Early Detection of Botrytis cinerea Infection in Cut Roses Using Thermal Imaging.

Botrytis cinerea (B. cinerea) causes gray mold disease (GMD), which results in physiological disorders in plants that decrease the longevity and economic value of horticultural crops. To prevent the spread of GMD during distribution, a rapid, early detection technique is necessary. Thermal imaging has been used for GMD detection in various plants, including potted roses; however, its application to cut roses, which have a high global demand, has not been established. In this study, we investigated the utility of thermal imaging for the early detection of B. cinerea infection in cut roses by monitoring changes in petal temperature after fungal inoculation. We examined the effects of GMD on the postharvest quality and petal temperature of cut roses treated with different concentrations of fungal conidial suspensions and chemicals. B. cinerea infection decreased the flower opening, disrupted the water balance, and decreased the vase life of cut roses. Additionally, the average temperature of rose petals was higher for infected flowers than for non-inoculated flowers. One day before the appearance of necrotic symptoms (day 1 of the vase period), the petal temperature in infected flowers was significantly higher, by 1.1 °C, than that of non-inoculated flowers. The GMD-induced increase in petal temperature was associated with the mRNA levels of genes related to ethylene, reactive oxygen species, and water transport. Furthermore, the increase in temperature caused by GMD was strongly correlated with symptom severity and fungal biomass. A multiple regression analysis revealed that the disease incidence in the petals was positively related to the petal temperature one day before the appearance of necrotic symptoms. These results show that thermography is an effective technique for evaluating changes in petal temperature and a possible method for early GMD detection in the cut flower industry.

Development of a longevity prediction model for cut roses using hyperspectral imaging and a convolutional neural network.

Introduction: Hyperspectral imaging (HSI) and deep learning techniques have been widely applied to predict postharvest quality and shelf life in multiple horticultural crops such as vegetables, mushrooms, and fruits; however, few studies show the application of these techniques to evaluate the quality issues of cut flowers. Therefore, in this study, we developed a non-contact and rapid detection technique for the emergence of gray mold disease (GMD) and the potential longevity of cut roses using deep learning techniques based on HSI data. Methods: Cut flowers of two rose cultivars ('All For Love' and 'White Beauty') underwent either dry transport (thus impaired cut flower hydration), ethylene exposure, or Botrytis cinerea inoculation, in order to identify the characteristic light wavelengths that are closely correlated with plant physiological states based on HSI. The flower bud of cut roses was selected for HSI measurement and the development of a vase life prediction model utilizing YOLOv5. Results and discussion: The HSI results revealed that spectral reflectance between 470 to 680 nm was strongly correlated with gray mold disease (GMD), whereas those between 700 to 900 nm were strongly correlated with flower wilting or vase life. To develop a YOLOv5 prediction model that can be used to anticipate flower longevity, the vase life of cut roses was classed into two categories as over 5 d (+5D) and under 5 d (-5D), based on scoring a grading standard on the flower quality. A total of 3000 images from HSI were forwarded to the YOLOv5 model for training and prediction of GMD and vase life of cut flowers. Validation of the prediction model using independent data confirmed its high predictive accuracy in evaluating the vase life of both 'All For Love' (r2 = 0.86) and 'White Beauty' (r2 = 0.83) cut flowers. The YOLOv5 model also accurately detected and classified GMD in the cut rose flowers based on the image data. Our results demonstrate that the combination of HSI and deep learning is a reliable method for detecting early GMD infection and evaluating the longevity of cut roses.

Regulation of Botrytis cinerea Infection and Gene Expression in Cut Roses by Using Nano Silver and Salicylic Acid.

Botrytis cinerea (B. cinerea) is one of the necrotrophic pathogens resulting in the heaviest commercial losses in cut rose flowers, and the severity of gray mold disease partly depends on the presence of ethylene during the storage and transport. The effectiveness of nano silver (NS) and salicylic acid (SA) was assessed as a novel control agent in protecting the cut rose flowers against B. cinerea infection and ethylene damages. The efficacy of NS and SA was compared with an inoculated control (CON). A non-treated control (NT) was also used to evaluate the natural infection process. The results indicated that pretreatment with 20 mg L-1 NS significantly reduced B. cinerea growth in rose petals during vase periods. NS effectively suppressed the mRNA levels of ethylene biosynthesis genes (RhACS2, RhACS4, and RhACO1) and the reduction in expression levels of ethylene receptor genes (RhETR1, RhETR2, and RhETR5) and the downstream regulator RhCTR2 in rose petals after B. cinerea inoculation. NS application also decreased the expression of the B. cinerea snod-prot-like 1 (Bcspl1) gene which acts as the virulence factor in cut roses. In NS flowers, the maximum quantum yield of PSII (Fv/Fm) value was higher and the leaf temperature was lower on day 1, suggesting that these factors can be used for detecting B. cinerea infection and water stress in cut rose flowers. Furthermore, NS improved water relations and extended the vase life of cut rose flowers by 3.3 d, compared with that of NT flowers. In contrast, SA had no inhibitive effects on both B. cinerea growth and ethylene response in cut roses. The findings from the present study highlight NS as a promising new candidate for preventing B. cinerea infection and ethylene damages and for improving the postharvest quality of cut roses exported overseas.

Analysis of gene expression during the transition to climacteric phase in carnation flowers (Dianthus caryophyllus L.).

It has been generally thought that in ethylene-sensitive plants such as carnations, senescence proceeds irreversibly once the tissues have entered the climacteric phase. While pre-climacteric petal tissues have a lower sensitivity to ethylene, these tissues are converted to the climacteric phase at a critical point during flower development. In this study, it is demonstrated that the senescence process initiated by exogenous ethylene is reversible in carnation petals. Petals treated with ethylene for 12h showed sustained inrolling and senescence, while petals treated with ethylene for 10h showed inrolling followed by recovery from inrolling. Reverse transcription-PCR analysis revealed differential expression of genes involved in ethylene biosynthesis and ethylene signalling between 10h and 12h ethylene treatment. Ethylene treatment at or beyond 12h (threshold time) decreased the mRNA levels of the receptor genes (DcETR1, DcERS1, and DcERS2) and DcCTR genes, and increased the ethylene biosynthesis genes DcACS1 and DcACO1. In contrast, ethylene treatment under the threshold time caused a transient decrease in the receptor genes and DcCTR genes, and a transient increase in DcACS1 and DcACO1. Sustained DcACS1 accumulation is correlated with decreases in DcCTR genes and increase in DcEIL3 and indicates that tissues have entered the climacteric phase and that senescence proceeds irreversibly. Inhibition of ACS (1-aminocyclopropane-1-carboxylic acid synthase) prior to 12h ethylene exposure was not able to prevent reduction in transcripts of DcCTR genes, yet suppressed transcript of DcACS1 and DcACO1. This leads to the recovery from inrolling of the petals, indicating that DcACS1 may act as a signalling molecule in senescence of flowers.