@book{Wagner2019,
  author    = {Wagner, Horst-G{\"u}nter},
  title     = {Bodenerosion in der Agrarlandschaft des Taubertales},
  publisher = {Institut f{\"u}r Geographie und Geologie},
  issn      = {0931-8623},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-192464},
  publisher      = {Universit{\"a}t W{\"u}rzburg},
  pages     = {189},
  year      = {2019},
  abstract  = {Die hier vorgelegte geographisch-historische Abhandlung basiert auf dem Vergleich von zwei im zeitlichen Abstand von ca 60 Jahren (1958/59 = Dissertation und 2016/17 = wiederholendes Gel{\"a}ndeprojekt) erfolgten Untersuchungen zum Verlauf und zum morphologischen Ergebnis von Bodenerosion nach akuten Starkregen sowie infolge schleichend-langfristiger Absp{\"u}lung von Feinboden in verschiedenen Relieftypen des Taubertalgebietes. Alle Vorg{\"a}nge der Bodenabtragung erfuhren erhebliche Differenzierung durch die unterschiedlichen Verfahren der landwirtschaftlichen Nutzung (z.B. Weinbau, Ackerbau,Viehhaltung). In zeitlichem Vergleich der einzelnen Lokalit{\"a}ten und Fallstudien (Kartierung, Fotografie, Datenerfassung)konnte einerseits Abschw{\"a}chung, andererseits Verst{\"a}rkung der Bodenabsp{\"u}lung festgesetllt werden. Um l{\"a}ngerfristig r{\"u}ckblickend die Wirkungsweise der fl{\"a}chen- u. linienhaften Bodenabtragung einzubeziehen, wurden historisch-archivalische Berichte {\"u}ber Folgen von Witterungsereignissen einbezogen und als Auswahl entsprechend der verschiedenen Bodennutzungsarten zusammengestellt. Diese Belege geben Aufschluss {\"u}ber historische Methoden und Techniken zur Verminderung erosionsbedingter Bodenverluste und damit zur Vermeidung existenzmindernder Erntesch{\"a}den. Mit diesem R{\"u}ckblick ergaben sich auch Hinweise auf Phasen historisch-klimatisch ver{\"a}nderter Niederschlagsregime. Im Hinblick auf die durch den Klimawandel zu erwartende Zunahme der Starkregenanteile ergibt sich die Notwendigkeit, den Oberfl{\"a}chenabfluss von Regenmengen und damit deren Erosionskraft durch bodenschonende Nutzungsweisen zu verlangsamen.},
  subject      = {Taubertal},
  language  = {de}
}
@article{AsamGessnerAlmengorGonzalezetal.2022,
  author    = {Asam, Sarah and Gessner, Ursula and Almengor Gonz{\´a}lez, Roger and Wenzl, Martina and Kriese, Jennifer and Kuenzer, Claudia},
  title     = {Mapping crop types of Germany by combining temporal statistical metrics of Sentinel-1 and Sentinel-2 time series with LPIS data},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {13},
  issn      = {2072-4292},
  doi       = {10.3390/rs14132981},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-278969},
  year      = {2022},
  abstract  = {Nationwide and consistent information on agricultural land use forms an important basis for sustainable land management maintaining food security, (agro)biodiversity, and soil fertility, especially as German agriculture has shown high vulnerability to climate change. Sentinel-1 and Sentinel-2 satellite data of the Copernicus program offer time series with temporal, spatial, radiometric, and spectral characteristics that have great potential for mapping and monitoring agricultural crops. This paper presents an approach which synergistically uses these multispectral and Synthetic Aperture Radar (SAR) time series for the classification of 17 crop classes at 10 m spatial resolution for Germany in the year 2018. Input data for the Random Forest (RF) classification are monthly statistics of Sentinel-1 and Sentinel-2 time series. This approach reduces the amount of input data and pre-processing steps while retaining phenological information, which is crucial for crop type discrimination. For training and validation, Land Parcel Identification System (LPIS) data were available covering 15 of the 16 German Federal States. An overall map accuracy of 75.5\% was achieved, with class-specific F1-scores above 80\% for winter wheat, maize, sugar beet, and rapeseed. By combining optical and SAR data, overall accuracies could be increased by 6\% and 9\%, respectively, compared to single sensor approaches. While no increase in overall accuracy could be achieved by stratifying the classification in natural landscape regions, the class-wise accuracies for all but the cereal classes could be improved, on average, by 7\%. In comparison to census data, the crop areas could be approximated well with, on average, only 1\% of deviation in class-specific acreages. Using this streamlined approach, similar accuracies for the most widespread crop types as well as for smaller permanent crop classes were reached as in other Germany-wide crop type studies, indicating its potential for repeated nationwide crop type mapping.},
  language  = {en}
}
@article{RokhafrouzLatifiAbkaretal.2021,
  author    = {Rokhafrouz, Mohammad and Latifi, Hooman and Abkar, Ali A. and Wojciechowski, Tomasz and Czechlowski, Mirosław and Naieni, Ali Sadeghi and Maghsoudi, Yasser and Niedbała, Gniewko},
  title     = {Simplified and hybrid remote sensing-based delineation of management zones for nitrogen variable rate application in wheat},
  series = {Agriculture},
  volume    = {11},
  journal   = {Agriculture},
  number    = {11},
  issn      = {2077-0472},
  doi       = {10.3390/agriculture11111104},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-250033},
  year      = {2021},
  abstract  = {Enhancing digital and precision agriculture is currently inevitable to overcome the economic and environmental challenges of the agriculture in the 21st century. The purpose of this study was to generate and compare management zones (MZ) based on the Sentinel-2 satellite data for variable rate application of mineral nitrogen in wheat production, calculated using different remote sensing (RS)-based models under varied soil, yield and crop data availability. Three models were applied, including (1) a modified "RS- and threshold-based clustering", (2) a "hybrid-based, unsupervised clustering", in which data from different sources were combined for MZ delineation, and (3) a "RS-based, unsupervised clustering". Various data processing methods including machine learning were used in the model development. Statistical tests such as the Paired Sample T-test, Kruskal-Wallis H-test and Wilcoxon signed-rank test were applied to evaluate the final delineated MZ maps. Additionally, a procedure for improving models based on information about phenological phases and the occurrence of agricultural drought was implemented. The results showed that information on agronomy and climate enables improving and optimizing MZ delineation. The integration of prior knowledge on new climate conditions (drought) in image selection was tested for effective use of the models. Lack of this information led to the infeasibility of obtaining optimal results. Models that solely rely on remote sensing information are comparatively less expensive than hybrid models. Additionally, remote sensing-based models enable delineating MZ for fertilizer recommendations that are temporally closer to fertilization times.},
  language  = {en}
}
@article{ReinermannGessnerAsametal.2022,
  author    = {Reinermann, Sophie and Gessner, Ursula and Asam, Sarah and Ullmann, Tobias and Schucknecht, Anne and Kuenzer, Claudia},
  title     = {Detection of grassland mowing events for Germany by combining Sentinel-1 and Sentinel-2 time series},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {7},
  issn      = {2072-4292},
  doi       = {10.3390/rs14071647},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-267164},
  year      = {2022},
  abstract  = {Grasslands cover one-third of the agricultural area in Germany and play an important economic role by providing fodder for livestock. In addition, they fulfill important ecosystem services, such as carbon storage, water purification, and the provision of habitats. These ecosystem services usually depend on the grassland management. In central Europe, grasslands are grazed and/or mown, whereby the management type and intensity vary in space and time. Spatial information on the mowing timing and frequency on larger scales are usually not available but would be required in order to assess the ecosystem services, species composition, and grassland yields. Time series of high-resolution satellite remote sensing data can be used to analyze the temporal and spatial dynamics of grasslands. Within this study, we aim to overcome the drawbacks identified by previous studies, such as optical data availability and the lack of comprehensive reference data, by testing the time series of various Sentinel-2 (S2) and Sentinal-1 (S1) parameters and combinations of them in order to detect mowing events in Germany in 2019. We developed a threshold-based algorithm by using information from a comprehensive reference dataset of heterogeneously managed grassland parcels in Germany, obtained by RGB cameras. The developed approach using the enhanced vegetation index (EVI) derived from S2 led to a successful mowing event detection in Germany (60.3\% of mowing events detected, F1-Score = 0.64). However, events shortly before, during, or shortly after cloud gaps were missed and in regions with lower S2 orbit coverage fewer mowing events were detected. Therefore, S1-based backscatter, InSAR, and PolSAR features were investigated during S2 data gaps. From these, the PolSAR entropy detected mowing events most reliably. For a focus region, we tested an integrated approach by combining S2 and S1 parameters. This approach detected additional mowing events, but also led to many false positive events, resulting in a reduction in the F1-Score (from 0.65 of S2 to 0.61 of S2 + S1 for the focus region). According to our analysis, a majority of grasslands in Germany are only mown zero to two times (around 84\%) and are probably additionally used for grazing. A small proportion is mown more often than four times (3\%). Regions with a generally higher grassland mowing frequency are located in southern, south-eastern, and northern Germany.},
  language  = {en}
}
@article{HalbgewachsWegmanndaPonte2022,
  author    = {Halbgewachs, Magdalena and Wegmann, Martin and da Ponte, Emmanuel},
  title     = {A spectral mixture analysis and landscape metrics based framework for monitoring spatiotemporal forest cover changes: a case study in Mato Grosso, Brazil},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {8},
  issn      = {2072-4292},
  doi       = {10.3390/rs14081907},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-270644},
  year      = {2022},
  abstract  = {An increasing amount of Brazilian rainforest is being lost or degraded for various reasons, both anthropogenic and natural, leading to a loss of biodiversity and further global consequences. Especially in the Brazilian state of Mato Grosso, soy production and large-scale cattle farms led to extensive losses of rainforest in recent years. We used a spectral mixture approach followed by a decision tree classification based on more than 30 years of Landsat data to quantify these losses. Research has shown that current methods for assessing forest degradation are lacking accuracy. Therefore, we generated classifications to determine land cover changes for each year, focusing on both cleared and degraded forest land. The analyses showed a decrease in forest area in Mato Grosso by 28.8\% between 1986 and 2020. In order to measure changed forest structures for the selected period, fragmentation analyses based on diverse landscape metrics were carried out for the municipality of Colniza in Mato Grosso. It was found that forest areas experienced also a high degree of fragmentation over the study period, with an increase of 83.3\% of the number of patches and a decrease of the mean patch area of 86.1\% for the selected time period, resulting in altered habitats for flora and fauna.},
  language  = {en}
}
@article{KleinCoccoUereyenetal.2022,
  author    = {Klein, Igor and Cocco, Arturo and Uereyen, Soner and Mannu, Roberto and Floris, Ignazio and Oppelt, Natascha and Kuenzer, Claudia},
  title     = {Outbreak of Moroccan locust in Sardinia (Italy): a remote sensing perspective},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {23},
  issn      = {2072-4292},
  doi       = {10.3390/rs14236050},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297232},
  year      = {2022},
  abstract  = {The Moroccan locust has been considered one of the most dangerous agricultural pests in the Mediterranean region. The economic importance of its outbreaks diminished during the second half of the 20th century due to a high degree of agricultural industrialization and other human-caused transformations of its habitat. Nevertheless, in Sardinia (Italy) from 2019 on, a growing invasion of this locust species is ongoing, being the worst in over three decades. Locust swarms destroyed crops and pasture lands of approximately 60,000 ha in 2022. Drought, in combination with increasing uncultivated land, contributed to forming the perfect conditions for a Moroccan locust population upsurge. The specific aim of this paper is the quantification of land cover land use (LCLU) influence with regard to the recent locust outbreak in Sardinia using remote sensing data. In particular, the role of untilled, fallow, or abandoned land in the locust population upsurge is the focus of this case study. To address this objective, LCLU was derived from Sentinel-2A/B Multispectral Instrument (MSI) data between 2017 and 2021 using time-series composites and a random forest (RF) classification model. Coordinates of infested locations, altitude, and locust development stages were collected during field observation campaigns between March and July 2022 and used in this study to assess actual and previous land cover situation of these locations. Findings show that 43\% of detected locust locations were found on untilled, fallow, or uncultivated land and another 23\% within a radius of 100 m to such areas. Furthermore, oviposition and breeding sites are mostly found in sparse vegetation (97\%). This study demonstrates that up-to-date remote sensing data and target-oriented analyses can provide valuable information to contribute to early warning systems and decision support and thus to minimize the risk concerning this agricultural pest. This is of particular interest for all agricultural pests that are strictly related to changing human activities within transformed habitats.},
  language  = {en}
}
@article{NwoghaAbtewRaveendranetal.2023,
  author    = {Nwogha, Jeremiah S. and Abtew, Wosene G. and Raveendran, Muthurajan and Oselebe, Happiness O. and Obidiegwu, Jude E. and Chilaka, Cynthia A. and Amirtham, Damodarasamy D.},
  title     = {Role of non-structural sugar metabolism in regulating tuber dormancy in white yam (Dioscorea rotundata)},
  series = {Agriculture},
  volume    = {13},
  journal   = {Agriculture},
  number    = {2},
  issn      = {2077-0472},
  doi       = {10.3390/agriculture13020343},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304486},
  year      = {2023},
  abstract  = {Changes in sugar composition occur continuously in plant tissues at different developmental stages. Tuber dormancy induction, stability, and breaking are very critical developmental transitions in yam crop production. Prolonged tuber dormancy after physiological maturity has constituted a great challenge in yam genetic improvement and productivity. In the present study, biochemical profiling of non-structural sugar in yam tubers during dormancy was performed to determine the role of non-structural sugar in yam tuber dormancy regulation. Two genotypes of the white yam species, one local genotype (Obiaoturugo) and one improved genotype (TDr1100873), were used for this study. Tubers were sampled at 42, 56, 87, 101, 115, and 143 days after physiological maturity (DAPM). Obiaoturugo exhibited a short dormant phenotype and sprouted at 101-DAPM, whereas TDr1100873 exhibited a long dormant phenotype and sprouted at 143-DAPM. Significant metabolic changes were observed in non-structural sugar parameters, dry matter, and moisture content in Obiaoturugo from 56-DAPM, whereas in TDr1100873, significant metabolic changes were observed from 101-DAPM. It was observed that the onset of these metabolic changes occurred at a point when the tubers of both genotypes exhibited a dry matter content of 60\%, indicating that a dry matter content of 60\% might be a critical threshold for white yam tuber sprouting. Non-reducing sugars increased by 9-10-fold during sprouting in both genotypes, which indicates their key role in tuber dormancy regulation in white yam. This result implicates that some key sugar metabolites can be targeted for dormancy manipulation of the yam crop.},
  language  = {en}
}
@article{DhillonDahmsKuebertFlocketal.2023,
  author    = {Dhillon, Maninder Singh and Dahms, Thorsten and K{\"u}bert-Flock, Carina and Liepa, Adomas and Rummler, Thomas and Arnault, Joel and Steffan-Dewenter, Ingolf and Ullmann, Tobias},
  title     = {Impact of STARFM on crop yield predictions: fusing MODIS with Landsat 5, 7, and 8 NDVIs in Bavaria Germany},
  series = {Remote Sensing},
  volume    = {15},
  journal   = {Remote Sensing},
  number    = {6},
  issn      = {2072-4292},
  doi       = {10.3390/rs15061651},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311092},
  year      = {2023},
  abstract  = {Rapid and accurate yield estimates at both field and regional levels remain the goal of sustainable agriculture and food security. Hereby, the identification of consistent and reliable methodologies providing accurate yield predictions is one of the hot topics in agricultural research. This study investigated the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for winter wheat (WW) and oil-seed rape (OSR) using a semi-empirical light use efficiency (LUE) model for the Free State of Bavaria (70,550 km\(^2\)), Germany, from 2001 to 2019. A synthetic normalised difference vegetation index (NDVI) time series was generated and validated by fusing the high spatial resolution (30 m, 16 days) Landsat 5 Thematic Mapper (TM) (2001 to 2012), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2012), and Landsat 8 Operational Land Imager (OLI) (2013 to 2019) with the coarse resolution of MOD13Q1 (250 m, 16 days) from 2001 to 2019. Except for some temporal periods (i.e., 2001, 2002, and 2012), the study obtained an R\(^2\) of more than 0.65 and a RMSE of less than 0.11, which proves that the Landsat 8 OLI fused products are of higher accuracy than the Landsat 5 TM products. Moreover, the accuracies of the NDVI fusion data have been found to correlate with the total number of available Landsat scenes every year (N), with a correlation coefficient (R) of +0.83 (between R\(^2\) of yearly synthetic NDVIs and N) and -0.84 (between RMSEs and N). For crop yield prediction, the synthetic NDVI time series and climate elements (such as minimum temperature, maximum temperature, relative humidity, evaporation, transpiration, and solar radiation) are inputted to the LUE model, resulting in an average R\(^2\) of 0.75 (WW) and 0.73 (OSR), and RMSEs of 4.33 dt/ha and 2.19 dt/ha. The yield prediction results prove the consistency and stability of the LUE model for yield estimation. Using the LUE model, accurate crop yield predictions were obtained for WW (R\(^2\) = 0.88) and OSR (R\(^2\) = 0.74). Lastly, the study observed a high positive correlation of R = 0.81 and R = 0.77 between the yearly R\(^2\) of synthetic accuracy and modelled yield accuracy for WW and OSR, respectively.},
  language  = {en}
}
@article{DhillonKuebertFlockDahmsetal.2023,
  author    = {Dhillon, Maninder Singh and K{\"u}bert-Flock, Carina and Dahms, Thorsten and Rummler, Thomas and Arnault, Joel and Steffan-Dewenter, Ingolf and Ullmann, Tobias},
  title     = {Evaluation of MODIS, Landsat 8 and Sentinel-2 data for accurate crop yield predictions: a case study using STARFM NDVI in Bavaria, Germany},
  series = {Remote Sensing},
  volume    = {15},
  journal   = {Remote Sensing},
  number    = {7},
  issn      = {2072-4292},
  doi       = {10.3390/rs15071830},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311132},
  year      = {2023},
  abstract  = {The increasing availability and variety of global satellite products and the rapid development of new algorithms has provided great potential to generate a new level of data with different spatial, temporal, and spectral resolutions. However, the ability of these synthetic spatiotemporal datasets to accurately map and monitor our planet on a field or regional scale remains underexplored. This study aimed to support future research efforts in estimating crop yields by identifying the optimal spatial (10 m, 30 m, or 250 m) and temporal (8 or 16 days) resolutions on a regional scale. The current study explored and discussed the suitability of four different synthetic (Landsat (L)-MOD13Q1 (30 m, 8 and 16 days) and Sentinel-2 (S)-MOD13Q1 (10 m, 8 and 16 days)) and two real (MOD13Q1 (250 m, 8 and 16 days)) NDVI products combined separately to two widely used crop growth models (CGMs) (World Food Studies (WOFOST), and the semi-empiric Light Use Efficiency approach (LUE)) for winter wheat (WW) and oil seed rape (OSR) yield forecasts in Bavaria (70,550 km\(^2\)) for the year 2019. For WW and OSR, the synthetic products' high spatial and temporal resolution resulted in higher yield accuracies using LUE and WOFOST. The observations of high temporal resolution (8-day) products of both S-MOD13Q1 and L-MOD13Q1 played a significant role in accurately measuring the yield of WW and OSR. For example, L- and S-MOD13Q1 resulted in an R\(^2\) = 0.82 and 0.85, RMSE = 5.46 and 5.01 dt/ha for WW, R\(^2\) = 0.89 and 0.82, and RMSE = 2.23 and 2.11 dt/ha for OSR using the LUE model, respectively. Similarly, for the 8- and 16-day products, the simple LUE model (R\(^2\) = 0.77 and relative RMSE (RRMSE) = 8.17\%) required fewer input parameters to simulate crop yield and was highly accurate, reliable, and more precise than the complex WOFOST model (R\(^2\) = 0.66 and RRMSE = 11.35\%) with higher input parameters. Conclusively, both S-MOD13Q1 and L-MOD13Q1, in combination with LUE, were more prominent for predicting crop yields on a regional scale than the 16-day products; however, L-MOD13Q1 was advantageous for generating and exploring the long-term yield time series due to the availability of Landsat data since 1982, with a maximum resolution of 30 m. In addition, this study recommended the further use of its findings for implementing and validating the long-term crop yield time series in different regions of the world.},
  language  = {en}
}
@article{MoustafaFouadIbrahimetal.2023,
  author    = {Moustafa, Moataz A. M. and Fouad, Eman A. and Ibrahim, Emad and Erdei, Anna Laura and K{\´a}rp{\´a}ti, Zsolt and F{\´o}nagy, Adrien},
  title     = {The comparative toxicity, biochemical and physiological impacts of chlorantraniliprole and indoxacarb on Mamestra brassicae (Lepidoptera: Noctuidae)},
  series = {Toxics},
  volume    = {11},
  journal   = {Toxics},
  number    = {3},
  issn      = {2305-6304},
  doi       = {10.3390/toxics11030212},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-303931},
  year      = {2023},
  abstract  = {Background: The cabbage moth, Mamestra brassicae, is a polyphagous pest that attacks several crops. Here, the sublethal and lethal effects of chlorantraniliprole and indoxacarb were investigated on the developmental stages, detoxification enzymes, reproductive activity, calling behavior, peripheral physiology, and pheromone titer of M. brasssicae. Methods: To assess pesticide effects, the second instar larvae were maintained for 24 h on a semi-artificial diet containing insecticides at their LC\(_{10}\), LC\(_{30}\), and LC\(_{50}\) concentrations. Results: M. brassicae was more susceptible to chlorantraniliprole (LC\(_{50}\) = 0.35 mg/L) than indoxacarb (LC\(_{50}\) = 1.71 mg/L). A significantly increased developmental time was observed with both insecticides at all tested concentrations but decreases in pupation rate, pupal weight, and emergence were limited to the LC50 concentration. Reductions in both the total number of eggs laid per female and the egg viability were observed with both insecticides at their LC\(_{30}\) and LC\(_{50}\) concentrations. Both female calling activity and the sex pheromone (Z11-hexadecenyl acetate and hexadecenyl acetate) titer were significantly reduced by chlorantraniliprole in LC\(_{50}\) concentration. Antennal responses of female antennae to benzaldehyde and 3-octanone were significantly weaker than controls after exposure to the indoxocarb LC\(_{50}\) concentration. Significant reductions in the enzymatic activity of glutathione S-transferases, mixed-function oxidases, and carboxylesterases were observed in response to both insecticides.},
  language  = {en}
}
@article{ConradKehlMuelleretal.2023,
  author    = {Conrad, David and Kehl, Alexandra and M{\"u}ller, Tobias and Klopfleisch, Robert and Aupperle-Lellbach, Heike},
  title     = {Immunohistochemical and molecular genetic analysis of canine digital mast cell tumours},
  series = {Animals},
  volume    = {13},
  journal   = {Animals},
  number    = {10},
  issn      = {2076-2615},
  doi       = {10.3390/ani13101694},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-319199},
  year      = {2023},
  abstract  = {Grading, immunohistochemistry and c-kit mutation status are criteria for assessing the prognosis and therapeutic options of canine cutaneous mast cell tumours (MCTs). As a subset, canine digital MCTs have rarely been explored in this context. Therefore, in this retrospective study, 68 paraffin-embedded canine digital MCTs were analysed, and histological grading was assessed according to Patnaik and Kiupel. The immunohistochemical markers KIT and Ki67 were used, as well as polymerase chain reaction (PCR) for mutational screening in c-kit exons 8, 9, 11 and 14. Patnaik grading resulted in 22.1\% grade I, 67.6\% grade II and 10.3\% grade III tumours. Some 86.8\% of the digital MCTs were Kiupel low-grade. Aberrant KIT staining patterns II and III were found in 58.8\%, and a count of more than 23 Ki67-positive cells in 52.3\% of the cases. Both parameters were significantly associated with an internal tandem duplication (ITD) in c-kit exon 11 (12.7\%). French Bulldogs, which tend to form well-differentiated cutaneous MCTs, had a higher proportion of digital high-grade MCTs and ITD in c-kit exon 11 compared with mongrels. Due to its retrospective nature, this study did not allow for an analysis of survival data. Nevertheless, it may contribute to the targeted characterisation of digital MCTs.},
  language  = {en}
}