@article{sennik_kinoshita-millard_oh_kafer_dean_oralkan_2023, title={Plant Disease Detection Using an Electronic Nose}, ISSN={["1930-0395"]}, DOI={10.1109/SENSORS56945.2023.10325015}, abstractNote={This paper presents experimental results on differentiating between healthy wheat plants and plants infected with Fusarium Head Blight (FHB) based on sensing the ambient gases in the plant environment using a gravimetric electronic nose enabled by a functionalized capacitive micromachined ultrasonic transducer (CMUT) array and machine learning (ML) algorithms. The CMUT sensor array is functionalized with organic/inorganic materials to capture disease-related volatile signals. The sensor data is processed and analyzed using ML algorithms for accurate plant classification. Experimental results demonstrate the effectiveness of the proposed approach in achieving high accuracy for plant disease detection at the end of the 11th day after plant inoculation.}, journal={2023 IEEE SENSORS}, author={Sennik, Erdem and Kinoshita-Millard, Samuel and Oh, Yeonyee and Kafer, Christopher W. and Dean, Ralph A. and Oralkan, Omer}, year={2023} }
 @article{oh_ingram_shekasteband_adhikari_louws_dean_2023, title={Tissues and mechanisms associated with Verticillium wilt resistance in tomato using bi-grafted near-isogenic lines}, volume={5}, ISSN={["1460-2431"]}, url={https://doi.org/10.1093/jxb/erad182}, DOI={10.1093/jxb/erad182}, abstractNote={Abstract}, number={15}, journal={JOURNAL OF EXPERIMENTAL BOTANY}, author={Oh, Yeonyee and Ingram, Thomas and Shekasteband, Reza and Adhikari, Tika and Louws, Frank J. and Dean, Ralph A.}, editor={Höfte, MonicaEditor}, year={2023}, month={May} }
 @article{sennik_erden_constantino_oh_dean_oralkan_2021, title={Electronic nose system based on a functionalized capacitive micromachined ultrasonic transducer (CMUT) array for selective detection of plant volatiles}, volume={341}, ISSN={["0925-4005"]}, url={https://doi.org/10.1016/j.snb.2021.130001}, DOI={10.1016/j.snb.2021.130001}, abstractNote={Here, a small, low-power, wireless gas sensor platform for selective detection of volatile organic compounds (VOCs) released from plants under different abiotic or biotic stress conditions is described. This sensor platform is implemented based on a capacitive micromachined ultrasonic transducer (CMUT) array, in which elements were functionalized with a variety of materials including polymers, phthalocyanines, and metals to improve selectivity. Input impedance measurements of the functionalized CMUT array were compared to pre-coating measurements to analyze the mechanical loading. The CMUT arrays were then exposed to VOCs known to be emitted by plants with different concentrations under dry air flow at room temperature. The results demonstrated that 1-Octanol created the strongest response across different channels and a resolution of 3-ppb was calculated for the CMUT element functionalized using silver ink when exposed to 1-Octanol. The relative responses of different channels to tested volatiles were observed to be different. The k-nearest neighbor (k-NN) algorithm was used for the gas classification by dividing the data to training and test groups. The k-NN results showed that the gases at low concentrations were successfully classified with better than 97 % accuracy. Finally, to emulate the ambient atmosphere for plants, the gas tests were repeated by adding different levels of humidity to the gas flow. With a minimum 98 % accuracy, the k-NN classifier demonstrated that the functionalized CMUT array can be used for selective detection of the group of plant VOCs used in this study, even at different relative humidity levels in the ambient atmosphere.}, journal={SENSORS AND ACTUATORS B-CHEMICAL}, publisher={Elsevier BV}, author={Sennik, Erdem and Erden, Fatih and Constantino, Nasie and Oh, YeonYee and Dean, Ralph A. and Oralkan, Omer}, year={2021}, month={Aug} }
 @article{constantino_oh_sennik_andersen_warden_oralkan_dean_2021, title={Soybean Cyst Nematodes Influence Aboveground Plant Volatile Signals Prior to Symptom Development}, volume={12}, ISSN={["1664-462X"]}, DOI={10.3389/fpls.2021.749014}, abstractNote={Soybean cyst nematode (SCN), Heterodera glycines, is one of the most destructive soybean pests worldwide. Unlike many diseases, SCN doesn't show above ground evidence of disease until several weeks after infestation. Knowledge of Volatile Organic Compounds (VOCs) related to pests and pathogens of foliar tissue is extensive, however, information related to above ground VOCs in response to root damage is lacking. In temporal studies, gas chromatography-mass spectrometry analysis of VOCs from the foliar tissues of SCN infested plants yielded 107 VOCs, referred to as Common Plant Volatiles (CPVs), 33 with confirmed identities. Plants showed no significant stunting until 10 days after infestation. Total CPVs increased over time and were significantly higher from SCN infested plants compared to mock infested plants post 7 days after infestation (DAI). Hierarchical clustering analysis of expression ratios (SCN: Mock) across all time points revealed 5 groups, with the largest group containing VOCs elevated in response to SCN infestation. Linear projection of Principal Component Analysis clearly separated SCN infested from mock infested plants at time points 5, 7, 10 and 14 DAI. Elevated Styrene (CPV11), D-Limonene (CPV32), Tetradecane (CPV65), 2,6-Di-T-butyl-4-methylene-2,5-cyclohexadiene-1-one (CPV74), Butylated Hydroxytoluene (CPV76) and suppressed Ethylhexyl benzoate (CPV87) levels, were associated with SCN infestation prior to stunting. Our findings demonstrate that SCN infestation elevates the release of certain VOCs from foliage and that some are evident prior to symptom development. VOCs associated with SCN infestations prior to symptom development may be valuable for innovative diagnostic approaches.}, journal={FRONTIERS IN PLANT SCIENCE}, author={Constantino, Nasie and Oh, Yeonyee and Sennik, Erdem and Andersen, Brian and Warden, Michael and Oralkan, Omer and Dean, Ralph A.}, year={2021}, month={Sep} }
 @article{ingram_oh_adhikari_louws_dean_2020, title={Comparative Genome Analyses of 18 Verticillium dahliae Tomato Isolates Reveals Phylogenetic and Race Specific Signatures}, volume={11}, ISSN={["1664-302X"]}, DOI={10.3389/fmicb.2020.573755}, abstractNote={Host resistance is one of the few strategies available to combat the soil borne pathogenic fungus Verticillium dahliae. Understanding pathogen diversity in populations is key to successfully deploying host resistance. In this study the genomes of 18 V. dahliae isolates of races 1 (n = 2), 2 (n = 4), and 3 (n = 12) from Japan, California, and North Carolina were sequenced and mapped to the reference genome of JR2 (from tomato). The genomes were analyzed for phylogenetic and pathogen specific signatures to classify specific strains or genes for future research. Four highly clonal lineages/groups were discovered, including a lineage unique to North Carolina isolates, which had the rare MAT1-1 mating type. No evidence for recombination between isolates of different mating types was observed, even in isolates of different mating types discovered in the same field. By mapping these 18 isolates genomes to the JR2 reference genome, 193 unique candidate effectors were found using SignalP and EffectorP. Within these effectors, 144 highly conserved effectors, 42 mutable effectors (truncated or present in some isolates but absent in others), and 7 effectors present in highly variable regions of the chromosomes were discovered. Of the 144 core effectors, 21 were highly conserved in V. alfalfae and V. longisporum, 7 of which have no known function. Within the non-core effectors 30 contained large numbers of non-synonymous mutations, while 15 of them contained indels, frameshift mutations, or were present on highly variable regions of the chromosome. Two of these highly variable region effectors (HVREs) were only present in race 2 isolates, but not in race 3 isolates. The race 1 effector Ave1 was also present in a highly variable region. These data may suggest that these highly variable regions are enriched in race determinant genes, consistent with the two-speed genome hypothesis.}, journal={FRONTIERS IN MICROBIOLOGY}, author={Ingram, Thomas W. and Oh, Yeonyee and Adhikari, Tika B. and Louws, Frank J. and Dean, Ralph A.}, year={2020}, month={Nov} }
 @article{wang_eyre_thon_oh_dean_2020, title={Dynamic Changes in the Microbiome of Rice During Shoot and Root Growth Derived From Seeds}, volume={11}, ISSN={["1664-302X"]}, DOI={10.3389/fmicb.2020.559728}, abstractNote={Microbes form close associations with host plants including rice as both surface (epiphytes) and internal (endophytes) inhabitants. Yet despite rice being one of the most important cereal crops agriculturally and economically, knowledge of its microbiome, particularly core inhabitants and any functional properties bestowed is limited. In this study, the microbiome in rice seedlings derived directly from seeds was identified, characterized and compared to the microbiome of the seed. Rice seeds were sourced from two different locations in Arkansas, USA of two different rice genotypes (Katy, M202) from two different harvest years (2013, 2014). Seeds were planted in sterile media and bacterial as well as fungal communities were identified through 16S and ITS sequencing, respectively, for four seedling compartments (root surface, root endosphere, shoot surface, shoot endosphere). Overall, 966 bacterial and 280 fungal ASVs were found in seedlings. Greater abundance and diversity were detected for the microbiome associated with roots compared to shoots and with more epiphytes than endophytes. The seedling compartments were the driving factor for microbial community composition rather than other factors such as rice genotype, location and harvest year. Comparison with datasets from seeds revealed that 91 (out of 296) bacterial and 11 (out of 341) fungal ASVs were shared with seedlings with the majority being retained within root tissues. Core bacterial and fungal microbiome shared across seedling samples were identified. Core bacteria genera identified in this study such as Rhizobium, Pantoea, Sphingomonas, and Paenibacillus have been reported as plant growth promoting bacteria while core fungi such as Pleosporales, Alternaria and Occultifur have potential as biocontrol agents.}, journal={FRONTIERS IN MICROBIOLOGY}, author={Wang, Mengying and Eyre, Alexander W. and Thon, Michael R. and Oh, Yeonyee and Dean, Ralph A.}, year={2020}, month={Sep} }