First Report of New Bacterial Leaf streak of Rice Caused by Pantoea ananatis in China

Rice (Oryza sativa L.) is the largest grain crop, accounting for about 40 % of the total grain production in China. In mid-July 2021, bacterial leaf streak-like disease emerged in rice varieties Chunyou584 and Yongyou2604 in Linyi city, Shandong Province, China. Disease incidences of the disease ranged from 80% to 90% in the surveyed fields. Infected rice leaves displayed dark green to yellowish-brown water-soaked thin streaks, and a large amount of beaded yellow oozes were observed on the lesions. After drying, there were gelatinous granules that were not easy to fall off and spread between leaf veins (Fig.S1A). According to the field symptoms of this disease, it was preliminarily suspected to be rice bacterial leaf streak caused by Xanthomonas oryzae pv. oryzicola (Xoc), which is a guaranteed disease in China. To isolate the causal agent, leaf discs (~1 cm2) of diseased leaves were collected from the margins of the lesions, surface sterilized and ground into pieces in sterile double distilled water. The 10-3, 10-4 and 10-5 dilutions were spread onto peptone sugar agar (PSA) and incubated at 28°C for 36 hours. Yellow mucous bacterial colonies were consistently obtained on PSA medium. To identify the pathogen, fragments of the 16S rDNA, leuS and rpoB were amplified and sequenced using the primers previously reported (Yu et al. 2021). Three strains (LY01, LY02 and LY03) showed identical colony morphology and LY01 was used for further analyses. Sequence analyses showed that the fragments of 16S rDNA (955 bp, GenBank accession number: OK261898), leuS (755 bp, GenBank accession number: OK298387) and rpoB (926 bp, GenBank accession number: OK298388) of strain LY01 shared 99.16%, 99.46% and 100% similarities with those of Pantoea ananatis TZ39 (GenBank accession numbers: CP081342.1 for 16S rDNA, MW981338.1 for leuS and MW981344.1 for rpoB), respectively, which suggest the pathogenic bacterial strain LY01 isolated is P. ananatis. In addition, the single colony of P. ananatis LY01 was shown as Fig. S2B. Furthermore, pathogenicity tests were also performed according to the following steps. Bacterial suspension at OD600=0.1 was inoculated into eight rice leaves of four healthy rice plants (Chunyou 584) at 25-33°C and 60%-80% relative humidity in the field using a clipping method (Yang et al. 2020) or spraying methods, and sterile distilled water was as negative control. The clipped leaves (Fig. S1B) and spray-inoculated leaves (Fig. S1C) showed dark green water-soaked streaks at 14 days after inoculation, respectively, which showed similar symptoms with those samples collected from the fields (Fig. S1A). On contrary, the control rice leaves remained healthy and symptomless (Fig. S2A). The bacterium was re-isolated in the inoculated rice leaves and the re-isolated bacterial isolates, which was confirmed by sequencing 16S rDNA, leuS and rpoB, incited the same symptoms as in fields, which fulfills Koch’s postulates. In the past decade, P. ananatis was reported to result in grain discoloration and leaf blight in China (Yan et al. 2010; Xue et al. 2020, Yu et al. 2021), which could result in 40% - 60% yield losses. To our best knowledge, this is the first report of the bacterial leaf streak-likely disease occurred in Shandong Province caused by P. ananatis, so we named it as Pantoea leaf streak of rice. Although P. ananatis was also reported in Zhejiang province and Jiangxi province, which caused leaf streak lesions on rice, the disease symptoms are completely different from those of Pantoea leaf streak of rice. To the best of our knowledge, this is the first report of Pantoea leaf streak of rice caused by P. ananatis. This study provides sloid evidence that Pantoea leaf streak of rice in Eastern China can be caused by the new pathogen, P. ananatis, rather than Xoc as traditionally assumed. Disease development and quarantine of the new Pantoea leaf streak of rice disease caused by P. ananatis on rice need more attention in the near future.

Evaluation The Efficiency of Some of Bio - Control Fungi on The Content of Rice Leaves (Oryza Sativa L.) Class Jassmine of Phenols, Alkaloids, And Some of Hormones

This study was conducted to evaluate the effect of using biocontrol fungi - Trichoderma harzianum. Australian (T.h.a). and Trichoderma harzianum. tahadi(T.h.t) and Chaetumium elatum( C.e) isolates on contents of rice leaves ) Oryza sativa L. (class jasmine of phenols, alkaloids, and hormones( zeatin, gibberellic acid, indol acitic acid). To attaining these aims, two experements were carryied out in two regions at Rice Research Center(RRC), and Agriculture college - AL-Najaf province. The results of this study can be summarized as follows: The suspension (10)-4 of biocontrol agent T.h.a gave a significant difference in concentrations of phenols in rice leaves for treatment: Soil + hay + NP + T.h.a which reached 0.378, 0.363 ppm in RRC and college of agriculture fields, in compare with control treatment which gave 0.251,0.245 ppm, respectively. T.h.a. gave a significant differences in concentrations of alkaloids in rice leaves for treatment: Soil + hay + NP + T.h.a which reached 1.67,1.51 µg/ml in RRC and college of agriculture fields, in compare with control treatment which gave 1.19,1.15 µg/ml., respectively T.h.a attained the highest concentrations of hormones ( zeatin, gebberllic acid, indol acitic acid) in rice leaves for treatment: Soil + hay + NP + T.h.a which reached (0.0941, 53.84, 0.287) ppm, at RRC and (0.0835, 44.52, 0.268) ppm for college of agriculture fields, in compare with control treatment which gave ( 0.0712, 51.12, 0.210) ppm with RRC and (0.0523, 42.10, 0.174)ppm for college of agriculture, respectively.

Applying Spectral Fractal Dimension to Predict the SPAD Value of Rice Leaves Under Disease Stress

BackgroundThe chlorophyll content is a vital indicator for reflecting the photosynthesis ability of plants and it plays a significant role in monitoring the general health of plants. Since the chlorophyll content and the soil-plant analysis development (SPAD) value are positively correlated, it is feasible to estimate the SPAD value by calculating the vegetation indices (VIs) through hyperspectral images, thereby estimating the chlorophyll content. However, current indices simply adopted few wavelengths of the hyperspectral information, which may decrease the estimation accuracy. Besides, few researches explored the applicability of VIs over plant leaves under disease stress.MethodsIn this study, the SPAD value was estimated by calculating the fractal dimension of hyperspectral curves, ranging from 420 to 950 nm. The correlation between the SPAD value and wavelengths under disease stress was analyzed. In addition, a SPAD prediction model was built upon the combination of selected indices and 4 machine learning methods, including decision tree (DT), partial least square regression (PLSR), support vector regression (SVR), and back propagation neural network (BPNN). The performance of these models was compared through the correlation of determination, root mean square error, and relative error.ResultsThe results suggested that the SPAD value of rice leaves under different disease levels were sensitive to different wavelengths, meaning that the fixed wavelength selection in current indices may achieve poor estimation results. Compared with current VIs, a stronger positive correlation was detected between the SPAD value and our proposal, reaching an average correlation coefficient of 0.8263. For the prediction model, the one built with our proposal and SVR achieved the best performance, reaching R2, RMSE, and RE at 0.8752, 3.7715, and 7.8614%, respectively.ConclusionsThis work provides an in-depth insight for accurately and robustly estimating the SPAD value of rice leaves under disease stress, and our proposal is of great significance for monitoring the chlorophyll content in large-scale fields non-destructively.

Evaluation of Phytochemical Contents and In Vitro Antioxidant, Anti-Inflammatory, and Anticancer Activities of Black Rice Leaf (Oryza sativa L.) Extract and Its Fractions

Black rice leaves (Oryza sativa L.) are a major part of rice straw left in open fields after rice harvest as agricultural waste. In this study, crude ethanolic extract (CEE) and various solvent fractions (hexane (Hex), ethyl acetate (EtOAc), n-butanol (n-BuOH), and aqueous fractions) of black rice leaves were investigated for their bioactive compound contents as well as antioxidant, anti-inflammatory, and anticancer activities. The results demonstrated that among all the fractions, the n-BuOH fraction presented the greatest contents of total phenolics and flavonoids, while anthocyanins were found to be abundant in the n-BuOH and aqueous fractions, which also exhibited powerful antioxidant abilities according to DPPH and ABTS radical-scavenging assays and a reducing power assay. Regarding anti-inflammatory activity, CEE and EtOAc reduced the production of NO and cytokine secretion (PGE2, IL-6, and IL-1β) but displayed less effect on tumor necrosis factor α (TNF-α) release in lipopolysaccharide (LPS)-induced RAW 264.7 cells. They also significantly decreased iNOS and COX-2 protein expression. Additionally, the phenolics-rich ethyl acetate fraction showed the greatest activity against HepG2 liver carcinoma cells, inhibited cell growth, increased the Sub-G1 population, and induced apoptosis via mitochondrion-dependent mechanisms. In conclusion, black rice leaves, a byproduct of rice, exhibited strong antioxidant, anti-inflammatory, and anticancer capacities and might be useful for application in functional foods and the pharmaceutical industry.

Hexokinase gene OsHXK1 positively regulates leaf senescence in rice

Background Leaf senescence is a highly complex and meticulous regulatory process, and the disruption of any factor involved in leaf senescence might lead to premature or delayed leaf senescence and thus result in reduced or increased crop yields. Despite sincere efforts by scientists, there remain many unsolved problems related to the regulatory factors and molecular mechanisms of leaf senescence. Results This study successfully revealed that OsHXK1 was highly expressed in senescent leaves of rice. The upregulation of OsHXK1 led to premature senescence of rice leaves, a decreased level of chlorophyll, and damage to the chloroplast structure. The overexpression of OsHXK1 resulted in increases in glucose and ROS levels and produced programmed cell death (PCD) signals earlier at the booting stage. Further analysis showed that expression level of the respiratory burst oxidase homolog (RBOH) genes and OsGLO1 were increased in OsHXK1-overexpressing plants at the booting stage. Conclusions Overall, the outcomes of this study suggested that OsHXK1 could act as a positive regulator of rice leaf senescence by mediating glucose accumulation and inducing an increase in ROS.

Closer vein spacing by ectopic expression of nucleotide-binding and leucine-rich repeat proteins in rice leaves

Key message Elevated expression of nucleotide-binding and leucine-rich repeat proteins led to closer vein spacing and higher vein density in rice leaves. Abstract To feed the growing global population and mitigate the negative effects of climate change, there is a need to improve the photosynthetic capacity and efficiency of major crops such as rice to enhance grain yield potential. Alterations in internal leaf morphology and cellular architecture are needed to underpin some of these improvements. One of the targets is to generate a “Kranz-like” anatomy in leaves that includes decreased interveinal spacing close to that in C4 plant species. As C4 photosynthesis has evolved from C3 photosynthesis independently in multiple lineages, the genes required to facilitate C4 may already be present in the rice genome. The Taiwan Rice Insertional Mutants (TRIM) population offers the advantage of gain-of-function phenotype trapping, which accelerates the identification of rice gene function. In the present study, we screened the TRIM population to determine the extent to which genetic plasticity can alter vein density (VD) in rice. Close vein spacing mutant 1 (CVS1), identified from a VD screening of approximately 17,000 TRIM lines, conferred heritable high leaf VD. Increased vein number in CVS1 was confirmed to be associated with activated expression of two nucleotide-binding and leucine-rich repeat (NB-LRR) proteins. Overexpression of the two NB-LRR genes individually in rice recapitulates the high VD phenotype, due mainly to reduced interveinal mesophyll cell (M cell) number, length, bulliform cell size and thus interveinal distance. Our studies demonstrate that the trait of high VD in rice can be achieved by elevated expression of NB-LRR proteins limited to no yield penalty.

Detection and Classification of Rice Infestation with Rice Leaf Folder (Cnaphalocrocis medinalis) Using Hyperspectral Imaging Techniques

The detection of rice leaf folder (RLF) infestation usually depends on manual monitoring, and early infestations cannot be detected visually. To improve detection accuracy and reduce human error, we use push-broom hyperspectral sensors to scan rice images and use machine learning and deep neural learning methods to detect RLF-infested rice leaves. Different from traditional image processing methods, hyperspectral imaging data analysis is based on pixel-based classification and target recognition. Since the spectral information itself is a feature and can be considered a vector, deep learning neural networks do not need to use convolutional neural networks to extract features. To correctly detect the spectral image of rice leaves infested by RLF, we use the constrained energy minimization (CEM) method to suppress the background noise of the spectral image. A band selection method was utilized to reduce the computational energy consumption of using the full-band process, and six bands were selected as candidate bands. The following method is the band expansion process (BEP) method, which is utilized to expand the vector length to improve the problem of compressed spectral information for band selection. We use CEM and deep neural networks to detect defects in the spectral images of infected rice leaves and compare the performance of each in the full frequency band, frequency band selection, and frequency BEP. A total of 339 hyperspectral images were collected in this study; the results showed that six bands were sufficient for detecting early infestations of RLF, with a detection accuracy of 98% and a Dice similarity coefficient of 0.8, which provides advantages of commercialization of this field.

Control of rice blast disease caused by Magnaporthe oryzae by application of antifungal nanomaterials from Emericella nidulans

Metabolites of Emericella nidulans (EN) were separated by chromatographic methods from crude hexane included emericellin and sterigmatocystin, while crude ethyl acetate found demethylsterigmatocystin. These metabolites proved to be antagonistic to Magnaporthe oryzae, the causal agent of rice blast. Crude extracts and nano-particles derived from EN inhibited M. oryzae. The ethyl acetate crude extract derived inhibited M. oryzae with an effective dose (ED₅₀) of 66 μg/mL. The nanoparticles showed better inhibition of M. oryzae than crude extracts at low concentrations. Nanoparticles, namely from crude ethyl acetate, crude methanol and crude hexane of EN were active against M. oryzae with ED₅₀ of 4.2 μg/mL, 4.5 μg/mL, 8.9 μg/mL, respectively. It detected sakuranetin (rate of flow value is 0.09) in nano-EN treated rice leaves. These nanoparticles inhibited M. oryzae and acted as a new elicitor to induce immunity.

Detection and Dynamic Variation Characteristics of Rice Nitrogen Status after Anthesis Based on the RGB Color Index

We aimed to elucidate the color changes of rice leaves after anthesis and create an algorithm for monitoring the nitrogen contents of rice leaves and of the whole plant. Hence, we aimed to provide a theoretical basis for the precise management of rice nitrogen fertilizer and the research and development of digital image nutrition monitoring equipment and reference. We selected the leaf colors of the main stems of four major rice varieties promoted in production, including Huaidao 5 (late-maturing medium japonica rice), Yangjing 4227 (early maturing late japonica rice), Changyou 5 (late japonica hybrid rice), and Yongyou 8 (late japonica hybrid rice). Under different nitrogen levels, the leaf R, G, and B values of the four rice varieties at different stages after anthesis, the dynamic changes in RGB normalized values, the correlations between RGB normalized values and leaf SPAD values, the leaf nitrogen content and whole plant nitrogen content, and the nitrogen prediction model were studied. The research results demonstrate the following: (1) regardless of nitrogen levels, the leaf of R, G, B, NRI, NGI and NBI of different rice varieties after anthesis followed the order, G > R > B. R, G, NRI, NGI, and days after heading could be fitted according to a logarithmic equation, y = aebx (0.726 ≤ R2 ≤ 0.992); B, NBI, and days after heading could be fitted using a linear equation, y = a + bx (0.863 ≤ R2 ≤ 0.992). Both fitting effects were significant (except NGI). (2) A quadratic function (Y = −1296.192x2 + 539.419x − 10.914; Y = −1173.104x2 + 527.073x − 12.993) was adopted to construct a monitoring model for the NBI and SPAD values of japonica rice and hybrid japonica rice leaves after anthesis and the R2 values were 0.902 and 0.838, respectively. Exponential functions (Y = 5.698e7.261x; Y = 3.371e9.326x) were employed to construct monitoring models of leaf nitrogen content, and the R2 values were 0.833 and 0.706, respectively. Exponential functions (Y = 5.145e4.9143x; Y = 3.966e5.364x) were also used to construct a monitoring model for the nitrogen content of the whole plant, and the R2 values were 0.737 and 0.511, respectively. The results obtained from prediction tests by using Determination Coefficient (R2), Relative Percent Deviation (RPD), and Root Mean Square Error (RMSE) showed that it was feasible, accurate, and efficient to use a scanner for measuring the nitrogen content of rice.