Cauliflower is one of the most important vegetable crops grown worldwide. However, the lack of genetic diversity information and efficient molecular markers hinders efforts to improve cauliflower. This study aims to construct DNA fingerprints for 329 cauliflower cultivars based on SNP markers and the KASP system. After rigorous filtering, a total of 1662 candidate SNPs were obtained from nearly 17.9 million SNP loci. The mean values of PIC, MAF, heterozygosity and gene diversity of these SNPs were 0.389, 0.419, 0.075, and 0.506, respectively. We developed a program for in silico simulations on 153 core germplasm samples to generate ideal SNP marker sets from the candidates. Finally, 41 highly polymorphic KASP markers were selected and applied to identify 329 cauliflower cultivars, mainly collected from the public market. Furthermore, based on the KASP genotyping data, we performed phylogenetic analysis and population structure analysis of the 329 cultivars. As a result, these cultivars could be classified into three major clusters, and the classification patterns were significantly related to their curd solidity and geographical origin. Finally, fingerprints of the 329 cultivars and 2D barcodes with the genetic information of each sample were generated. The fingerprinting database developed in this study provides a practical tool for identifying the authenticity and purity of cauliflower seeds and valuable genetic information about the current cauliflower cultivars.

Brassinazole resistant 1 (BZR1), a brassinosteroid (BR) signaling component, plays a pivotal role in regulating numerous specific developmental processes. Our study demonstrated that exogenous treatment with 2,4-epibrassinolide (EBR) significantly enhanced the accumulation of carotenoids and chlorophylls in Chinese kale (Brassica oleracea var. alboglabra). The underlying mechanisms was deciphered through yeast one-hybrid (Y1H) and dual-luciferase (LUC) assays, whereby BoaBZR1.1 directly interacts with the promoters of BoaCRTISO and BoaPSY2, activating their expression. This effect was further validated through overexpression of BoaBZR1.1 in Chinese kale calli and plants, both of which exhibited increased carotenoid accumulation. Additionally, qPCR analysis unveiled upregulation of carotenoid and chlorophyll biosynthetic genes in the T1 generation of BoaBZR1.1-overexpressing plants. These findings underscored the significance of BoaBZR1.1-mediated BR signaling in regulating carotenoid accumulation in Chinese kale and suggested the potential for enhancing the nutritional quality of Chinese kale through genetic engineering of BoaBZR1.1.

Cauliflower (Brassica oleracea var. botrytis) is a popular vegetable worldwide due to its delicious taste, high nutritional value and anti-cancer properties. Cauliflower normally produces white curds, and natural spontaneous mutations lead to the production of orange, purple or green curds. However, some white cauliflowers show uneven purple pigmentation in their curds, which seriously affects the appearance quality and economic value of this crop. The underlying mechanism is still unclear. In this study, we performed comparative transcriptional and metabolic profiling analysis of light orange, white and purplish cauliflower curds. Metabolite analysis revealed that the pigments conferring purple colouration were delphinin and cyanin. Transcriptome analysis showed that the anthocyanin metabolism-related structural genes DFR, ANS and UGT and the transcription factor genes PAP2, TT8, GL3, EGL3 and TTG1 were upregulated in purplish versus white curds. These findings shed light on the formation of purplish curds, which could facilitate the breeding of purely white or red cauliflower.

Cauliflower is a nutritious vegetable with inflorescences that are specialized to form the edible organs called curds. Uncovering key genes underlying important traits is crucial for the genetic improvement of this important crop. However, the genetic basis of many important agronomic traits, including curd performance and plant architecture in cauliflower, remains unclear. GWASs have proved to be powerful tools to study agronomic traits in many crops. To reveal the genetic basis of four important agronomic traits, namely, the main stem height (MSH), purplish curd (PC), external leaf wing (ELW) and weight of a single curd (WSC), we selected 220 core accessions of loose-curd cauliflower for resequencing, phenotypic investigation and GWAS. The approach revealed significant novel loci. We detected several significant associations: on C02 for MSH and PC, on C06 for ELW and on C01 for WSC. More interestingly, we identified a significant single-peak signal for the weight of a single curd (WSC), an important yield trait, and within this signal interval, we identified the BOB01G136670 gene with five SNPs encoding nonsynonymous mutations in the CDS region; these mutations resulted in two haplotypes with significant differences in curd weight. The weight of a single curd was significantly increased in the varieties with the BOB01G136670 ^Hap1 allele compared to those with BOB01G136670 ^Hap2. BOB01G136670 was highly conserved with the homologous genes that encode serine carboxypeptidase and belong to the S10 family in other species, including GS5, which functions as a positive regulator of grain size in rice, wheat and maize. Additionally, BOB01G136670 was highly expressed specifically at the curd enlargement stage, with low or even no expression at all in other tissues and stages, indicating that BOB01G136670 is a plausible candidate gene for WSC. Overall, this study identified genomic loci for four important agronomic traits that are relevant for accelerating biological breeding and the improvement of cauliflower varieties.

In order to rapidly and non-destructively detect the residual rate of emamectin benzoate+indoxacarb pesticides on cauliflower, a study was conducted using hyperspectral technology to investigate the dissipation law of this pesticide over time. Hyperspectral imaging was employed to capture spectral data from cauliflower samples with and without the pesticide, focusing on the region of interest. The spectral data, consisting of 216 bands (ranging from 950 nm to 1666 nm), were preprocessed using techniques such as Savitzky–Golay convolution smoothing (S-G), multivariate scattering correction (MSC), and standard normal variate (SNV). Next, characteristic spectra for each pesticide were extracted using the competitive adaptive reweighted sampling algorithm (CARS). This study utilized the partial least squares (PLS) algorithm to construct a discriminative model aimed at identifying pesticide residues on cauliflower. The accuracy of the hyperspectral imaging technique was validated by comparing the results with those obtained through chromatography. The PLS model, optimized using the SNV method, exhibited the highest discriminant accuracy, achieving a recognition rate of 100%. The residual rate of indoxacarb detected through hyperspectral technology closely corresponded to the results obtained through chromatography. It was found that the discrepancy in the half-life of pesticides as detected by hyperspectral and chromatographic methods is a mere 0.14 days. These findings highlight the potential of hyperspectral imaging technology for studying pesticide dissipation on cauliflower and detecting pesticide residues.