Crop Science最新文献

Betalain pigments, betacyanins, and betaxanthins are widely used as coloring agents as well as in pharmaceutical and functional foods. However, significant betacyanin production occurs in only a few species of plants, which limits their wider application. We used the reporter gene RUBY controlled by CaMV 35S promoter to produce betalain in alfalfa (Medicago sativa L.). Betalain pigments were produced throughout the plant with the intensity of coloration varying with RUBY expression. Concentrations of betacyanin in herbage ranged from 50 to 650 mg/100 g dry wt and betaxanthin from 0.28 to 2.55 mg/100 g dry wt, significantly higher than in roots of table beet. Also, alfalfa plants expressing RUBY reduced methane production in in vitro enteric methane assays and had increased stem cell wall fiber digestibility compared to wild-type plants. Alfalfa plants expressing RUBY would provide a low cost and sustainable source of betalain for food and feed applications. When RUBY alfalfa is incorporated into rations, it could be advantageous in cattle production systems to increase forage digestibility and protein synthesis.

Song, Q., Du, C., Wang, J., & Zuo, K. (2025). Spatiotemporal lipid remodeling and signaling networks in cotton fiber development. Crop Science, 65, e70196. https://doi.org/10.1002/csc2.70196

The authors were listed in the incorrect order in the byline as Kaijing Zuo, Qingwei Song, Jin Wang, and Chuanhui Du. The correct order is Qingwei Song, Chuanhui Du, Jin Wang, and Kaijing Zuo.

The author order was also incorrectly presented in the Author Contributions section: Kaijing Zuo: Writing—review and editing. Qingwei Song: Writing—original draft. Jin Wang: Writing—review and editing. Chuanhui Du: Writing—original draft. The correct order is Qingwei Song: Writing—original draft. Chuanhui Du: Writing—original draft. Jin Wang: Writing—review and editing. Kaijing Zuo: Writing—review and editing.

We apologize for this error.

Ultra-early seeding provides several benefits for hexaploid wheat (Triticum aestivum L.), including an extended planting window, grain yield protection, enhancement and stability, earlier harvest, and improved weed competitiveness. However, a knowledge gap exists around whether durum wheat (Triticum turgidum ssp. durum) is also amenable to this practice. Thus, an experiment was conducted at four locations in Alberta and Saskatchewan, Canada, from 2022 to 2024. The treatment combinations consisted of five durum wheat cultivars, planted at six soil temperature triggers separated by 2°C increments beginning at 0°C through to 10°C. Among the cultivars, irrespective of planting time, AAC Donlow, CDC Defy, and AAC Stronghold attained similar grain yields when averaged across all environments, which were superior to CDC Desire and Transcend. Planting at a soil temperature of 2°C measured at the 5-cm soil depth generally resulted in higher grain yields and greater net returns. Moreover, a partial least squares regression-additive Main effects and multiplicative interaction analysis indicated that a 2°C planting system was better adapted to warmer June and arid summer conditions, which suggests the system imparts enhanced heat and drought stress resilience. If planting was delayed—that is, ≥10°C soil temperature—a yield drag was usually experienced. Grain protein concentration was not affected by the soil temperature trigger. Thus, commercially available durum cultivars are amenable to ultra-early seeding and optimized when planted at a soil temperature of 2°C, which could increase returns by $CAD 134 ha⁻¹. Future studies will investigate durum responses when planted ultra-early versus dormant-plantings in fall, with variations to planting depth.

We promote whole-genome pooled sequencing data as a persistent, reusable resource to improve management and utilization of heterogeneous germplasm collections. Using 14.9 Tbp of DNA sequence data from 4987 individuals in the sugar beet (Beta vulgaris L. ssp. vulgaris) primary gene pool as a test case, we demonstrate appropriate analytical procedures to reveal population structure, assemble optimized subsets, perform allele mining, and contribute to gene discovery. Table, sugar, fodder, and leaf beets were found to be genetically distinct, with an affinity shown between wild and leaf beets. Differing genetic trajectories were inferred for germplasm releases from four regional U.S. Department of Agriculture-Agricultural Research Service sugar beet breeding programs. Using a germplasm panel developed to represent broad-sense variation in B. vulgaris L. ssp. maritima, we show that the wild relative is variable, divergent, and remains underexploited despite an established, successful history of wild introgressions. We discover that novel Rz2-type rhizomania disease resistance alleles are common in table beets and the wild relative but are uncommon in US sugar beet germplasm. Phenotypic characterization data held in gene banks can be used with pooled sequencing data for association analyses—a whole-genome signature of selection scan identified BvWIP2 as a candidate gene for monogerm seed development, a valuable trait in beets, consistent with a recent association study using single individuals. Mass production of whole-genome pooled sequencing datasets linked to gene bank collections would minimize the need to re-sequence individuals, in some cases eliminating the wet lab component of genetic studies, shifting the emphasis of gene discovery to phenotyping and bioinformatics.

Elderberries (Sambucus spp.) have been valued as food and medicine around the world for millennia. Elderberry products are experiencing an increase in demand as ongoing research substantiates their putative health benefits. European elderberries (Sambucus nigra subsp. nigra) are an established industry in Europe and are often imported into the United States to meet demand for elderberry products. However, European cultivars do not reliably perform well in US Midwest environments. American elderberry (Sambucus nigra subsp. canadensis) is native to eastern North America and has only recently seen an increase in production and research efforts. The growing American elderberry industry in North America is mainly supported by cultivars selected from the wild. Targeted breeding efforts have the potential to substantially improve the performance and quality of American elderberry cultivars in a way that helps meet growing demand for domestic elderberry products. The following review summarizes foundational research on American elderberry performance, phenology, quality, and composition that informs emerging breeding efforts. Existing germplasm resources and trials are also summarized to aid both producers and new breeding initiatives, highlighting opportunities for growth. The body of work presented enables the informed development of new breeding pipelines and processes for American elderberries in the southern US Midwest, which are in their early stages but are well-positioned to support industry growth and production.

The Solanaceae family comprises several species of flowering plants, including economically important food crops that contribute to a substantial proportion of our nutritional needs, such as Solanum tuberosum (potatoes), Solanum lycopersicum (tomatoes), Solanum melongena (eggplants), and Capsicum annuum (peppers). However, the yield and quality of vegetable crops are constrained by several endemic and emerging pests and diseases. Understanding the host defense mechanisms that govern disease susceptibility and resistance can help develop strategies to prevent yield losses and improve quality. Recently, the role of epigenetic regulation in mediating biotic stress responses has garnered attention. This review provides a comprehensive insight into recent progress in understanding epigenetic regulation that mediates biotic stress responses in solanaceous crops. The dynamic DNA methylation and histone modifications that correlate with the differential expression of defense-responsive genes, conferring tolerance to pathogens, have been discussed. In addition, the identification of numerous microRNAs and long noncoding RNAs in the context of biotic stress, and the functional validation of a few of them, which confer tolerance against pathogens, has been elucidated. Although a few studies have analyzed epigenetic responses to biotic stress in solanaceous vegetable crops, several caveats remain, including the functional identification of immune-responsive genes modulated by epigenetic marks and noncoding RNAs, which present an excellent opportunity to explore further the mechanisms of biotic stress response in solanaceous plants. Moreover, we also discuss epigenetic memory, which is involved in defense against subsequent infections, and transgenerational memory, which can influence the immune response of progeny.

Genomic selection (GS) is a powerful strategy for accelerating genetic gain in plant breeding. While in recent years GS has been widely adopted in breeding programs for agronomic crops, its implementation in vegetable breeding has been comparatively limited. Vegetable breeders face many unique challenges that impede the direct translation of GS implementation strategies from agronomic breeding programs. These challenges include the large number of traits that are important for cultivar development, the difficulty in quantitatively phenotyping many of these traits, especially those related to quality and sensory attributes, and the diversity of reproductive strategies and biological features represented among different vegetable crops. Successful vegetable breeders have been able to efficiently develop new varieties with improved quality and productivity, while constantly adapting to shifting market demands and growing methods, by complementing their understanding of heredity with elements of creativity and intuition-based decision-making. Like earlier advances in genetics and statistics that were once viewed as only theoretical, we feel GS can become an additional part of breeders’ routine selection strategy and, ultimately, another element of the “art” of vegetable breeding.

African yam bean (AYB), or sphenostylis stenocarpa (Hochst. Ex. A. Rich) Harms, is a leguminous crop with potential to enhance food security and agricultural sustainability. A total of one hundred Africa yam bean accessions from six Nigeria states were planted for agronomic evaluation. Out of 100 samples, ninety-four accessions were genotyped using DArTseq approach and generated 2527 high-quality single-nucleotide polymorphism (SNP) polymorphic markers. The QC-filtered markers had a call rate ≥0.80, marker reproducibility ≥0.95, minor allele frequency ≤0.01, and missing data ≤20%. The expected heterozygosity varied from 0.007 to 0.201 while the observed heterozygosity varied from 0.015 to 0.121. The overall inbreeding coefficient (FIS) was 0.623. The results revealed diversity within the AYB accessions for both the agronomic trait and SNP markers. Analysis of variance revealed significant variations (p ≤ 0.05) in traits such as total seed weight, days to first flower, and pod length (PODL), suggesting genetic diversity within the population. Tropical Sphenostylis stenocarpa (TSs) accessions TSs-513, TSs-560, TSs-526, TSs-571, TSs-581, TSs-601, TSs-602, and TSs-582 exhibited excellent performance for some traits such as number of seeds per pod, PODL, and days to first flowering. Neighbor-joining cluster analysis grouped the AYB population into four main clusters, where majority of Abia, Enugu, and Cross River states AYB accessions were grouped together with their origin. Population structure analysis results were consistent with the cluster analysis. The comprehensive view of genetic diversity and population structure analysis, highlights both genetic distinctness between geographical origin and relationship among accessions. The results of genetic diversity and population structure analysis confirmed that there is substantial genetic variation among the AYB accessions. These results provide valuable insights for AYB breeding in sub-Saharan Africa, enabling the selection of diverse parental lines, maintaining genetic variability, and enhancing adaptability. Understanding genetic structure enables efficient germplasm conservation and the development of improved, resilient breeding populations.

Accurate simulation of the crop growth process was the foundation for the development of smart agriculture. However, the uncertainty of crop growth models limits their practical application. This study integrates the Soil Water Atmosphere Plant (SWAP) model with the Iterative Ensemble Smoother (IES) algorithm to develop the SWAP–IES optimization approach and explores various uncertainty factors of the system, including the ensemble size, observational errors setting, combination of observation variables and their corresponding observation stages, and uncertain parameters selection. The results suggested that, under water stress conditions, an ensemble size of 50 was recommended. It was advisable to choose leaf area index (LAI) and soil moisture content (SW) as observation variables, focusing on monitoring data from the flowering to the milk stage. The suitable observational error settings for LAI and SW were 0.3–0.5 m² m⁻² and 0.03–0.05 cm³ cm⁻³, respectively. For uncertain parameters, it was recommended to select the five crop parameters (RGRLAI, SPAN, CVO, EFF, and CVL) and three soil parameters (θ_s, K_s, and n) for simulation. The SWAP-IES, validated with 2020 and 2021 spring wheat (Triticum aestivum L.) experiments, demonstrated high accuracy in simulating yields, with root mean square error values of 0.56 and 0.61 t ha⁻¹, respectively. The SWAP–IES optimization approach could significantly reduce the uncertainty in the simulation process and improve simulation accuracy by optimizing the system settings strategy.

Farmers often use private and public labs, crop advisors, or fertilizer dealers to determine fertilizer needs for crops, with recommendations and resulting costs from these sources having the potential to vary greatly. Twelve on-farm trials across the state of Utah in alfalfa (Medicago sativa), small grain forage, and silage corn (Zea mays) were established in 2021 to compare fertilizer recommendations from five labs and a nonfertilized control, two public labs (Utah State University and University of Idaho), and three commercial labs in the Western United States, with some sites being replicated in 2022–2023. A baseline soil sample from each field was split and sent to multiple labs for analysis and corresponding nutrient rates recommended by each lab applied at each site. Fertilizer recommendations from the five laboratories varied greatly, both for types of nutrients and rates recommended, with differences between highest and lowest treatment costs ranging from $528 to $2024 ha⁻¹ across sites. Crop yield and forage quality data were collected from sites from 2021 to 2023, with fertilizer treatments having little to no impact at four silage corn or five alfalfa sites. Yield was increased by at least one private and university lab at all three small grain forage sites and crude protein content was increased at sites with multiple years of data. Fertilizer treatments occasionally improved forage yield and quality but not crop market value. The results of this study demonstrate that growers should be aware when selecting fertilizer recommendations, and opportunities exist for better public-private coordination of science-based recommendations.