About

Alexander Bucksch is a Principal Investigator at the Computational Plant Science lab. His research focuses on understanding how plant roots work together to optimize the survival of plant populations, especially under increasingly adverse environmental conditions. His team develops and utilizes innovative phenotyping methods, often self-developed, to analyze shape variations in roots across biological scales and explore how these variations relate to mechanisms that build resilience and survival in plants. Their work has impactful applications in agriculture, helping to enhance crop yields on a field-wide scale, and supports researchers in plant breeding and development, paving the way for more productive agricultural systems.

Research topics

• Biology
• Artificial Intelligence
• Environmental science
• Computer Science
• Botany
• Agronomy
• Ecology
• Algorithm
• Horticulture
• Geography
• Geology
• Chemistry
• Remote sensing
• Biochemistry

Selected publications

• Root angle in maize influences nitrogen capture and is regulated by calcineurin B‐like protein <scp>(CBL)</scp>‐interacting serine/threonine‐protein kinase 15 (<scp><i>ZmCIPK15</i></scp>)

  Plant Cell & Environment · 2021 · 89 citations

  • Biology
  • Horticulture
  • Botany

  Crops with reduced nutrient and water requirements are urgently needed in global agriculture. Root growth angle plays an important role in nutrient and water acquisition. A maize diversity panel of 481 genotypes was screened for variation in root angle employing a high-throughput field phenotyping platform. Genome-wide association mapping identified several single nucleotide polymorphisms (SNPs) associated with root angle, including one located in the root expressed CBL-interacting serine/threonine-protein kinase 15 (ZmCIPK15) gene (LOC100285495). Reverse genetic studies validated the functional importance of ZmCIPK15, causing a approximately 10° change in root angle in specific nodal positions. A steeper root growth angle improved nitrogen capture in silico and in the field. OpenSimRoot simulations predicted at 40 days of growth that this change in angle would improve nitrogen uptake by 11% and plant biomass by 4% in low nitrogen conditions. In field studies under suboptimal N availability, the cipk15 mutant with steeper growth angles had 18% greater shoot biomass and 29% greater shoot nitrogen accumulation compared to the wild type after 70 days of growth. We propose that a steeper root growth angle modulated by ZmCIPK15 will facilitate efforts to develop new crop varieties with optimal root architecture for improved performance under edaphic stress.

  DOI

• DIRT/3D: 3D root phenotyping for field-grown maize ( <i>Zea mays</i> )

  PLANT PHYSIOLOGY · 2021 · 81 citations

  Senior authorCorresponding
  • Agronomy
  • Biology
  • Environmental science

  The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r2>0.84 and a high broad-sense heritability of Hmean2> 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

  DOI

• Canopy Roughness: A New Phenotypic Trait to Estimate Aboveground Biomass from Unmanned Aerial System

  Plant Phenomics · 2020 · 29 citations

  • Computer Science
  • Artificial Intelligence
  • Remote sensing

  ) greater than 0.5 in all trials. Moreover, we found that canopy roughness has the ability to discern AGB variations among different genotypes. Our test trials demonstrate the potential of canopy roughness as a reliable trait for high-throughput phenotyping to estimate AGB. As such, canopy roughness provides practical information to breeders in order to select phenotypes on the basis of UAS data.

  DOI

Recent grants

• CAREER: The phenotypic spectrum: Quantifying new patterns of architecture variation in crop roots

  NSF · $971k · 2019–2023

Frequent coauthors

• Suxing Liu

  University of Arizona

  21 shared

• Peter Pietrzyk

  University of Georgia

  19 shared

• Joshua S. Weitz

  University of Maryland, College Park

  17 shared

• Jonathan P. Lynch

  Pennsylvania State University

  16 shared

• Patompong Saengwilai

  Mahidol University

  13 shared

• Ankita Roy

  University of Georgia

  11 shared

• James Burridge

  11 shared

• Roderik Lindenbergh

  10 shared

Labs

• Computational Plant SciencePI

Education

• Dr.

  Technische Universiteit Delft

  2011

• M.sc. and B.sc.

  Brandenburgische Technische Universitat Cottbus

  2006

Similar researchers at University of Arizona

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• Jeremy Garciah-129
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• Katia Cunhah-115
• Lisa M Rimszah-99