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Crops

Crops is an international, peer-reviewed, open access journal on the science and technology of crops published bimonthly online by MDPI.

Quartile Ranking JCR - Q2 (Agronomy)

All Articles (199)

Blue light (BL) is a key environmental signal influencing plant flowering, yet its role in floral development beyond the transition phase remains underexplored. This review provides a comprehensive synthesis of current research on BL-mediated floral development, with a particular emphasis on horticultural crops grown in a controlled environment. Unlike prior reviews that focus primarily on floral induction, this article systematically examines BL’s effects on later stages of flowering, including floral organ morphogenesis, sex expression, bud abortion, flower opening, scent emission, coloration, pollination, and senescence. Drawing on evidence from both model plants (e.g., Arabidopsis thaliana) and crop species, this review identifies key photoreceptors, hormonal regulators, and signaling components involved in BL responses. It also highlights species-specific and context-dependent outcomes of BL manipulation, proposes mechanistic hypotheses to explain conflicting findings, and outlines critical knowledge gaps. By integrating molecular, physiological, and environmental perspectives, this review offers a framework for optimizing BL applications to improve flowering traits and postharvest quality in horticultural production systems.

15 October 2025

The physiological mechanisms underlying flower sex expression mediated by blue light, as well as other potentially integrated signals. PPS = phytochrome photostationary state; PHYB = phytochrome B; CRY1 = cryptochrome 1; AP3 = APETALA3; PI = PISTILLATA; ARR17 = ARABIDOPSIS RESPONSE REGULATOR 17; MeGI = MALE GROWTH INHIBITOR; ASC11 = AGAMOUS-LIKE SUPPRESSOR OF CYTOKININ 11; WIP1 = WOUND-INDUCED PROTEIN 1; ACS 7 = 1-aminocyclopropane-1-carboxylic acid synthase 7; AG = AGAMOUS; GA = gibberellin; ABA = abscisic acid; JA = jasmonic acid; CTK = cytokinin. In the diagram, the green rectangles are other signals that may integrate with blue light pathway; the blue rounded rectangles are photoreceptors or photosynthetic pigments; the pink ovals are transcription factors or other regulators; the yellow hexagons are key floral regulators. The dashed rectangles include a group of integrated signals. The dashed action lines indicate that the action can be affected by many factors, or the involved detailed action mechanism is still unclear.

Durum wheat is a vital wheat species cultivated worldwide for human consumption, ranking second to bread wheat. The Ethiopian durum wheat allele pool shows wide gene diversity; however, limited improvement work has been done to exploit this diversity. Thus, this study aimed to assess the genetic variability, heritability, and interrelationship among different phenotypic traits in 210 recombinant inbred lines (RILs) using an alpha lattice design with two replications. The analysis of variance revealed a significant difference for all the measured traits. The phenotypic coefficient of variation (PCV) was greater than the genotypic coefficient of variation (GCV) for all the characters, which reflects that the existing range of variability within the genotypes was not only due to the varying influence of genotype but also the environment. A correlation analysis disclosed that grain yield was positively related to the traits of plant height and 1000-kernel weight, suggesting that selecting these traits could enhance yield. Path analysis revealed that days to booting, maturity, and 1000-kernel weight directly affect grain yield. Among the measured traits, early developmental traits revealed higher broad-sense heritability. The findings of this study highlight high genetic diversity among Ethiopian durum wheat genotypes, opening up opportunities to integrate these materials into future wheat-breeding programs through introgression with other germplasm sources in Ethiopia and beyond.

15 October 2025

Map showing the geographical location of the experimental site (shaded green and red). (Note: All boundaries are approximate and do not correspond to political borders.) The map was created using the ArcGIS software suite version 10.7.1.

Elephant grass (Pennisetum purpureum Schumach, EG) is a promising biomass energy crop due to its high productivity and adaptability to harsh environments. In the transition to renewable energy, varietal evaluation is essential to identify cultivars that maximize biomass and energy yield. This study assessed three varieties (VS-19, VA-06, and VDP as control) across three harvest cycles (new planting, first regrowth, and second regrowth) between 2022 and 2024 at the Cotton and Agricultural Development Research Institute, Ninh Thuan Province, Vietnam. The site was characterized by mean temperatures of 25–36 °C, relative humidity of 65–82%, and average precipitation of 75.7 mm per month. Agronomic traits, energy potential (heating oil equivalent per hectare, HOE/ha), forage quality, and soil amendment value of the EG were examined to address the research question whether EG can be integrated into a three-cycle utilization model (energy, forage, soil amendment) to support a circular bioeconomy in Vietnam. All cultivars showed good growth, strong drought tolerance, and resistance to pests and diseases. VS-19 showed superior tillering, strong lodging resistance, and the highest biomass yield (63.8 t/ha) with an energy output of 32,636 HOE/ha, while VA-06 (56.1 t/ha; 28,699 HOE/ha) and VDP (54.7 t/ha; 27,952 HOE/ha) produced slightly lower but comparable outputs. Forage evaluation indicated moderate nutritional quality, while residues from the third cycle showed favorable carbon and nutrients content, making EG suitable as a soil amendment. EG thus demonstrates high biomass and energy yields, forage potential, and soil improvement capacity, reinforcing its role in integrated bioenergy and agricultural systems.

14 October 2025

Morphological characteristics of EG varieties before harvest; (a) Plant height; (b) Number of dried basal leaves; (c) Number of visible internodes.

Predicting Plant Breeder Decisions Across Multiple Selection Stages in a Wheat Breeding Program

  • Sebastian Michel,
  • Franziska Löschenberger and
  • Christian Ametz
  • + 2 authors

Selection decisions in plant breeding programs are complex, and breeders aim to integrate phenotypic impressions, genotypic data, and agronomic performance across multiple selection stages to develop successful varieties. This study investigates whether such decisions can be predicted in a commercial winter wheat (Triticum aestivum L.) breeding program using elastic net models trained on genome-wide distributed markers and genomic estimated breeding values. For this purpose, a dataset of several thousand lines tested between 2015 and 2019 in preliminary, advanced, and elite multi-environment yield trials was analyzed across three decision-making scenarios. The predictive models achieved a higher precision than random selection in all scenarios, with an increased performance when genomic estimated breeding values were included as predictors. Comparisons of breeder selections and model recommendations in terms of selection differentials for key agronomic traits showed a substantial overlap in breeding objectives, while both the breeder’s decisions and the model’s suggestions maintained similar levels of genetic diversity. Although the precision of the elastic net model was of moderate magnitude, divergent model recommendations often identified promising alternative lines, highlighting the potential of artificial intelligence to support decision-making in plant breeding.

2 October 2025

Number of non-selected lines (
  
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) versus lines that were selected once (
  
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) or twice (
  
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) from each cohort in 2015–2019 based on the breeder’s decisions in the respective preliminary yield trials as well as two subsequent years of advanced and elite multi-environment trials.

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Crops - ISSN 2673-7655Creative Common CC BY license