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Physiology and Molecular Biology of Plants : an International Journal of Functional Plant Biology|September 23, 2024
Exploring novel SNPs and candidate genes associated with seed allometry in <i>Pisum sativum</i> LBhubneshwari Khajuria, Prakriti Rajput, Rehana Chowdhary, et al.
Plant Science : an International Journal of Experimental Plant Biology|September 18, 2025
The role of root phene interactions in zinc and copper uptake efficiency in maize under NPK fertilizationPrakriti Rajput, Shubham Sharma, Haroon Rashid Hakla, et al.
Physiologia Plantarum|June 18, 2024
Natural variation in root traits identifies significant SNPs and candidate genes for phosphate deficiency tolerance in Zea mays LPrakriti Rajput, Mohammad Urfan, Shubham Sharma, et al.
Physiology and Molecular Biology of Plants : an International Journal of Functional Plant Biology|April 11, 2022
Green synthesis of zinc oxide nanoparticles using <i>Eucalyptus lanceolata</i> leaf litter: characterization, antimicrobial and agricultural efficacy in maizePooja Sharma, Mohammad Urfan, Rythem Anand, et al.
Chemosphere|August 11, 2022
Paclobutrazol improves surface water use efficiency by regulating allometric trait behavior in maizeMohammad Urfan, Haroon Rashid Hakla, Shubham Sharma, et al.
Plants (Basel, Switzerland)|February 10, 2024
Genome-Wide Association Study (GWAS) for Identifying SNPs and Genes Related to Phosphate-Induced Phenotypic Traits in Tomato (<i>Solanum lycopersicum</i> L.)Haroon Rashid Hakla, Shubham Sharma, Mohammad Urfan, et al.
Scientific Reports|February 10, 2021
Nickel excess affects phenology and reproductive attributes of Asterella wallichiana and Plagiochasma appendiculatum growing in natural habitatsAnil Sharma, Madhu Bhagat, Mohammad Urfan, et al.
Physiology and Molecular Biology of Plants : an International Journal of Functional Plant Biology|August 1, 2022
Recent trends in root phenomics of plant systems with available methods- discrepancies and consonancesMohammad Urfan, Shubham Sharma, Haroon Rashid Hakla, et al.
Research (Washington, D.C.)|October 7, 2024
The Deep Learning-Crop Platform (DL-CRoP): For Species-Level Identification and Nutrient Status of Agricultural CropsMohammad Urfan, Prakriti Rajput, Palak Mahajan, et al.
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