Browsing by Author "Zhang, Xuemei"

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    Brewer’s Spent Grain with Yeast Amendment Shows Potential for Anaerobic Soil Disinfestation of Weeds and Pythium irregulare
    Liu, Danyang; Samtani, Jayesh; Johnson, Charles; Zhang, Xuemei; Butler, David M.; Derr, Jeffrey (MDPI, 2023-08-08)
    Anaerobic soil disinfestation (ASD) is a promising alternative to chemical fumigation for controlling soilborne plant pathogens and weeds. This study investigated the impact of brewer’s spent grain (BSG), a locally available carbon source, on various weed species and the oomycete pathogen Pythium irregulare in ASD. Two greenhouse studies were conducted using BSG and yeast at full and reduced rates in a completely randomized design with four replicates and two runs per study. In both studies, ASD treatments significantly decreased the seed viability of all weed species and the Pythium irregulare inoculum, while promoting higher cumulative anaerobicity compared to the non-treated control. The addition of yeast had a notable effect when combined with BSG but not with rice bran. When used in reduced carbon rates, yeast supplementation enhanced the efficacy of BSG, providing comparable control to the full rate for most weed species, including redroot pigweed, white clover, and yellow nutsedge. Interestingly, no ASD treatment affected the soil temperature. Furthermore, BSG treatments caused higher concentrations of volatile fatty acids compared to ASD with rice bran and the non-treated control. This finding suggests that the inclusion of yeast in ASD shows potential for reducing the carbon input required for effective soil disinfestation.
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    Ecology and Management of Pythium species in Float Greenhouse Tobacco Transplant Production
    Zhang, Xuemei (Virginia Tech, 2021-01-07)
    Pythium diseases are common in the greenhouse production of tobacco transplants and can cause up to 70% seedling loss in hydroponic (float-bed) greenhouses. However, the symptoms and consequences of Pythium diseases are often variable among these greenhouses. A tobacco transplant greenhouse survey was conducted in 2017 in order to investigate the sources of this variability, especially the composition and distribution of Pythium communities within greenhouses. The survey revealed twelve Pythium species. Approximately 80% of the surveyed greenhouses harbored Pythium in at least one of four sites within the greenhouse, including the center walkway, weeds, but especially bay water and tobacco seedlings. Pythium dissotocum, followed by P. myriotylum, were the most common species. Pythium myriotylum, P. coloratum, and P. dissotocum were aggressive pathogens that suppressed seed germination and caused root rot, stunting, foliar chlorosis, and death of tobacco seedlings. Pythium aristosporum, P. porphyrae, P. torulosum, P. inflatum, P. irregulare, P. catenulatum, and a different isolate of P. dissotocum, were weak pathogens, causing root symptoms without affecting the upper part of tobacco seedlings. Pythium adhaerens, P. attrantheridium, and P. pectinolyticum did not affect tobacco seeds or seedlings. The consequences of Pythium infection were more likely to be severe when they occurred during seed germination than at seedling emergence, or after plant stem elongation when seedling roots had started to grow into underlying nutrient solutions, depending on the species of Pythium. High and low variation was observed among isolates of P. dissotocum and P. myriotylum, respectively. Pythium myriotylum co-existed with multiple other Pythium or oomycete species in the same environments within tobacco greenhouses, and significant in vitro and/or in vivo interactions between P. myriotylum and some naturally co-existing species were revealed. Pythium porphyrae may have the potential to protect tobacco seeds and seedlings from P. myriotylum infection. Greenhouse Pythium control trials identified ethaboxam, mefenoxam, and copper ionization as potentially promising alternatives to etridiazole for Pythium disease management in tobacco transplant production. The outcomes of this project provide useful new information to better understand the composition, distribution, and diversity of Pythium communities in tobacco transplant greenhouses and to improve Pythium disease management for tobacco transplant production.
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    Machine Learning Analysis of Hyperspectral Images of Damaged Wheat Kernels
    Dhakal, Kshitiz; Sivaramakrishnan, Upasana; Zhang, Xuemei; Belay, Kassaye; Oakes, Joseph; Wei, Xing; Li, Song (MDPI, 2023-03-28)
    Fusarium head blight (FHB) is a disease of small grains caused by the fungus Fusarium graminearum. In this study, we explored the use of hyperspectral imaging (HSI) to evaluate the damage caused by FHB in wheat kernels. We evaluated the use of HSI for disease classification and correlated the damage with the mycotoxin deoxynivalenol (DON) content. Computational analyses were carried out to determine which machine learning methods had the best accuracy to classify different levels of damage in wheat kernel samples. The classes of samples were based on the DON content obtained from Gas Chromatography–Mass Spectrometry (GC-MS). We found that G-Boost, an ensemble method, showed the best performance with 97% accuracy in classifying wheat kernels into different severity levels. Mask R-CNN, an instance segmentation method, was used to segment the wheat kernels from HSI data. The regions of interest (ROIs) obtained from Mask R-CNN achieved a high mAP of 0.97. The results from Mask R-CNN, when combined with the classification method, were able to correlate HSI data with the DON concentration in small grains with an R2 of 0.75. Our results show the potential of HSI to quantify DON in wheat kernels in commercial settings such as elevators or mills.