{
  "abstract": "Wheat (Triticum aestivum L.) yield in Pakistan has remained stagnant over the past two decades mainly due to the narrow genetic diversity of cultivated varieties. To overcome this limitation and explore new genetic resources for improved productivity, twelve Chinese wheat hybrid lines were evaluated in comparison with two local cultivars at the Agronomy Research Farm, the University of Agriculture Peshawar, Pakistan over two seasons (2021–2022, 2022–2023). Results showed that early emergence occurred in the hybrid lines 20 BH 37 and 20 BH 53 (12.5 days). Wheat lines 20 BH 53 and 20 BH 56 produced higher number of tillers m-2 (441 and 412), spike density (396 and 391 spikes m-2), thousand grain weight (41.9 g and 43.5 g), grains spike-1 (54 and 56), biological yield (9561 and 9306 kg ha-1), and grain yield (4253 and 4225 kg ha-1), respectively. Hybrid lines 20 BH 53 and 20 BH 56 also exhibited a 17–18% increase in grain yield over Wadan-17 and a 16–17% increase over Akbar-19, highlighting their potential as superior genetic resources for wheat productivity enhancement. Positive correlation was observed for grain yield and yield components. Principal component analysis revealed considerable genetic diversity among the tested hybrid lines, supporting their inclusion in future breeding programs. It is concluded that wheat hybrid lines 20 BH 53 and 20 BH 56 outperformed in yield and yield traits over local cultivars under semiarid conditions, indicating their suitability for agro-ecological conditions of northern parts of Pakistan and for future breeding programs.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Agronomy, The University of Agriculture, Peshawar, Pakistan",
    "Institute of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Science, Beijing, China",
    "Department of Agronomy, Amir Muhammad Khan Campus Mardan, The University of Agriculture, Peshawar, Pakistan",
    "Department of Agriculture, University of Swabi, Pakhtunkhwa, Pakistan"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Hamid Ali Khan"
    },
    {
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        1
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      "name": "Muhammad Arif"
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      "name": "Shengquan Zhang"
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    {
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        3
      ],
      "name": "Fazal Munsif"
    },
    {
      "name": "Hongyao Lou"
    },
    {
      "name": "Yutian Gao"
    },
    {
      "name": "Basit Ullah"
    },
    {
      "name": "Muhammad Mehran Anjum"
    },
    {
      "name": "Maaz Khan"
    },
    {
      "name": "Beena Saeed"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5bdyvajzzb6nf.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0356875",
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  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
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  "native_subjects": [
    [
      "openalex",
      "1110|Wheat and Barley Genetics and Pathology"
    ],
    [
      "plos",
      "/Biology and life sciences/Agriculture/Agricultural soil science"
    ],
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      "plos",
      "/Biology and life sciences/Agriculture/Agronomy"
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      "/Biology and life sciences/Agriculture/Agronomy/Plant breeding"
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      "plos",
      "/Biology and life sciences/Organisms/Eukaryota/Plants/Grasses/Wheat"
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      "/Physical sciences/Mathematics/Statistics/Statistical methods/Multivariate analysis/Principal component analysis"
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      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Multivariate analysis/Principal component analysis"
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  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0356875&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-11",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/5bdyvajzzb6nf.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:56Z",
      "native_id": "10.1371/journal.pone.0356875",
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      "url": "https://doi.org/10.1371/journal.pone.0356875"
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  "subjects": [
    {
      "field": "earth",
      "origin": "plos:meteorology",
      "subfield": "atmospheric"
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    {
      "field": "earth",
      "origin": "plos:soil science",
      "subfield": "hydrology-soils"
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    {
      "field": "mathematics",
      "origin": "plos:statistical methods",
      "subfield": "statistics"
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  "title": "Unlocking wheat yield potential through evaluation of high-performing hybrid lines in semiarid conditions of northern Pakistan",
  "title_text": "Unlocking wheat yield potential through evaluation of high-performing hybrid lines in semiarid conditions of northern Pakistan",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:56Z",
  "url": "https://research.draconitic.com/paper/5bdyvajzzb6nf",
  "venue": "PLOS One",
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}