally representative sugar beet varieties, this study applied analysis of variance, the additive main effects and multiplicative interaction (AMMI), best linear unbiased prediction (BLUP) analysis, and the genotype main effects plus genotype–environment interaction (GGE) biplot method. We evaluated the sugar content and root yield of 16 sugar beet varieties grown at seven different trial locations in 2021. The results indicated significant differences between the uncorrected data and the BLUP values, with the latter being more accurate and reliable in representing breeding values. Among the tested varieties, KWS 7748–1 (V6) exhibited the highest and most stable yield across all three models, demonstrating strong adaptability and high yield potential in various environments. This suggests that KWS 7748–1 (V6) has high potential for stable yields, even in regions with fluctuating climatic conditions. Therefore, it could become an important resource in breeding programs, particularly for improving yield adaptability and stress resistance. Its reliability in diverse environments makes it an ideal candidate for widespread cultivation, contributing to increased sugar beet production and food security. Furthermore, Jialaid Banner (E7) was identified as the most discriminative and representative trial location. The combined application of analysis of variance, AMMI model, BLUP analysis, and GGE biplot method enhanced the scientific rigor, comprehensiveness, and effectiveness of the regional trials for sugar beet varieties.

This research paper addresses the challenge of editing complex genes in crops, specifically sugarcane and other polyploid plants, by leveraging CRISPR-Cas9 technology. A specialized computer program was developed to facilitate precise and efficient gene editing in these crops. Genomic sequences, annotations, and related datasets were sourced from the Sugarcane Genomes database (http://sugarcane-genome.org). Data in FASTA, GFF, and CSV formats enabled efficient preprocessing. ClustalW was used to identify target regions in the sugarcane genome for gRNA design, focusing on subsequences of 20 bases that ended with the "NGG" protospacer adjacent motif (PAM). Specific criteria were followed for gRNA design, considering patterns and matching confidence. High-performance computing, including GPUs and cloud platforms, handled the extensive genomic data. ChopChop and CRISPOR algorithms, along with Python libraries, supported systematic analysis, ensuring precise gRNA design. Potential target regions were identified in the PP2C genes within the sugarcane genome for CRISPR-Cas9 genome editing. The source genome database, classified based on gene families, yielded 6904 subsequences, with 1251 showing over 90% similarity, indicating conserved regions. The tool identified off-targets and unique targets. The sugarcane guide RNA (gRNA) design tool was initially developed and tested using a single set of genes and passed the initial validation, demonstrating its capability to accurately design gRNAs for the selected gene set. Given this success, the tool's application is planned to be expanded to encompass the entire sugarcane genome, enabling comprehensive gRNA design for all gene sets in sugarcane and facilitating more extensive genetic editing and research opportunities.

There is a lack of systematic analysis and research on the special components of red beet and sugar beet, which are common beet varieties rich in a variety of beneficial chemicals. To investigate the differences in the composition of flavonoids and terpenoids in roots of red beet and sugar beet, poinsettia(red beet) and HD802(sugar beet) were detected and analysed in the present study by using the UPLC-MS/MS detection platform and the MWDB(Metware database), and orthogonal partial least squares discriminant analysis (OPLS-DA) was used to screen out the differential metabolites from the detected flavonoid metabolites and terpenoids metabolites. A total of 69 flavonoid metabolites from 6 classes and 48 terpenoids from 6 classes were detected in two kinds of beet roots. Analysis of variance (ANOVA) showed that the content of 5 flavonoid and 4 terpenoid differential metabolites was higher in red beet roots than in sugar beet roots, and the content of the remaining 25 flavonoid and 2 terpenoid differential metabolites was lower than that of sugar beet roots. According to the metabolite Log₂FC, the components of the flavonoid metabolites with large difference ratio were mainly Polymethyl flavonoid derivatives, Iso-rhamnoside and Rhamnoside, Marigold glycoside, Methoxyl flavonoid derivatives, Diosmetin derivatives, Chrysoeriol and its derivatives, Luteolin derivatives, Homonetsin derivatives and Kaempferol derivatives. Significant differences in flavonoid metabolites and terpenoid metabolites between the two beet roots were found by non-targeted analysis of variance and can be further analysed as characteristic metabolites.

Sugarcane is a tropical and subtropica cultivated crop that exhibits complex genetic traits. Key agronomic characteristics, such as tillering rate (T-rate) and the number of canes per hectare (NCPH), are crucial for yield optimization. This study employed a two-way pseudo-testcross strategy mapping approach with a 172 F1 population derived from ‘Yuenong73-204’ (low-tillering) × ‘CP72-1210’ (high-tillering). A genetic map spanning 1578.04 cM was constructed using 572 SNP identified via chip array genotyping. Through quantitative trait loci (QTL) mapping with LOD > 3, five QTLs linked to T-rate and four to NCPH were identified. Meanwhile, one QTL consistently present in at least two environments and one QTL present in both tillering traits. These QTLs accounted for the explanatory rate of phenotypic variation (PVE), ranging from 7.7 to 11.1% for T-rate and 5.6% to 10.7% for NCPH. Additionally, we screened one representative loci (AX-171307910) with one excellent genotype (GG), based on the QTL of qSE1/E2NCPH57 for NCPH, which excellent genotype will lead sugarcane toward better tillering traits. Finally, seven having this excellent genotype were screened. Further analysis revealed 3 relatively reliable candidate genes within the QTL of qSE1/E2NCPH57, including Soffic.01G0055400-1P, Soffic.01G0055410-1A, and Soffic.01G0055150-1A, respectively. However, RT-qPCR analysis discovered that the expression level of Soffic.01G0055400-1P and Soffic.01G0055150-A showed significant difference between Yuenong73-204 and CP72-1210, suggesting these two candidate genes were highly likely to be important genes affecting tillering. These insights offer valuable reference points for genetic enhancement strategies targeting tillers and for effective stalk development in sugarcane.

One of the most significant challenges in the agricultural sector is managing waste from its products. This study examined the energy and environmental indicators of three products derived from sugarcane bagasse including: compost, livestock feed and medium fiberboard produced in the agriculture and industry of the Imam Khomeini factory in Shushtar, Khuzestan Province of Iran. The energy analysis results showed that the total energy output for producing one ton of compost, livestock feed, and one m³ of fiberboard was 300 MJ, 32,170 MJ, and 34,390 MJ and the energy ratio was 0.007, 1.41, and 2.38, respectively. Urea fertilizer (75% of total energy share) in compost production, peat bagasse (45% of total energy share) in livestock feed production and polyurethane adhesive (52% of total energy share) in fiberboard production were identified as the most consumed inputs for each product. The environmental results showed that the total environmental damage (Final Environmental Index) for compost, livestock feed and medium fiberboard was 1.077 pp ton⁻¹, 9.02 pp ton⁻¹ and 3.43 pp ton⁻¹, respectively.

Jaggery, a non-centrifugal sugar (NCS), is regarded as a healthier option than refined sugar because of its non-sugar components. The study aimed to determine whether processing variation contributed significantly to changes in physical characteristics, polyphenolic contents, antioxidant activity, and mineral and vitamin contents. Total of 30 (16 blocks and 14 powder) NCS samples produced in two states of India were evaluated for sugars, moisture, ash, water activity, colour, total polyphenols and flavonoid contents, antioxidant activity, and mineral and vitamin contents. Profiling of polyphenolic compounds was conducted with liquid chromatography-mass spectroscopy. In vitro radical scavenging and ferric reducing power were evaluated for antioxidant activities using whole NCS samples. Block and powder samples were found to differ in terms of the micronutrient profile, total polyphenolic content, water activity, and colour index. A variation was also seen between the two selected regions of production in addition to variation within the same location. Several polyphenols, including maritimetin, prunitrin, and isoferulic acid, were found in few NCS samples. Variations among in vitro antioxidant activity could be correlated (r ≥ 0.5) to phenolics and flavonoids contents. Shelf-life assessment of representative NCS powder and blocks at two different storage conditions showed lower microbial stability of blocks compared to powders (p < 0.05). Therefore, NCS produced at the same unit during the same season cannot be considered as a standard composition of micronutrients and bioactives. This research provides more evidence demonstrating how the location, processing method, and sugarcane variety used can affect the nutritional profile of NCS and their potential health benefits.

Coconut (Cocos nucifera L) jaggery is an alternative sweetener, especially among rural Asian communities. The focus of this study is the evaluation of in vitro digestibility and prediction of glycemic index (PGI) for four types of coconut jaggery; jaggery produced from traditional sap collection method using hal bark (Vateria capalifera) (HAL Jaggery), the jaggery prepared from pure sap collected from a novel sap collection device (NSCM Jaggery), jaggery from collected sap through a novel sap collection method with 0.2% cinnamon (Cinnamomum zeylanicum) (CIN Jaggery) and the jaggery value added with 0.05% of nutmeg (Myristica fragrans) (NUT Jaggery). Digestion and digestibility tests for each type of sweetener were done with cane sugar as a comparison. Results revealed that four types of jaggery have different hydrolysis rates from 30 to 180 min. The hydrolysis index (HI) of cane sugar was significantly higher than that of the others (55 ± 0.023%), whereas the lowest HI was observed in NUT Jaggery (32 ± 0.014%). According to the in vitro glycemic prediction, all four types of coconut jaggery samples were categorized under a medium GI sweetener, while cane sugar was categorized as a high GI (69.91 ± 0.02) sweetener.