Crop Science最新文献

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.

Frequently occurring extreme weather events and environmental changes may significantly reduce corn (Zea mays L.) yields. Thus, the selection of favorable traits and stable genotypes has emerged as a fundamental objective of breeding programs aimed at countering adverse weather effects. Field experiments in eight environments were conducted in 2019 and 2020 to evaluate the performance and stability of 93 inbred maize lines by multiple models and parameters. The genotype–environment interaction (GEI) plot and GEI effect functions in the Metan package were used to visualize the response patterns of different genotypes in multiple environments. Response patterns of 93 inbred lines with different traits across eight environments were constructed, revealing substantial GEI for anthesis–silking interval, days to 50% anthesis, and days to 50% silking, which were primarily influenced by environmental factors. Through evaluation by multiple methods, a total of 13 genotypes demonstrated excellent performance across four or more parameters or models, such as Zong31, Xz5426, and so forth. Based on the multi-trait stability index (MTSI) model, all traits were positively selected. Grain yield had the highest selection weight at 25.8%, while ear barren tip had the lowest at 6.19%. Thirteen genotypes were selected, with DH509-9 being the most stable (MTSI = 3.75). Cross-validation revealed superior predictive accuracy in all additive main effects and multiplicative interaction (AMMI) models compared to best linear unbiased prediction (BLUP) models. The mean root mean square prediction difference was highest for AMMI0 (72.06) and lowest for BLUP_e (27.08), and AMMI0 model was the optimal model. The approach investigated in this research has the potential to significantly streamline the decision-making process for breeders to identify genotypes characterized by both high average performance and robust phenotypic stability.

The native, perennial shrub American hazelnut (Corylus americana) is cultivated in the US Midwest for its significant ecological benefits, as well as its high-value nut crop. Genetic improvement of perennial crops involves long-term breeding efforts, and benefits from the use of genetic data in selection to reduce breeding cycle time. In addition, high-throughput phenotyping methods are essential to the efficient and accurate screening of large breeding populations. This study reports novel advances in both of these domains, for American (C. americana) and interspecific hybrids between European (Corylus avellana) and American hazelnuts. Two populations of hazelnuts, one composed of C. americana and one composed of C. americana × C. avellana hybrids, were phenotyped over the course of 2 years in two locations using a digital imagery-based method for quantifying morphological nut and kernel traits. These data were used to perform composite interval mapping using a recently released genetic map, and genomic prediction using a newly available chromosome-scale reference genome for C. americana. Multiple quantitative trait loci were detected for all traits analyzed, with an average total R² of 52%. Genomic prediction exhibited high accuracy, with an average correlation coefficient between genotypic values and phenotypic observations of 0.78 across both environments. These results suggest that incorporating genetic data in selection is a tenable method for improving genetic gain for highly polygenic traits in hazelnut breeding programs.

In the context of over-fertilization, especially of phosphorus (P), the debate about the usefulness of applying starter fertilization to maize (Zea mays L.) must be revisited. One solution is to breed crops with an enhanced phosphorus use efficiency, which require less fertilizer yet are high-yielding. This study examined a diverse panel of Flint elite lines and double haploid lines from six European landraces, which were crossed with two Dent testers. The resulting 588 testcross hybrids were evaluated under two fertilization treatments: with and without the addition of a di-ammonium phosphate starter fertilization. The omission of the starter fertilization led to a decrease in early developmental traits, like plant height and biomass, in all four tested environments. Surprisingly, grain yield increased in three out of four environments, an effect that was especially noticeable in the landrace line testcrosses and is possibly caused by the increased ability to cope with environmental stress occurring at later developmental stages. Importantly, there is substantial genetic variation that can be exploited in breeding for the response to fertilizer levels, with some landrace testcrosses performing in the range of the Flint elite testcrosses. Furthermore, additive genetic effects were found to be the main contributor to early developmental traits and grain yield under both fertilization treatments. These results suggest that landraces may offer valuable genetic variation for breeding for reduced phosphate fertilizer input. In conclusion, breeding programs should include breeding for nutrient acquisition but combined with a tolerance to withstand seasonal climate variations.