Browsing by Person "Kienbaum, Lydia"

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Combining ability and hybrid breeding in Tunisian melon (Cucumis melo L.) for fruit traits
(2024) Chikh-Rouhou, Hela; Kienbaum, Lydia; Gharib, Amani H. A. M.; Fayos, Oreto; Garcés-Claver, Ana; Wang, Huasen; Miao, Li
A half-diallel cross study of seven melon inbred lines was carried out. The seven parents and their 21 F1 hybrids were evaluated for precocity of maturity, average weight per fruit, and fruit quality (fruit size, rind thickness, and soluble solids). The Diallel analysis was investigated for breeding values of these melon genotypes via general and specific combining ability, relationships between general and specific combining ability, and heterosis for the evaluated traits. The analysis of variance of the traits evaluated indicated highly significant differences among genotypes, suggesting the presence of adequate genetic variation for breeding. Additive genetic effects were most important with respect to fruit weight, while genetic dominance and epistasis effects mainly controlled fruit quality traits (fruit size, rind thickness, and TSS). Parent 1 (P1) and parent 3 (P3) had significant positive general combining ability effects for fruit weight. Also, P3 had positive general combining ability effects for fruit length and diameter, and cavity diameter. P3 was found to show maximum significant GCA in the desirable direction for all the traits except for TSS. Evaluation of heterosis (%) revealed that hybrid P1 × P3 can be considered as the best-performing hybrid for average fruit weight, TSS, and precocity, which also exhibited the highest positive and significant SCA effect for these traits. These results suggested that, among the melon genotypes studied, there is the potential to generate superior new varieties in hybrid production.
Comparison of floral traits in Calibrachoa cultivars and assessment of their impacts on attractiveness to flower-visiting insects
(2021) Marquardt, Melanie; Kienbaum, Lydia; Losert, Dominik; Kretschmer, Lea Annina; Rigling, Marina; Zhang, Yanyan; Schweikert, Karsten; Westermann, Nils; Ruttensperger, Ute; Rosenkranz, Peter
Ornamental plants are appreciated by humans for their colorfulness, beauty, abundant flowering and long blooming periods. Many ornamental plants can also constitute an additional foraging resource for flower-visiting insects. However, the ability of the popular ornamental plant Calibrachoa to support urban insect communities is not well documented. In this study, 20 different Calibrachoa cultivars were selected and tested in regard to their insect friendliness based on standardized observations (I) in flight tents using the large earth bumble bee Bombus terrestris as a model species and (II) in open field trials. To investigate what floral characteristics might constitute attractiveness to bumble bees, various floral traits were recorded and compared across all tested Calibrachoa cultivars. Over a two-year period, a total of 6,327 foraging bumble bees were recorded in the tent observations. In the open field observations, we counted 4,188 flower-visiting insects. Our results revealed that (I) all Calibrachoa cultivars were visited by insects for foraging, (II) the number of insect visitors varied significantly among the 20 tested cultivars and (III) the cultivars displayed different floral traits. For the morphometric floral traits and the aroma profiles of Calibrachoa, only the mean nectar quantity and a few identified compounds could be correlated with attractiveness to the model species B. terrestris. We also found that the petal color of the tested cultivars had a significant impact on the number of visitors. Therefore, B. terrestris clearly preferred red or blue Calibrachoa cultivars over those with other petal colors. However, as the cultivar preferences in the different insect groups differed, it is highly recommended to use various cultivars in urban plantings. Nevertheless, efforts must be made to explain what additional floral traits make Calibrachoa and other ornamental plants generally attractive to flower visitors. This information can then be used for breeding purposes to increase the insect friendliness of ornamental plants.
DeepCob: precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics
(2021) Kienbaum, Lydia; Correa Abondano, Miguel; Blas, Raul; Schmid, Karl
Background: Maize cobs are an important component of crop yield that exhibit a high diversity in size, shape and color in native landraces and modern varieties. Various phenotyping approaches were developed to measure maize cob parameters in a high throughput fashion. More recently, deep learning methods like convolutional neural networks (CNNs) became available and were shown to be highly useful for high-throughput plant phenotyping. We aimed at comparing classical image segmentation with deep learning methods for maize cob image segmentation and phenotyping using a large image dataset of native maize landrace diversity from Peru. Results: Comparison of three image analysis methods showed that a Mask R-CNN trained on a diverse set of maize cob images was highly superior to classical image analysis using the Felzenszwalb-Huttenlocher algorithm and a Window-based CNN due to its robustness to image quality and object segmentation accuracy (r = 0.99). We integrated Mask R-CNN into a high-throughput pipeline to segment both maize cobs and rulers in images and perform an automated quantitative analysis of eight phenotypic traits, including diameter, length, ellipticity, asymmetry, aspect ratio and average values of red, green and blue color channels for cob color. Statistical analysis identified key training parameters for efficient iterative model updating. We also show that a small number of 10–20 images is sufficient to update the initial Mask R-CNN model to process new types of cob images. To demonstrate an application of the pipeline we analyzed phenotypic variation in 19,867 maize cobs extracted from 3449 images of 2484 accessions from the maize genebank of Peru to identify phenotypically homogeneous and heterogeneous genebank accessions using multivariate clustering. Conclusions: Single Mask R-CNN model and associated analysis pipeline are widely applicable tools for maize cob phenotyping in contexts like genebank phenomics or plant breeding.
Evaluation of the importance of ornamental plants for pollinators in urban and suburban areas in Stuttgart, Germany
(2021) Marquardt, Melanie; Kienbaum, Lydia; Kretschmer, Lea Annina; Penell, Anja; Schweikert, Karsten; Ruttensperger, Ute; Rosenkranz, Peter
Urban landscapes are often characterized by a wide range of diverse flowering plants consisting of native and exotic plants. These flower-rich habitats have proven to be particularly valuable for urban pollinating insects. However, the ability of ornamental plants in supporting urban pollinator communities is still not well documented. For this study, we established flower beds at 13 different urban testing sites, which were planted with identical sets of ornamental garden plants. The pollinator visitation patterns were then observed throughout the summer seasons. Over a two-year period, a total of 10,565 pollinators were recorded with wild bees (> 50%, excluding bumblebees) being the most abundant pollinator group. Our results revealed that (I) the assortment of ornamental plants was visited by a high number of urban pollinators for collecting pollen and nectar, and (II) the pollinator abundance and composition varied significantly within the tested ornamental plants. These differences occurred not only among plant species but to the same extent among cultivars, whereby the number of pollinators was positively correlated with number of flowering units per plant. By using a generalized linear mixed model (GLMM) and redundancy analysis (RDA) we identified further significant impacts of the two variables year and location on the insect pollinator abundance and richness. Despite of the local and yearly variations, our approach provided a good and field-applicable method to evaluate the pollinator friendliness in ornamental plants. Such tools are urgently required to validate labels like ‘bee friendly’ or ‘pollinator friendly’ used by plant breeding companies.