Soil fungi establish mutualistic interactions with the roots of most vascular land plants.Arbuscular mycorrhizal (AM) fungi are among the most extensively characterised mycobionts to date. Current approaches to quantifying the extent of root colonisation and the abundance of hyphal structures in mutant roots rely on staining and human scoring involving simple, yet repetitive tasks prone to variations between experimenters. We developed AMFinder which allows for automatic computer vision-based identification and quantification of AM fungal colonisation and intraradical hyphal structures on inkstained root images using convolutional neural networks. AMFinder delivered high-confidence predictions on image datasets of roots of multiple plant hosts (Nicotiana benthamiana, Medicago truncatula, Lotus japonicus, Oryza sativa) and captured the altered colonisation in ram1-1, str, and smax1 mutants. A streamlined protocol for sample preparation and imaging allowed us to quantify mycobionts from the genera Rhizophagus, Claroideoglomus, Rhizoglomus and Funneliformis via flatbed scanning or digital microscopy including dynamic increases in colonisation in whole root systems over time. AMFinder adapts to a wide array of experimental conditions. It enables accurate, reproducible analyses of plant root systems and will support better documentation of AM fungal colonisation analyses. AMFinder can be accessed on https://github.com/SchornacklabSLCU/amfinder.
In Australia, temperatures below 11°C (called cold shocks) were believed to retard cotton (Gossypium hirsutum L.) growth, development and yield. Recent studies, however, have suggested that temperatures lower than this did not impede cotton development beyond normal developmental responses to cool temperatures. This paper aims to test the hypothesis that cold exposure to 10°C for 10 and 20 nights does not reduce tissue viability in vegetative and early flowering cotton plants. Cold temperatures at 10°C for 10 and 20 consecutive nights were imposed on cotton plants, grown in both controlled temperature glasshouses and outdoors, at the vegetative seedling and early flowering stages. Extreme temperature tests at 2, 5 and 7°C for two nights were also imposed to generate tissue damage for comparison. 2,3,5-Triphenyl tetrazolium chloride (TTC) tissue viability (testing for mitochondrial activity), relative electrical conductivity (REC, testing for membrane integrity), leaf chlorophyll fluorescence, leaf photosynthesis, plant dry weight and yield were measured. Only exposure at 2°C for two nights showed negative effects in the TTC and REC tests, and leaves of these plants died soon after exposure. There were no consistent negative effects in the TTC and REC tests for all treatments at 10°C for 10 and 20 nights compared with the respective controls, suggesting that there was no structural or functional damage to leaves. In support of these findings, leaf photosynthesis and both light- and dark-adapted chlorophyll fluorescence for the 20 nights at 10°C treatment were occasionally below the controls but recovered quickly, suggesting that only temporary dynamic photoinhibition occurred. Cotton plant development was delayed following 10 and 20 nights at 10°C owing to reduced degree day accumulation. These data support previous work that cold temperatures at 10°C for up to 20 nights would be unlikely to result in yield reduction as a consequence of plant damage, and also that crop development can be estimated with degree days without an adjustment for cold shock. The use of TTC and REC has potential for novel detection of tissue damage for cotton at extreme temperatures.
Soil fungi establish mutualistic interactions with the roots of most vascular land plants. Arbuscular mycorrhizal (AM) fungi are among the most extensively characterised mycobionts to date. Current approaches to quantifying the extent of root colonisation and the relative abundance of intraradical hyphal structures in mutant roots rely on staining and human scoring involving simple, yet repetitive tasks prone to variations between experimenters. We developed the software AMFinder which allows for automatic computer vision-based identification and quantification of AM fungal colonisation and intraradical hyphal structures on ink-stained root images using convolutional neural networks. AMFinder delivered high-confidence predictions on image datasets of colonised roots of Medicago truncatula, Lotus japonicus, Oryza sativa and Nicotiana benthamiana obtained via flatbed scanning or digital microscopy enabling reproducible and transparent data analysis. A streamlined protocol for sample preparation and imaging allowed us to quantify dynamic increases in colonisation in whole root systems over time. AMFinder adapts to a wide array of experimental conditions. It enables accurate, reproducible analyses of plant root systems and will support better documentation of AM fungal colonisation analyses. AMFinder can be accessed here: https://github.com/SchornacklabSLCU/amfinder.git
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