Lydia Kienbaum

ORCID: 0000-0003-0218-693X
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About
Contact & Profiles
Research Areas
  • Advances in Cucurbitaceae Research
  • Plant and animal studies
  • Smart Agriculture and AI
  • Plant Parasitism and Resistance
  • Genetic Mapping and Diversity in Plants and Animals
  • Powdery Mildew Fungal Diseases
  • Insect and Pesticide Research
  • Identification and Quantification in Food
  • Cynara cardunculus studies
  • Seed and Plant Biochemistry
  • Cocoa and Sweet Potato Agronomy
  • Spectroscopy and Chemometric Analyses

University of Hohenheim
2020-2025

Abstract Urban landscapes are often characterized by a wide range of diverse flowering plants consisting native and exotic plants. These flower-rich habitats have proven to be particularly valuable for urban pollinating insects. However, the ability ornamental in supporting pollinator communities is still not well documented. For this study, we established flower beds at 13 different testing sites, which were planted with identical sets garden The visitation patterns then observed throughout...

10.1007/s11252-020-01085-0 article EN cc-by Urban Ecosystems 2020-12-26

ABSTRACT Quinoa is a grain crop with excellent nutritional properties that has attracted global attention for its potential contribution to future food security in changing climate. Despite long history of cultivation, quinoa been improved little by modern breeding and niche outside native cultivation area. Grain yield strongly affected panicle traits, whose phenotypic analysis time consuming prone error because their complex architecture, automated image an efficient alternative. We...

10.1111/pbr.13266 article EN cc-by Plant Breeding 2025-02-12

Abstract Background Maize cobs are an important component of crop yield that exhibit a high diversity in size, shape and color native landraces modern varieties. Various phenotyping approaches were developed to measure maize cob parameters throughput fashion. More recently, deep learning methods like convolutional neural networks (CNNs) became available shown be highly useful for high-throughput plant phenotyping. We aimed at comparing classical image segmentation with using large dataset...

10.1186/s13007-021-00787-6 article EN cc-by Plant Methods 2021-08-21

Powdery mildew caused by Podosphaera xanthii is among the most threatening fungal diseases affecting melons on Mediterranean coast. Although use of genetic resistance a highly recommended alternative to control this pathogen, many races fungus have been described and, therefore, usually overcome; thus, breeding for pathogen challenge. Several melon genotypes carrying powdery but their agronomical and fruit characters are far away from required types in commercial markets. Taking into...

10.3390/horticulturae8121172 article EN cc-by Horticulturae 2022-12-09

Abstract Ornamental plants are appreciated by humans for their colorfulness, beauty, abundant flowering and long blooming periods. Many ornamental can also constitute an additional foraging resource flower-visiting insects. However, the ability of popular plant Calibrachoa to support urban insect communities is not well documented. In this study, 20 different cultivars were selected tested in regard friendliness based on standardized observations (I) flight tents using large earth bumble bee...

10.1007/s11829-021-09844-2 article EN cc-by Arthropod-Plant Interactions 2021-06-29

A half-diallel cross study of seven melon inbred lines was carried out. The parents and their 21 F1 hybrids were evaluated for precocity maturity, average weight per fruit, fruit quality (fruit size, rind thickness, soluble solids). Diallel analysis investigated breeding values these genotypes via general specific combining ability, relationships between heterosis the traits. variance traits indicated highly significant differences among genotypes, suggesting presence adequate genetic...

10.3390/horticulturae10070724 article EN cc-by Horticulturae 2024-07-09

Abstract Background Maize cobs are an important component of crop yield that exhibit a high diversity in size, shape and color native landraces modern varieties. Various phenotyping approaches were developed to measure maize cob parameters throughput fashion. More recently, deep learning methods like convolutional neural networks (CNN) became available shown be highly useful for high-throughput plant phenotyping. We aimed at comparing classical image segmentation with using large dataset...

10.1101/2021.03.16.435660 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2021-03-17
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