Sugar beet, an important sugar crop, contributes significantly to the world’s sugar production. However, genotype–environment interactions (GEI) often affect the quality characteristics of sugar beet. Hence, understanding the effects of GEI on sugar beet quality can aid in identifying high-quality genotypes that can adapt to different environments. Traditional variance analysis can only be used to examine the yield of a variety and not its specific adaptability to specific conditions. Therefore, more comprehensive analytical methods are required to evaluate the characteristics of the variety under specific environments. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype × environment interaction (GGE) biplot models can be employed to comprehensively evaluate different varieties and address the drawbacks associated with a single evaluation method. Moreover, these models also allow us to explore new varieties more objectively and comprehensively. In this study, the adaptability and stability of 16 sugar beet varieties, in terms of yield and sugar content, were evaluated using AMMI and GGE biplot analysis in seven pilot projects undertaken in 2022. In the assessment of a small but significant proportion of the total GEI variance for the two qualitative traits (yield and sugar content), 80.58% of the variance was explained by the cumulative contribution of IPC1, IPC2, and IPC3. AMMI and GGE biplots clearly highlighted that KWS4207 (G3) exhibited high and stable quality. They also demonstrated that the experiments in Jalaid Banner (Inner Mongolia) (E7) were the most representative. Together, the results suggested that the comprehensive application of AMMI and GGE biplot analysis allowed for a more comprehensive, scientific, and effective evaluation of sugar beet varieties across different regions. The findings offer a theoretical basis for sugar beet breeding and could guide the rational design of experiments for testing new varieties of sugar beet.

The aim of this study was to assess the agronomic traits and genotype by yield × trait (GYT) interactions of sugar beet across seven ecological pilot areas in Northeast and North China using GYT biplot analysis. Utilizing correlation analysis and implementing the AMMI model, GGE biplot, and GYT biplot, the study analyzed the agronomic characteristics including plant height, leaf length, leaf width, leaf stalk diameter, SPAD value, root rot, brown spot, sugar content, and sugar yield of 16 sugar beet varieties in the 2023 regional experiment across seven planting ecological pilot areas. The pairwise correlation between yield and trait combinations was analyzed using the GYT biplot technique. Principal components PC1 and PC2 accounted for 80.19 and 12.31% of genotype-trait interactions. KWS7748 (G1) exhibited broader adaptability and superior yield compared to other varieties across different planting areas. Among the varieties tested in the regional sugar beet experiment, KWS7748 (G1) demonstrated the best comprehensive performance. Simultaneously, in the multi-character evaluation methods of sugar beet varieties, the results of GYT biplot analysis and evaluation proved to be more reliable than those of GGE and GT biplot, indicating its effectiveness as a scientific evaluation method for sugar beet varieties.

Yellowhorn (Xanthoceras sorbifolium Bunge) is an oil-bearing tree species in northern China. In this study, we used yellowhorn from Heilongjiang to analyze the morphological and physiological changes of fruit development and conducted transcriptome sequencing. The results showed that the fruit experienced relatively slow growth from fertilization to DAF20 (20 days after flowering). From DAF40 to DAF60, the fruit entered an accelerated development stage, with a rapid increase in both transverse and longitudinal diameters, and the kernel contour developed completely at DAF40. From DAF60 to DAF80, the transverse and vertical diameters of the fruit developed slowly, and the overall measures remained stable until maturity. The soluble sugar, starch, and anthocyanin content gradually accumulated until reaching a peak at DAF80 and then rapidly decreased. RNA-seq analysis revealed differentially expressed genes (DEGs) in the seed coat and kernel, implying that seed components have different metabolite accumulation mechanisms. During the stages of seed kernel development, k-means clustering separated the DEGs into eight sub-classes, indicating gene expression shifts during the fruit ripening process. In subclass 8, the fatty acid biosynthesis pathway was enriched, suggesting that this class was responsible for lipid accumulation in the kernel. WGCNA revealed ten tissue-specific modules for the 12 samples among 20 modules. We identified 54 fatty acid biosynthesis pathway genes across the genome, of which 14 was quantified and confirmed by RT-qPCR. Most genes in the plastid synthesis stage showed high expression during the DAF40–DAF60 period, while genes in the endoplasmic reticulum synthesis stage showed diverse expression patterns. EVM0012847 (KCS) and EVM0002968 (HCD) showed similar high expression in the early stages and low expression in the late stages. EVM0022385 (HCD) exhibited decreased expression from DAF40 to DAF60 and then increased from DAF60 to DAF100. EVM0000575 (KCS) was increasingly expressed from DAF40 to DAF60 and then decreased from DAF60 to DAF100. Finally, we identified transcription factors (TFs) (HB-other, bHLH and ARF) that were predicted to bind to fatty acid biosynthesis pathway genes with significant correlations. These results are conducive to promoting the transcriptional regulation of lipid metabolism and the genetic improvement in terms of high lipid content of yellowhorn.

Tomato (Solanum lycopersicum) is one of the highest-value vegetable crops worldwide, but tomato planting can be easily affected by leaf mold. Tomato leaf mold disease is caused by Cladosporium fulvum, and plants carrying the Cf genes have effective resistance to C. fulvum. To identify leaf mold resistant varieties and screen for specific cDNA amplified fragment length polymorphism (cDNA-AFLP) molecular markers, tomato plants harbouring genes Cf-5, Cf-11, Cf-19, and the moneymaker (MM) tomato line (without Cf gene) were used as plant materials. The changes in reactive oxygen species (ROS) levels and antioxidant activities of plant leaves after inoculation of C. fulvum were measured. Ethylene (ETH), abscisic acid (ABA) and salicylic acid (SA) contents were also determined. The results revealed that the ROS levels in Cf-19 tomato were the most sensitive to C. fulvum inoculation, while in MM they were the least. The antioxidant enzymes of Cf-carrying plants exhibited different activities as compared to those of MM. In the cDNA-AFLP analysis data, the expression of ERF109, sedoheptulose-1,7-bisphosphatase (SBPase), L-ascorbic acid oxidase (AAO) and Thioredoxin H2 (TRX2) were different between Cf-gene carriers and MM plants. In summary, in the process of leaf–mold interaction, the outbreak of ROS and development of systemic acquired resistance (SAR) are tightly combined with antioxidant enzymes, including thioredoxin. Tomato plants carrying the Cf-19 gene appear to have stronger C. fulvum resistance.