Rice Panicle Research Articles

Performance evaluation of the ORYZA_V3 model for rice growth and organ nitrogen content

AbstractThe ORYZA version 3 (ORYZA_V3) model is commonly used for simulating paddy rice (Oryza sativa L.) growth. However, few studies have investigated the performance of the ORYZA_V3 model for predicting in‐season crop growth variables, especially for the nitrogen (N) translocation process among paddy rice organs in the whole growing season, that is, from sowing to harvest stages. This study examines the prediction accuracy of seven paddy rice growth variables based on one cropping season of field experiment. The results show that (1) the ORYZA_V3 model generates accurate prediction of paddy rice leaf area index, above‐ground biomass, and yield, where root mean square errors (RMSEs) are 0.98–1.11 ha/ha, 2360.5–3028.7 kg/ha, and 492.9–515.2 kg/ha, respectively, coefficient of determination (R2) ranges from 0.76 to 1.00, and index of agreement (D‐index) ranges from 0.50 to 0.98. (2) The prediction accuracy of paddy rice leaf and stem N contents is acceptable, where RMSE ranges from 0.0017 to 0.0041 kg/kg, R2 ranges from 0.82 to 0.96, and D‐index ranges from 0.93 to 0.98. (3) The ORYZA_V3 model cannot generate accurate prediction of rice root and panicle N contents, where RMSE ranges from 0.0007 to 0.0022 kg/kg, R2 ranges from 0.01 to 0.20, and D‐index ranges from 0.17 to 0.65. The structural uncertainty in the N translocation module may be a major reason for the unacceptable crop model prediction. This study demonstrated the substantial potential of the ORYZA_V3 model for simulating and understanding paddy rice growth and organ N translocation.

The OsNLP3/4-OsRFL module regulates nitrogen-promoted panicle architecture in rice.

Rice panicles, a major component of yield, are regulated by phytohormones and nutrients. How mineral nutrients promote panicle architecture remains largely unknown. Here, we report that NIN-LIKE PROTEIN3 and 4 (OsNLP3/4) are crucial positive regulators of rice panicle architecture in response to nitrogen (N). Loss-of-function mutants of either OsNLP3 or OsNLP4 produced smaller panicles with reduced primary and secondary branches and fewer grains than wild-type, whereas their overexpression plants showed the opposite phenotypes. The OsNLP3/4-regulated panicle architecture was positively correlated with N availability. OsNLP3/4 directly bind to the promoter of OsRFL and activate its expression to promote inflorescence meristem development. Furthermore, OsRFL activates OsMOC1 expression by binding to its promoter. Our findings reveal the novel N-responsive OsNLP3/4-OsRFL-OsMOC1 module that integrates N availability to regulate panicle architecture, shedding light on how N nutrient signals regulate panicle architecture and providing candidate targets for the improvement of crop yield.

Assessment of variability parameters and diversity of panicle architectural traits associated with yield in rice (Oryza sativa L.)

The rice panicle, a pivotal reproductive structure, signifies the transition from vegetative to reproductive growth in plants. Comprising components such as the rachis, primary and secondary branches, seed quantities and branch lengths, panicle architecture profoundly influences grain production. This study delves into the diversity of panicle architecture traits and scrutinizes variability parameters across 69 distinct rice genotypes. Our findings underscore substantial variations in panicle architecture traits among genotypes. Particularly noteworthy are traits with the highest coefficient of variation (CV%), encompassing the count of secondary branches, single plant yield, productive tillers per plant, seeds per secondary branch and panicle weight. Correlation analysis reveals robust positive connections between panicle weight, the number of filled grains per panicle, 1000-grain weight and single plant yield. The number of secondary branches exhibits the most substantial phenotypic coefficient of variation (PCV%) at 47.14%, accompanied by a genotypic coefficient of variation (GCV%) of 43.57%. Traits such as days to 50% flowering, plant height and number of filled grains per panicle manifest high heritability (97.04%, 91.24% and 76.22% respectively) and notable genetic advancement (23.11%, 39.62% and 47.49%). The principal component analysis identifies the primary component (PC1) as the principal contributor to variance. Biplot analysis accentuates positive correlations between attributes like the number of filled grains per panicle, panicle length, plant height, primary branch count, panicle weight, seeds per primary branch and the number of secondary branches with single plant yield. By employing Mahalanobis D2 statistics, the classification of genotypes into 6 distinct clusters reveals clusters III and IV as distinguished by their significant inter-cluster and intra-cluster distances. This comprehensive analysis unveils the potential for harnessing panicle architecture traits to enhance grain production and advances our comprehension of intricate relationships within diverse rice genotypes.

Paddy yield prediction based on 2D images of rice panicles using regression techniques

Paddy yield prediction based on 2D images of rice panicles using regression techniques

An atypical heterotrimeric Gα and its interactome suggest an extra-large role in overcoming abiotic and biotic stress.

Canonical heterotrimeric G-proteins (G-proteins) are comprised of Gα, Gβ, and Gγ subunits. G-proteins regulate multiple crucial plant growth and development processes, incorporating environmental responses. Besides Gα, Gβ and Gγ, the discovery of atypical Gα subunits termed as extra-large G-proteins or extra-large GTP-binding proteins (XLGs) makes G-protein signaling unique in plants. The C-terminus of XLG shares similarities with the canonical Gα subunits; the N-terminus harbors a nuclear localization signal (NLS) and is rich in cysteine. The earlier explorations suggest XLG's role in flowering, the development of embryos and seedlings, root morphogenesis, stamen development, cytokinin-induced development, stomatal opening and regulation of rice grain filling. The XLGs are also known to initiate signaling cascades that prime plants against a variety of abiotic and biotic stresses. They are also engaged in controlling several agronomic parameters such as rice panicle length, grain filling, grain size, and biomass, highlighting their potential contribution to crop improvement. The present review explores the remarkable properties of non-canonical Gα subunits (XLGs) and reflects on the various developmental, abiotic and biotic stress signaling pathways controlled by them. Moreover, the bottleneck dilemma of how a tiny handful of XLGs control a multiplicity of stress-responsive activities is partially resolved in this review by addressing the interaction of XLGs with different interacting proteins. XLG proteins presented in this review can be exploited to gain access to highly productive and stress-tolerant plants.

High-throughput and separating-free phenotyping method for on-panicle rice grains based on deep learning.

Rice is a vital food crop that feeds most of the global population. Cultivating high-yielding and superior-quality rice varieties has always been a critical research direction. Rice grain-related traits can be used as crucial phenotypic evidence to assess yield potential and quality. However, the analysis of rice grain traits is still mainly based on manual counting or various seed evaluation devices, which incur high costs in time and money. This study proposed a high-precision phenotyping method for rice panicles based on visible light scanning imaging and deep learning technology, which can achieve high-throughput extraction of critical traits of rice panicles without separating and threshing rice panicles. The imaging of rice panicles was realized through visible light scanning. The grains were detected and segmented using the Faster R-CNN-based model, and an improved Pix2Pix model cascaded with it was used to compensate for the information loss caused by the natural occlusion between the rice grains. An image processing pipeline was designed to calculate fifteen phenotypic traits of the on-panicle rice grains. Eight varieties of rice were used to verify the reliability of this method. The R2 values between the extraction by the method and manual measurements of the grain number, grain length, grain width, grain length/width ratio and grain perimeter were 0.99, 0.96, 0.83, 0.90 and 0.84, respectively. Their mean absolute percentage error (MAPE) values were 1.65%, 7.15%, 5.76%, 9.13% and 6.51%. The average imaging time of each rice panicle was about 60 seconds, and the total time of data processing and phenotyping traits extraction was less than 10 seconds. By randomly selecting one thousand grains from each of the eight varieties and analyzing traits, it was found that there were certain differences between varieties in the number distribution of thousand-grain length, thousand-grain width, and thousand-grain length/width ratio. The results show that this method is suitable for high-throughput, non-destructive, and high-precision extraction of on-panicle grains traits without separating. Low cost and robust performance make it easy to popularize. The research results will provide new ideas and methods for extracting panicle traits of rice and other crops.

Probing the effects of silicon amendment on combined stressors on rice: Lead pollution and blast fungus (Magnaporthe oryzae) infection

As agroecology deteriorates, agricultural production is threatened by the combined stressors of exposure to environmental pollutants and pathogenic microbes. Proper agronomic practices for crop growth management and fertilization require understanding plant tolerance strategies. Both rice blast and heavy metals substantially impair rice crops, while silicon (Si) is an effective amendment to alleviate the combined stressors. Herein, this study was conducted to investigate the rice physiology and pathology perspective on the mechanism of Si alleviation against both lead (Pb) toxicity and Magnaporthe oryzae infection, utilizing pot experiments with inoculation of the virulent Magnaporthe oryzae strain. Exogenous Si reduced the phyto-availability and plant absorption of Pb, resulting in a 73.5% reduction in exchangeable Pb concentration in soil and a 40.23% reduction in rice plants. Furthermore, Si addition boosted the plant antioxidant system by increasing the activities of related enzymes, as the activities of catalase, superoxide dismutase, and polyphenol oxidase were significantly improved while the activity of peroxidase in rice panicles decreased. As a result, an improvement in dry matter quantity by 19.19% was observed compared to treatments without Si application, and the panicle blast severity (PBS) was reduced by 0.4–37.52%. Notwithstanding the interaction between the combined stressors, this study revealed that the speciation of Pb formation in the rhizosphere was the primary contributor to the alleviation of abiotic stresses, whereas the regulation of oxidative stress by enzymatic antioxidants played a dominant role in alleviating Magnaporthe oryzae colonization and impairments. The regulation process may reveal the mechanism of siliceous fertilizer functioning in the paddy system. Thereby the role of exogenous Si in anti-fungal, heavy metal toxicology, and plant physiology needs further study to fully elucidate the role of Si amendment, which is proposed to be considered from the perspective of soil chemistry and plant physiology.

Mining the candidate genes of rice panicle traits via a genome-wide association study.

Panicle traits are important for improving the panicle architecture and grain yield of rice. Therefore, we performed a genome-wide association study (GWAS) to analyze and determine the genetic determinants of five panicle traits. A total of 1.29 million single nucleotide polymorphism (SNP) loci were detected in 162 rice materials. We carried out a GWAS of panicle length (PL), total grain number per panicle (TGP), filled grain number per panicle (FGP), seed setting rate (SSR) and grain weight per panicle (GWP) in 2019, 2020 and 2021. Four quantitative trait loci (QTLs) for PL were detected on chromosomes 1, 6, and 9; one QTL for TGP, FGP, and GWP was detected on chromosome 4; two QTLs for FGP were detected on chromosomes 4 and 7; and one QTL for SSR was detected on chromosome 1. These QTLs were detected via a general linear model (GLM) and mixed linear model (MLM) in both years of the study period. In this study, the genomic best linear unbiased prediction (BLUP) method was used to verify the accuracy of the GWAS results. There are nine QTLs were both detected by the multi-environment GWAS method and the BLUP method. Moreover, further analysis revealed that three candidate genes, LOC_Os01g43700, LOC_Os09g25784, and LOC_Os04g47890, may be significantly related to panicle traits of rice. Haplotype analysis indicated that LOC_Os01g43700 and LOC_Os09g25784 are highly associated with PL and that LOC_Os04g47890 is highly associated with TGP, FGP, and GWP. Our results offer essential genetic information for the molecular improvement of panicle traits. The identified candidate genes and elite haplotypes could be used in marker-assisted selection to improve rice yield through pyramid breeding.

First report of Rice panicle blight caused by Fusarium sporotrichioides in China.

Rice (Oryza sativa L.) panicle blight, caused by various fungal and bacterial pathogens, is an emerging threat to rice production, due to the impact on rice yield and quality. In the autumn of 2020, a survey was conducted to understand the etiology of the disease in Liaoning province, an important rice growing area in northeastern China. Rice seeds with typical reddish or brown spots on the glumes were collected from various rice fields. Symptomatic seeds were sterilized with 5% sodium hypochlorite and 75% ethanol, rinsed in sterile distilled water, and placed on potato dextrose agar (PDA) plates. After 3 to 5 days of incubation at 25°C, suspected Fusarium strains showing cream to salmon colonies on PDA were purified by the single-spore isolation method. The identification of these strains were performed based on morphological and molecular characteristics. Fusarium incarnatum-equiseti species complex was the most frequently, followed by the members of Fusarium graminearum species complex and Fusarium fujikuroi species complex. However, one strain was identified as F. sporotrichioides Sherb. based on the following results: (I) Colonies on PDA produced dense mycelia and typical red pigment on the undersurface. Macroconidia were usually 3- to 5-septate, moderately curved to straight, and 27.46 ± 7.16 × 3.78 ± 0.8 μm (n = 50). Microconidia were ellipsoid to fusoid and 9.77 ± 2.29 × 2.99 ± 0.65 μm (n = 50). (II) Genomic DNA was extracted by AxyPrep Multisource Genomic DNA Miniprep Kit according to the manufacturer's instructions; the sequence analysis of partial translation elongation factor-1α (TEF-1α) and RNA polymerase II second largest subunit (RPB2) were accomplished with the primers EF1/2 and RPB5F/7CR, respectively. BLAST searches of the obtained sequences had 99-100% homology with several F. sporotrichioides strains from GenBank. DNA sequences of partial TEF-1α and RPB2 were deposited in GenBank as OQ068267 and OQ068269, respectively. (III) This strain can synthesis T-2, HT-2, diacetoxyscirpenol (DAS), and Neosolaniol (NEO) toxin at the concentration of about 5000, 600, 700 and 8000 μg/kg in rice culture, respectively, according to the previous culture and analysis methods (1,2). (IV) Pathogenicity tests were conducted with the rice variety Nanjing 9108 by spraying spore suspension (106 conidia/ml) on rice spikes (5 mL per spike) at the flowering stage. Control spikes were inoculated with sterile distilled water. Three weeks after inoculation, the inoculated rice glumes showed similar symptoms with the original samples in the field. No symptoms were observed on controls. Besides, F. sporotrichioides was successfully recovered from the inoculated rice spikes but not from controls. To our knowledge, this is the first report of F. sporotrichioides causing rice panicle blight in China and this disease appears to be a serious risk to food safety and human health. Funding: This work was supported by Jiangsu Agriculture Science and Technology (CX(21)1005).

First report of bacterial panicle blight (BPB) in Rice caused by Burkholderia gladioli in Bangladesh.

Bacterial panicle blight (BPB) has become one of the most destructive diseases of rice worldwide and Burkholderia gladioli and B. glumae are two major pathogens causing BPB (1). This disease causes several types of damage, most importantly grain spotting, rot, and panicle blight, which can result in yield losses of 75% or more (1,3). In recent years, symptoms including sheath rot, grain spotting, grain rot, and panicle blight have been observed in both inbred and hybrid rice varieties. These symptoms resemble those of BPB and cause cultivar-dependent yield losses. (3) also reported the same symptoms for BPB. To confirm the cause of the disease, 21 rice panicles (Haridhan, a local variety) with typical BPB symptoms were collected from a farmer's field in the region of Mymensingh, Bangladesh during the rainy season in mid-October, 2021. Due to the severity of the outbreak, the panicles became dark brown and produced chaffy grains; nearly 100% of the rice panicles in that field were severely infected. To identify the causal pathogen(s), 1g of rice grains from 20 plants with typical BPB symptoms were surface-sterilized by immersing them in 70% ethanol for a few seconds followed by sodium hypochlorite solution (3%) for 1min. The grains were then rinsed with sterilized distilled water three times. Surface-sterilized grains were then ground with a mortar and pestle; 5mL of sterile distilled water was added during grinding. The extracted suspension (20µL) was then either streaked or spread onto the selective medium (S-PG) (2). Bacterial colonies showing purple color on the S-PG medium were selected and purified as candidate pathogens. For molecular characterization, species specific primers targeting gyrB gene were used to perform PCR and resulted in 479bp as reported by (4). To verify further, the PCR products of 16SF & 16SR were amplified and sequenced partially producing around 1400bp (1) and five 16SF partial sequences were deposited into NCBI GenBank (OP108276 to OP108280). 16S rDNA and gyrB revealed almost 99% homology with Burkholderia gladioli (KU851248.1, MZ425424.1) and B. gladioli (AB220893, CP033430) respectively using BLAST analysis. These purified bacterial isolates produced a diffusible light-yellow pigment on King's B medium indicating toxoflavin production (3). The candidate five bacterial isolates were then confirmed by inoculating 10ml suspension 108CFU/mL into the panicles and sheaths of BRRIdhan28 in net house condition as described previously (1). All of the bacterial isolates obtained from the spotted rice grains produced light brown lesions on the inoculated leaf sheath as well as spotting on the grain. To fulfill Koch's postulates, the bacteria were re-isolated from the symptomatic panicles and were confirmed as B. gladioli by analyzing the sequences of gyrB and 16s rDNA genes. Taken together, these results confirmed that B. gladioli is responsible for causing BPB in the rice grain samples that we collected. To our knowledge, this is the first report of BPB caused by B. gladioli in Bangladesh and further research is necessary to develop an effective disease management technique, or else the production of rice will be severely hampered.

NITROGEN, POTASSIUM, AND SILICON FERTILIZATION TO ACHIEVE LOWER PANICLE BLAST SEVERITY AND IMPROVE YIELD COMPONENTS OF RICE USING RESPONSE SURFACE METHODOLOGY

Rice blast is one of the most critical limiting factors for rice plant growth performance, and it occurs in 85 countries, causing 10-35% grain yield losses. Several findings have indicated the positive benefits of nitrogen (N), potassium (K), and Silicon (Si) fertilization on plant development, yield, and biotic stress relief. However, due to rice blast attacks, its growth, development, and yield may be restricted or limited by insufficient or unbalanced N, K, and Si fertilizers. This study was conducted to optimize the fertilization strategies for rice panicle blast control and improve rice grain yield. The methods used were Central Composite Design and Response Surface Methodology. The application of N, K and Si did not influence the number of spikelets per meter square, filled grain (%) and 1000- grain weight (g). An increase in K and Si significantly reduced the rice blast severity in the off-season 2021 and the main-season 2021/2022. On the other hand, only Si had influenced rice grain yield production. An increase in Si showed a positive linear trend in rice grain yield. Based on these results, panicle blast disease is expected to be controlled with the recommended rate of 104 N kg/ha, 42 P2O5, 80 kg K2O, and an additional 200 Si kg/ha, which minimizes the rice blast severity (%) but at the same time maximizes the rice grain yield. The findings of this study provide a scientific base and technical advice for high-yield rice grain-growing under panicle blast disease hot spot areas.

Controlled-Release Blended Fertilizer Combined with Urea Reduces Nitrogen Losses by Runoff and Improves Nitrogen Use Efficiency and Yield of Wet Direct-Seeded Rice in Central China

Controlled-release fertilizer is one of the best fertilizer management strategies for improving the yield and nitrogen use efficiency of transplanted seedling rice. Wet direct-seeded rice has gradually replaced transplanted seedling rice since it saves labor. In addition, it is conducive to mechanization promotion. However, the effects of controlled-release fertilizers on wet direct-seeded rice remain largely unknown. A two-year field experiment aimed to compare the effects of controlled-release blended fertilizer at two rates (basal N to tiller N ratio = 7:3 (CRBF+U), CRBF alone), urea at two rates (basal–tiller ratio of 4:6 (U40), 6:4 (U60)) and a control (no N fertilizer) on the ammonia volatilization (AV) loss, nitrogen runoff loss, accumulation, transport, utilization and yield of rice. The nitrogen runoff loss in wet direct-seeded rice paddy fields was concentrated from sowing to the three-leaf and one-leaflet stage, and the loss rat was lowest after CRBF+U (11.41–12.94%). AV loss rate was lowest after CRBF (3.41%), followed by CRBF+U (3.55–3.89%). CRBF+U increased nitrogen accumulation by extending the duration of rapid nitrogen growth and accelerating maximum nitrogen growth. CRBF+U also increased the nitrogen transport rate of stems, sheaths and leaves from full heading to maturity, and intensified the increase in nitrogen in panicles, increasing the harvest index, agronomy utilization rate and apparent utilization rate of nitrogen. Finally, the grain number per panicle, seed-setting rate and actual yield of rice were significantly improved. In conclusion, CRBF+U can reduce nitrogen runoff loss and AV loss and can improve the yield and nitrogen use efficiency of wet direct-seeded rice.

Ethylene sensitivity underscores the yield advantage of high-grain numbers in cylinder-shaped rice panicles

Panicle-wise grain-filling of individual spikelets is location-specific in rice; apical spikelets dominate over their basal counterparts. This pattern of grain filling changes with panicle architecture among cultivars, but the underlying mechanisms are not understood. The newly introduced rice cultivars with cylinder-shaped panicles, although suited for high yield, exhibit several instances of poor filling. In this study shoot apical meristem gene expressions in the ontogeny stage and their influence on spikelet survival at the post-anthesis stage were elucidated by screening two types of rice Recombinant Inbreed Lines (RIL) having similar spikelet density in the cylinder-shaped panicles, such as SR-157 (low-sterile) and SR-159 (high-sterile) and their parents NPT-V12 (low-sterile) and SPS-1–6–1 (high-sterile). Between cultivars, SR-157 versus SR-159, and spikelets located apically versus basally, grain filling was more vulnerable in the latter than the former owing to a more remarkable evolution of ethylene at anthesis. Combined genome analyses revealed that branching genes like DEP2, SPL-14, PTR, and FZP over-expressed in high-sterile compared to low-sterile cultivars during the ontogeny stage. But this over-expression had no matching improvement in grain-setting in the post-anthesis stage. Grain starch synthesis was higher, and expression of ethylene receptors and signal transducer genes was lower in the low- compared to high-sterile cultivars. Thus, the quantum of grain set in the post-anthesis stage determining actual panicle yield was not dependent on the expression of genetic factors in the pre-anthesis stage defining potential grain yield. It was concluded that the default expression of ethylene synthesis and transducer genes at anthesis cause spikelet degeneration and deride the yield advantage of a high spikelet number in some cylinder-shaped rice panicles. The genomic studies controlling ethylene evolution and action in rice panicles must be an inalienable part of any constructive contribution to the yield potential.

Determination of Weed Control Efficiency of Pre-Rice Cropping Cassava/Legume Intercrops and Different Weed Management Practices in Low Land Rice at Badeggi Central Nigeria

The experiment was conducted at the lowland experimental field of National Cereals Research Institute, Badeggi. (90 45N, 600 7E, Alt, 70.57 m) in the Southern Guinea Savannah Agro-ecological zone of Nigeria in 2020-2022 cropping seasons The study was to evaluate the effect of pre-rice cropping cassava/legume intercrops and different weed management practices on weed control efficiency, growth and productivity of low land rice. The trial was conducted in two stages. The first (preceding intercropping) The treatments consisted of Mucuna puriens, Cowpea, Soybean, Lablab purpureus and Aeschynomene histrix that were intercropped with cassava (IIT 427 variety), sole cassava and natural fallow were also included as treatments. These were laid out in a Randomized Complete Block Design and replicated three times. Cassava/legume intercropping was carried out in January using residual moisture on raised beds that were prepared manually. Plot size used was 12.5 x 5 m with alley way of 0.5 m. Beds were constructed at 2.5 m long, 0.5 m wide and 0.75 m high. Planting of Cassava was done on the top sides of beds in two rows with the intra-row spacing of 0.5 (ten stands per bed) and planting of legumes were 0.5 m x 9.25 inter and intra-row spacing respectively except for soybean which was planted drilled at 5 cm intra row spacing immediately the beds were constructed. The cassava/legume cropping was harvested in August The second trial was the planting of rice on the plots previously cropped with cassava/legume intercrops. The trial was laid out in split plot design. Cassava/legume intercrop systems were allocated to the main plot, while weed management practices:- (i) Application of 4. 0 (propanil at 1.44 kg a.i. ha-1 plus 2,4 D at 0.80 kg a.i ha-1 ( Orizo plusR, at the rate of 2.24 kg a.i ha-1 at 3 weeks after transplanting (WAT) followed by hand weeding at 6 WAT (ii) two hand weedings at 3 and 6 WAT (iii) one hand weeding at 3 WAT, and (iv) weedy check were put into the sub plots with size of 12.5 x 5 m for main plots while and sub plot size was 3 x 5 m three replications. The results of treatments indicated that rice planted after cassava/Mucuna, cassava/Aeschynomene intercrops under two hand weeding and herbicide followed by one hand weeding produced lower density and dry matter. Weed control efficiency was higher in rice planted after cassava/mucuna intercrop. Weed reduction percentage range from 25-45 %, 30-50 % and 45-65 % in rice grown after cassava/legume intercrop compared to rice after fallow in 2011, 2012 and 2013 respectively. Higher rice plant height, higher number of rice tiller/stand were recorded in rice grown after cassava/Mucuna, cassava/Aeschynomene. Rice panicles per m2 and rice grain yield were increased by 72.9%, 83.6% and 84.1% in 2011, 2012 and 2013, respectively, with two hand weeding when compared with zero weeding. Rice planted after natural fallow under zero weeding produced higher weed density which resulted in poor rice performances. Rice planted after cassava Mucuna consistently controlled weed growth while cassava/cowpea and cassava Aeschynomene performed much better in rice production hence should be adopted as cropping systems for farmers

Grain yield prediction using multi-temporal UAV-based multispectral vegetation indices and endmember abundance in rice

Timely and accurately predicting grain yield before harvest is of great importance for rice production management and grain trade. Numerous methods based on remote sensing (RS) technology have explored to estimate rice grain yield. However, in most cases, these methods are negatively affected by the mixed pixels of RS images due to the effect of background and panicles. To resolve such issues, the abundance information of leaves, soil and water background and rice panicles were extracted from the multispectral images of unmanned aerial vehicle (UAV) for the multiple endmember spectral mixture analysis (MESMA) method. Based on the analysis of contribution of vegetation index (VI) and abundance (ABD) to rice grain yield, a rice grain yield prediction model was developed by combining multi-stage time-series, ABD and VI. Results showed that MESMA can mitigate endmember variability in the estimation of rice yield, and achieve higher accuracy than conventional spectral mixture analysis (SMA). The NDRE and the sum of leaf and panicle abundance (ABDL+P) can be well correlated to grain yield before heading stage (R2 = 0.75) and at heading stage (R2 = 0.72), respectively. In comparison to them, the multi-stage time-series model consisted of VI and ABD [∑(VI&ABD)] produces the highest correlation (R2 = 0.80). It could also resolve the issues about the underestimation of yield using different datasets from various multi-spectral camera in comparison to the single-parameter models ∑VI and ∑ABD, and produce the good validation accuracy with R2 = 0.73, RRMSE= 0.22 and R2 = 0.75, RRMSE= 0.15, respectively. This study suggests that the combination of UAV multi-temporal VI and ABD data can achieve accurate prediction of rice grain yield. This method effectively utilizes the optical information of leaves and rice panicles and reduces background effects, which provides a new idea for accurate rice yield prediction.

Rice DSP controls stigma, panicle and tiller primordium initiation.

Tiller and seed number are key determinants of rice (Oryza sativa) yield. These traits are mainly affected by tiller, panicle, spikelet and stigma formation, but to date, no single gene involved in the development of all these organs has been identified. Here, we found a rice mutant defective stigma and panicle (dsp) with greatly reduced numbers of tillers and panicle branches, and ovaries lacking stigmas, due to defects in primordium initiation. We cloned DSP using sequencing-based mapping and verified its function with the CRISPR/Cas9 system. DSP encodes a transcription factor containing an APETALA2/ETHYLENE RESPONSE FACTOR (AP2/ERF) domain that recognizes the GCC motif and a transcription-activating domain at the site of 244-314 that contains an angiosperm-related (AR) motif. Mutating the AR motif resulted in the dsp mutant phenotypes, whereas mutating the AP2/ERF domain led to seedling death. DSP directly regulated PINOID (PID) expression to determine the emergence of rice stigmas, and PID overexpression partially rescued the stigma defect in the dsp cr2-8 and dsp mutants. Moreover, DSP indirectly affected LAX PANICLE1 (LAX1) expression to determine tiller primordium formation and synergistically regulated panicle primordium development. Our results indicated that DSP was a key regulator that modulated different genetic pathways to control the initiation of stigma primordia, the axillary meristem formation of tillers and panicle branches, which revealed their molecular mechanisms and cross-networks, laying the vital foundation for rice yield and trait improvement.

Selection of Intermittent Irrigation to Increase Growth and Yield of Some Local Rice Varieties (Oryza sativa L.) in the Rainy Season

This study aims to examine the influence of various varieties and methods of irrigation on the response to rice growth and yield. The research was conducted in the Experimental Land of the Faculty of Agriculture, University of Muhammadiyah Yogyakarta, in January 2020. The study was conducted in the area using a factorial strip plot design in a Randomized Completely Block Design with three replications. Thirty-six experimental units were obtained. This research consists of two factors. Factor I consists of 4 methods of irrigation, namely continuous flooding, ten days flooding, six dry days, eight days flooding, eight dry days, and six days flooding, ten dry days. Factor II consists of 3 varieties: Ciherang, Cempo Hitam, and Mentik Susu. The observed parameters are the height of plants, number of tillers, leaves area, length of roots, fresh weight of plants, dry weight of plants, harvest index, panicle number, and weight of grain/ hectare. This study showed that Cempo Hitam and Mentik Susu varietas rice plants were higher, and the leaves were more expansive than the Ciherang variety. Irrigation does not affect plant height, number of tillers, leaf area, root length, or rice panicles. There is a mutual influence between variety with irrigation on the fresh and dry weight of rice plants, panicle length, harvest index, and yield per hectare of rice. A variety of Mentik Susu with conventional irrigation, ten days flooded, six days dry, six days flooded, and ten days dry, showed higher yields per hectare compared to the combination of other varieties and irrigations.

QTL-seq Identifies Genomic Regions Associated with Resistance to Dirty Panicle Disease in Rice

Dirty panicle disease is one of the most important diseases that can cause yield losses in rice production. Despite the severity of the disease, the molecular basis of resistance to the pathogen is poorly understood. Using QTL-seq with an F2 population, we identified three genomic regions on chromosomes 1, 9, and 10, namely qDP1, qDP9, and qDP10. These regions are significantly associated with resistance to dirty panicle disease caused by two fungal pathogens, Bioplaris oryzae and Cirvularia lunata. qDP1 was significantly associated only with resistance to B. oryzae, whereas qDP9 and qDP10 were significantly associated with both B. oryzae and C. lunata. We also developed KASP markers for each QTL detected and validated them in the F2 population. The markers were able to explain phenotypic variation in a range of 5.87–15.20%. Twelve potential candidate genes with annotated functions as resistance-related genes were proposed. These candidate genes include those encoding RLK, MATE, WAK, NBS-LRR, subtilisin-like protease, and ankyrin repeat proteins. The results of this study provide insights into the genetic mechanism of dirty panicles in rice and will be useful for future breeding programs for dirty panicle resistance. This is the first report of QTLs associated with resistance to dirty panicle disease in rice.

Refined feature fusion for in-field high-density and multi-scale rice panicle counting in UAV images

The yield of rice crops is strongly correlated to the number of panicles per unit area. Computer vision techniques have been utilized in previous studies to count the number of panicles automatically. However, when using images captured by Unmanned Aerial Vehicles (UAVs), the height and coverage area of the UAVs can cause shrinkage of the rice panicle objects, leading to errors in feature learning and reduced counting efficacy. In addition, there is a considerable relative size difference in rice ears, which can further affect counting accuracy. To address these issues, this paper proposes an algorithm named Refined Feature Fusion for Panicle Counting (RFF-PC). This algorithm utilizes a more refined scale division by extracting and fusing optimal features according to the object size distribution. Firstly, the number of rice ears with different sizes is quantified, and a fine division of the scale is made to calculate the receptive field size of different features that need to be fused. Secondly, multi-scale convolution generates ]features at each layer and feature pyramid fusion fuses more appropriate features at different layers to improve the ability to represent objects in complex multi-scale. Redundant information is removed through channel attention. Additionally, a refined Gaussian is used to generate ground truth close to the shape of real rice panicles. Over the UFPC2019 dataset captured at the height of 5 meters, the average counting accuracy of RFF-PC is 89.80%, and the counting accuracy only decreases from 94.33% to 90.58% over the images with an increased number of rice ears from 180 to 260, which outperforms several state-of-the-art algorithms, including MCNN, CSRNet, TasselNetV2+, DSNet, and DMCount.

Investigating the Mechanisms Underlying the Durability and Sustainable Use of Pb1 Gene-Mediated High Field Resistance to Rice Panicle Blast

Rice blast, caused by Magnaporthe oryzae, poses a significant threat to rice production. Rice blast susceptibility has been observed in Japanese rice varieties with excellent eating quality. Enhancing blast resistance is essential to ensure minimal use of agricultural chemicals. Two types of blast resistance are observed: True resistance, which is a type of qualitative resistance expressed by a major gene, and field resistance, which is a type of quantitative resistance expressed by multiple micro-acting genes. ‘Resistance collapse’, in which a variety with a true resistance gene becomes diseased by blast fungus races compatible with the resistance gene, has been observed. Varieties carrying blast-resistance genes, such as Pb1 (panicle blast resistance 1), have been developed through DNA marker-assisted selection. In this review, we focus on the Pb1, which expresses strong quantitative resistance to panicle blast and has been widely used in Japan without showing ‘resistance collapse’ for 40 years. Pb1 is an ‘adult plant resistance gene’ that does not exert strong selection pressure on the blast population during the leaf blast stage, thus preventing the selective multiplication of Pb1-compatible blast strains. This epidemiological mechanism prevents ‘resistance collapse’. Interdisciplinary research and breeding are required to sustainably use genes that induce high field resistance.