Rice is used as a staple food in different areas of world, especially in China. In recent years, rice seedlings have been affected seriously by symptoms resembling bacterial palea browning (BPB) in Heilongjiang Province. To isolate and identify the pathogenic bacteria responsible for the disease, 40 bacterial strains were isolated from diseased rice seedlings collected from the four major accumulative-temperature zones of rice fields cultivated in Heilongjiang Province, and these were identified as 13 species based on morphological characteristics and 16S ribosomal RNA (rRNA) gene sequences. Inoculation of all the isolates on healthy rice seedlings showed that the nine Enterobacter cloacae isolates were the pathogens causing typical symptoms of BPB, including yellowing to pale browning, stunting, withering, drying, and death. Moreover, the nine E. cloacae isolates could also cause symptoms of bacterial disease on the seedlings of soybean (Glycine max), maize (Zea mays L.), and tomato (Solanum lycopersicum). Phylogenetic analysis based on the 16S rRNA gene sequences and phenotypic and biochemical characteristics indicated that these nine pathogenic isolates were E. cloacae. In addition, analysis of the sequences of four housekeeping genes (rpoB, gyrB, infB, and atpD) from the selected strain SD4L also assigned the strain to E. cloacae. Therefore, E. cloacae is the pathogen causing disease of rice seedlings in Heilongjiang Province, which we propose to classify as a form of BPB. To the best of our knowledge, this is the first study to identify E. cloacae as a causal agent of BPB in rice.

Rice seedling blight, caused by Fusarium oxysporum, significantly affects global rice production levels. Fluoro-substituted benzothiadiazole derivatives (FBT) and chitosan oligosaccharide (COS) are elicitors that can enhance plant resistance to pathogen infection. However, there is a lack of information regarding FBT and COS used as elicitors in rice seedlings blight. Therefore, the aim of this study was to evaluate the effect of FBT and COS treatments on rice seedling blight and elucidate the molecular mechanisms of the two elicitors for inducing resistance using proteomic technique. Results indicated that FBT and COS significantly reduced the disease incidence and index, and relived the root growth inhibition caused by F. oxysporum (p < 0.05). Biochemical analyses demonstrated that these two elicitors effectively enhanced activities of defense enzymes. Moreover, the proteomic results of rice root tissues disclosed more differentially expressed proteins in diterpenoid biosynthesis pathway that were particularly stimulated by two elicitors compared to the other pathways studied, resulting in the accumulation of antimicrobial substance, momilactone. Findings of this study could provide sound theoretical basis for further applications of FBT and COS used as rice elicitors against seedling blight.

Planting rice in saline–alkali land can effectively improve saline–alkali soil and increase grain yield, but traditional identification methods for saline–alkali-tolerant rice varieties require tedious and time-consuming field investigations based on growth indicators by rice breeders. In this study, the Python machine deep learning method was used to analyze the Raman molecular spectroscopy of rice and assist in feature attribution, in order to study a fast and efficient identification method of saline–alkali-tolerant rice varieties. A total of 156 Raman spectra of four rice varieties (two saline–alkali-tolerant rice varieties and two saline–alkali-sensitive rice varieties) were analyzed, and the wave crests were extracted by an improved signal filtering difference method and the feature information of the wave crest was automatically extracted by scipy.signal.find_peaks. Select K Best (SKB), Recursive Feature Elimination (RFE) and Select F Model (SFM) were used to select useful molecular features. Based on these feature selection methods, a Logistic Regression Model (LRM) and Random Forests Model (RFM) were established for discriminant analysis. The experimental results showed that the RFM identification model based on the RFE method reached a higher recognition rate of 89.36%. According to the identification results of RFM and the identification of feature attribution materials, amylum was the most significant substance in the identification of saline–alkali-tolerant rice varieties. Therefore, an intelligent method for the identification of saline–alkali-tolerant rice varieties based on Raman molecular spectroscopy is proposed.

Early-matured aromatic japonica rice from the Northeast is the most popular rice commodity in the Chinese market. The Qigeng10 (QG10) was one of the varieties with the largest planting area in this region in recent years. It was an early-matured japonica rice variety with a lot of superior traits such as semi-dwarf, lodging resistance, long grain, aromatic and good quality. Therefore, a high-quality assembly of Qigeng10 genome is critical and useful for japonica research and breeding. In this study, we produced a high-precision QG10 chromosome-level genome by using a combination of Nanopore and Hi-C platforms. Finally, we assembled the QG10 genome into 77 contigs with an N50 length of 11.80 Mb in 27 scaffolds with an N50 length of 30.55 Mb. The assembled genome size was 378.31Mb with 65 contigs and constituted approximately 99.59% of the 12 chromosomes. We identified a total of 1,080,819 SNPs and 682,392 InDels between QG10 and Nipponbare. We also annotated 57,599 genes by the Ab initio method, homology-based technique, and RNA-seq. Based on the assembled genome sequence, we detected the sequence variation in a total of 63 cloned genes involved in grain yield, grain size, disease tolerance, lodging resistance, fragrance, and many other important traits. Finally, we identified five elite alleles (qTGW2Nipponbare, qTGW3Nanyangzhan, GW5IR24, GW6Suyunuo, and qGW8Basmati385) controlling long grain size, four elite alleles (COLD1Nipponbare, bZIP73Nipponbare, CTB4aKunmingxiaobaigu, and CTB2Kunmingxiaobaigu) controlling cold tolerance, three non-functional alleles (DTH7Kitaake, Ghd7Hejiang19, and Hd1Longgeng31) for early heading, two resistant alleles (PiaAkihikari and Pid4Digu) for rice blast, a resistant allele STV11Kasalath for rice stripe virus, an NRT1.1BIR24 allele for higher nitrate absorption activity, an elite allele SCM3Chugoku117 for stronger culms, and the typical aromatic gene badh2-E2 for fragrance in QG10. These results not only help us to better elucidate the genetic mechanisms underlying excellent agronomic traits in QG10 but also have wide-ranging implications for genomics-assisted breeding in early-matured fragrant japonica rice.