Sorghum (Sorghum bicolor L.) is a promising biomass crop with high yields of cellulose, hemicellulose, and lignin. Sorghum biomass has emerged as an eco-friendly industrial material useful for producing biofuels and bioplastics. This study conducted genotyping-by-sequencing (GBS)-based genome-wide association studies (GWAS) to establish the genetic basis of traits associated with biomass. Specifically, the researchers evaluated agronomic traits and phenolic compounds using 96 sorghum genotypes. Six phenolic compounds, luteolinidin diglucoside, luteolin glucoside, apigeninidin glucoside, luteolinidin, apigeninidin, and 5-O-Me luteolinidin, were found to be the major phenolic compounds in all genotypes. Out of our six detected phenolic compounds (luteolinidin diglucoside, luteolin glucoside, apigeninidin glucoside, luteolinidin, apigeninidin, and 5-O-Me luteolinidin), luteolinidin was the major phenolic compound in all genotypes. Next, a GWAS analysis was performed to confirm significant associations between 192,040 filtered single-nucleotide polymorphisms (SNPs) and biomass-related traits. The study identified 40 SNPs on 10 chromosomes that were significantly associated with heading date (4 SNPs), plant height (3 SNPs), dry yield (2 SNPs), and phenolic compounds (31 SNPs). The GWAS analysis showed that SbRio.10G099600 (FUT1) was associated with heading date, SbRio.09G149200 with plant height, SbRio.06G211400 (MAFB) with dry yield, SbRio.04G259800 (PDHA1) with total phenolic content and luteolinidin diglucoside, and SbRio.02G343600 (LeETR4) with total phenolic content and luteolinidin, suggesting that these genes could play key roles in sorghum. These findings demonstrate the potential value of sorghum as a biomass resource and the potential for selecting sorghum genotypes with reduced phenolic contents for use in the bioindustry.

Cannabis (Cannabis sativa) is a versatile crop belonging to the Cannabaceae family, and is dioecious, typically with separate male and female plants. The flowers of female plants, especially the trichomes, accumulate relatively higher contents of cannabinoids compared with those of male plants. For this reason, to obtain seeds that are genetically female, it is desirable to induce the development of male flowers on a female plant that produces genetically female haploid gametes. Silver thiosulfate (STS) is a highly effective chemical for male flower induction. We investigated male flower induction in three commercial cultivars of female cannabis (Spectrum303, SuperwomanS1, and CBGambit) regarding the treatment frequency, stage of application, and concentration of STS applied as a foliar spray. All three cultivars showed adequate induction of male flowers in response to 1.5 mM STS applied at the early reproductive stage. In particular, SuperwomanS1 was most highly responsive to induction of male flowers, even when treated with 0.3 mM STS at the early reproductive stage. Treatment with three applications of STS was more effective compared with a single application, but a single application of 1.5 mM STS at the early reproductive stage was sufficient for male flower induction. A single STS application during the middle stage of reproductive growth was inadequate for induction of male flowers. However, 6 weeks after three applications of STS, CBGambit exhibited approximately 54% male flower induction at 0.3 mM STS, Spectrum303 showed approximately 56% induction at 3 mM STS, and SuperwomanS1 yielded approximately 26% induction at 1.5 mM (expressed as percentage of total number of individuals with the induced male flowers). Pollen stainability tests using KI-I₂ solution and Alexander’s staining showed high pollen viability with over 65% at different single STS concentrations, indicating that pollen grains induced by STS have sufficient viability for the self-pollination. This study demonstrated that different cultivars of cannabis respond diversely to different STS concentrations and highlighted the potential benefits of three STS applications during the middle reproductive stage for cannabis breeding.

Rapeseed (Brassica napus L.) holds significant commercial value as one of the leading oil crops, with its agronomic features and oil quality being crucial determinants. In this investigation, 73,226 single nucleotide polymorphisms (SNPs) across 95 rapeseed mutant lines induced by gamma rays, alongside the original cultivar (‘Tamra’), using genotyping-by-sequencing (GBS) analysis were examined. This study encompassed gene ontology (GO) analysis and a genomewide association study (GWAS), thereby concentrating on agronomic traits (e.g., plant height, ear length, thousand-seed weight, and seed yield) and oil traits (including fatty acid composition and crude fat content). The GO analysis unveiled a multitude of genes with SNP variations associated with cellular processes, intracellular anatomical structures, and organic cyclic compound binding. Through GWAS, we detected 320 significant SNPs linked to both agronomic (104 SNPs) and oil traits (216 SNPs). Notably, two novel candidate genes, Bna.A05p02350D (SFGH) and Bna.C02p22490D (MDN1), are implicated in thousand-seed weight regulation. Additionally, Bna.C03p14350D (EXO70) and Bna.A09p05630D (PI4Kα1) emerged as novel candidate genes associated with erucic acid and crude fat content, respectively. These findings carry implications for identifying superior genotypes for the development of new cultivars. Association studies offer a cost-effective means of screening mutants and selecting elite rapeseed breeding lines, thereby enhancing the commercial viability of this pivotal oil crop.

Hyperspectral imaging (HSI) has emerged as a powerful tool for non-destructive phenotyping, yet fruit crop applications remain underexplored. We propose a methodological framework to enhance the spectral characterization of apple fruits by identifying robust vegetation indices (VIs) and interpretable endmembers. We screened 284 Vis, which were evaluated using four feature selection algorithms (Boruta, MI+Lasso, RFE, and ensemble voting), generalizing across red, yellow, green, and purple apple cultivars. An ensemble criterion (≥2 algorithms) yielded 50 selected VIs from the NDSI/DSI/RSI families, preserving > 95% classification accuracy and capturing cultivar-specific variation. Pigment-sensitive wavelength bands were identified via PLS-DA VIP scores and one-vs-rest ANOVA. Using these bands, we formulated a new normalized-difference, ratio, and difference spectral indices tailored to cultivar-specific pigmentation. Several indices achieved >89% classification accuracy and showed patterns consistent with those of anthocyanin, carotenoid, and chlorophyll. A two-stage spectral unmixing pipeline (K-Means → N-FINDR) achieved the lowest reconstruction RMSE (0.043%). This multi-level strategy provides a scalable, interpretable framework for enhancing phenotypic resolution in apple hyperspectral data, contributing to fruit index development and generalized spectral analysis methods for horticultural applications.

Kenaf (Hibiscus cannabinus L.), in the Malvaceae family, is an important crop for not only fiber production, but also various other industrial materials. We performed phylogenetic analysis and a genome-wide association study (GWAS) of seven agronomic traits: days to flowering, plant height, fresh weight, dry weight, flower color, stem color, and leaf shape, using 96 kenaf genotypes, including gamma-irradiation-derived mutant lines. Genotypes were determined by genotyping-by-sequencing (GBS) and a total of 49,241 single-nucleotide polymorphisms (SNPs) were used in the analysis. Days to flowering, plant height, fresh weight, and dry weight were positively correlated with each other, and stem color was also correlated with fresh weight and dry weight. The phylogenetic analysis divided the 96 lines into nine related groups within two independent groups, and the GWAS analysis detected a total of 49 SNPs for days to flowering, plant height, fresh weight, dry weight, flower color, stem color, and leaf shape with −log₁₀(P) ≥ 4, of which 22 were located in genic regions. The detected SNPs were located in genes with homology ranging from 45% to 96% to plants of the Malvaceae and Betulaceae, and these genes were found to be involved in plant growth and development via various pathways. Our identification of SNP markers related to agronomic traits is expected to help improve the quality of selective breeding programs for kenaf.