Critical Yield Components for Achieving High Grain Yield in Ratoon Rice

Critical Yield Components for Achieving High Grain Yield in Ratoon Rice | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Critical Yield Components for Achieving High Grain Yield in Ratoon Rice Hui He, Linqiong Song, Weiqin Wang, Huabin Zheng, Qiyuan Tang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4065524/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Ratoon rice is considered an eco-friendly and resource-efficient method for rice cultivation, providing innovative strategies to mitigate the global food crisis. To clarify the critical yield components for achieving high grain yield in ratoon rice, data from 136 widely cultivated rice cultivars were collected through a six-year field experiment. The study analyzed the correlations between yield components and yields for both the main season and the ratoon season, indicating that main yields vary between 5.9 and 10.9 t. ha -1 , exhibiting a highly significant positive correlation with spikelets per panicle; ratoon yields range from 1.8 to 7.1 t. ha -1 , showing a highly significant positive correlation with panicles per m², grain filling rate, and 1000-grain weight. Path analysis reveals that, in terms of contributing to ratoon yields, the grain filling rate is the most influential component, followed by panicles per m², and 1000-grain weight. Therefore, by selecting large-panicle cultivars in the main season and enhancing panicles per m², grain filling rate, and grain weight in the ratoon season, high annual yields in ratoon rice can be realized. Biological sciences/Plant sciences/Plant biotechnology/Field trials Biological sciences/Plant sciences/Plant breeding main season ratoon rice ratoon season yield components. Figures Figure 1 Figure 2 Figure 3 Introduction Rice, as one of the most critical global food crops, plays a vital role in ensuring human food security and nutritional health 1 . However, faced with challenges posed by climate change and the growth of the global population, enhancing rice yield and efficiency has become a prominent focus. In this context, ratoon rice has emerged as a sustainable agricultural practice. It utilizes the axillary buds left after the main season rice harvest to sprout new panicles, thereby yielding additional production 2,3 . This practice not only increases the annual yield per unit area but also optimizes resource utilization and reduces planting costs 4 . Rice yield is determined by its four yield components: panicles per unit land area, spikelets per panicle, grain filling rate, and grain weight. Previous research has indicated that the average main yield ranged from 8.2 to 10 t. ha − 1 . Key factors affecting the main yield include panicles per unit land area 5 and spikelets per panicle 6,7 ; spikelets per panicle and grain weight also influence the main yield 8 ; grain filling rate and grain weight are additional factors 9 . For the ratoon season, the average yield is between 2.4 and 3.3 t. ha − 1 10,11 . Critical components for ratoon yield include panicles per unit land area 8,12,13,14 ; panicles per unit land area and spikelets per panicle are also important for ratoon yield 9,16,13 ; additionally, spikelets per panicle, panicles per unit land area, and grain filling rate impact the ratoon yield 4 . Previous studies have demonstrated inconsistent insights into the determinants of ratoon rice yield and its yield components. This may be due to the limited duration, different cultivars, complex environments, etc. Hence, our study, using 136 widely cultivated rice cultivars over a six-year field experiment in the same region, aimed to obtain more comprehensive results. Aimed to decipher the relationship between the yield components and the yield in ratoon rice, as well as to assess the influence of these components on yield. These findings are instrumental in developing strategies for breeding and growing high-yielding cultivars of ratoon rice. Materials and Methods Experimental Site and Cultivars. The experiment was conducted from 2016 to 2021 in the northern region of Hunan Province, China, which has a subtropical monsoon climate with an average annual temperature of 16.1°C to 16.9°C and annual rainfall of 1230 to 1700 mm. The experimental field has moderate fertility, with convenient irrigation and drainage. In this study, a total of 136 rice cultivars were used for testing. These cultivars were extensively collected and are all approved varieties, voluntarily provided by seed companies and research institutions, which have granted us permission for their use for experimental purposes. All collected varieties comply with the relevant international, national, and/or institutional guidelines, ensuring the legality and ethical integrity of the research. A detailed list of the cultivars can be found in Appendix 1. Field Experimental Design and Agronomic Management Practice. The experimental design was a randomized block arrangement with three replications per cultivar, each plot measuring 13.4 m 2 ; sowing was done around April. For the main season, fertilization included nitrogen (N) at a total of 195 kg ha -1 , phosphorus pentoxide (P 2 O 5 ) at 90 kg ha -1 , and potassium oxide (K 2 O) at 180 kg ha -1 . The N was split into 90 kg ha -1 as base fertilizer, 70 kg ha -1 at the tillering stage, and 35 kg ha -1 as a later addition. The P was equally divided between the base and tillering stages. In the ratoon season, the N was applied at 105 kg ha -1 and the P at 27 kg ha -1 . The N was equally divided between sprouting fertilizer (20 days after the main season's panicle initiation) and seedling fertilizer, with all the P applied as seedling fertilizer. At the maturity of the main season, manual harvesting was done by variety with a stubble height of 30 cm. Within three days after harvesting, shallow water irrigation was combined with the application of seedling fertilizer for the ratoon season. Throughout the growth stage, local high-yield rice cultivation techniques were used for the control of diseases and pests like rice blast and leaf folder. Observation Indexes and Methods . All crops were manually harvested and sun-dried for yield calculation. Ten rice plant samples were collected to determine yield components. Statistical Analysis. The yield and yield components data were calculated, processed, and graphically represented using Excel 2010. Path analysis was conducted using DPS, and correlation analysis was performed using SPSS 26. Results Following a six-year field experiment, an analysis of data from 136 samples was conducted. The main yields ranged from 5.9 to 10.9 t. ha − 1 , with an average of 8.73 t. ha − 1 (Fig. 1 A); panicles per m² ranged from 154 to 350, averaging 237.7 (Fig. 2 A); spikelets per panicle varied from 90 to 266, with an average of 169.7 (Fig. 2 B); grain filling rate ranged from 67.3–98.8%, with an average of 83.6% (Fig. 2 C); 1000-grain weight ranged from 15.7 to 28.8 g, with an average of 23.2 g (Fig. 2 D). The ratoon yields were 1.8–7.1 t. ha − 1 , with an average of 4.7 t. ha − 1 (Fig. 1 B); panicles per m² ranged from 136 to 587.3, averaging 333.9 (Fig. 2 E); spikelets per panicle varied from 22 to 123, with an average of 66.0 (Fig. 2 F); grain filling rate ranged from 31.6–94.9%, averaging 70.3% (Fig. 2 G); 1000-grain weight ranged from 13.7 to 27.2 g, with an average of 22.1 g (Fig. 2 H). In the main season, only panicles per m² showed a highly significant positive correlation with the main yield (P < 0.01) (Fig. 3 A-D). Path analysis (Table 1 ) revealed that spikelets per panicle had the largest direct positive contribution to the main yield (1.075), and even after offsetting by the indirect contributions of the other three yield components, the total contribution remained the highest (0.518). Although panicles per m² had a direct positive contribution to the main yield of 0.620, it was almost offset by the indirect contribution of spikelets per panicle, resulting in a lower total contribution. In the ratoon season, panicles per m², grain filling rate, and 1000-grain weight all showed a highly significant positive correlation with yield (P panicles per m² (0.374) > grain filling rate (0.278). However, the negative indirect contribution of panicles per m² offset part of the positive direct contribution of 1000-grain weight to the ratoon yield, while grain filling rate had positive indirect contributions both to and from panicles per m², resulting in total contributions of grain filling rate (0.432) > panicles per m² (0.417) > 1000-grain weight (0.341), aligning with the correlation analysis (Fig. 3 E-H). Table 1 Contributions of yield components to the main yield and ratoon yield Yield (t. ha − 1 ) Yield components Direct contribution Indirect Contribution via X i (i = 1, 2, 3, 4) Total contribution X 1 X 2 X 3 X 4 Main yield X 1 0.620 -0.611 0.082 -0.104 -0.013 X 1.075 -0.352 -0.138 -0.068 0.518 X 3 0.311 0.164 -0.476 -0.025 -0.027 X 4 0.386 -0.167 -0.188 -0.020 0.010 Ratoon yield X 1 0.374 -0.014 0.124 -0.067 0.417 X 0.034 -0.154 -0.038 0.045 -0.114 X 3 0.278 0.167 -0.005 -0.009 0.432 X 4 0.405 -0.062 0.004 -0.006 0.341 The factors X 1 , X 2 , X 3 , and X 4 correspond to panicles per m², spikelets per panicle, grain filling rate, and 1000-grain weight, in that order. Discussion A six-year field experiment involving 136 cultivars of ratoon rice has revealed essential characteristics of their yields. The average yield of the main season stands at 8.73 t. ha − 1 , aligning with the outcomes of prior studies 11,15 . It indicates that under existing cultivars and cultivation methods, the main yield has reached a stable level. The average yield of the ratoon yield was 4.7 t. ha − 1 , higher than the previously reported average of 2.4 to 3.3 t. ha − 1 15,11 . This can be attributed to the use of a high-yield culture technique which ensured high and stable yields in the ratoon season 16 . This research corroborates that spikelets per panicle were the critical component for the main yield, in agreement with certain studies 8,18 . To improve the main yield, prioritizing the selection and cultivation of large-panicle cultivars is imperative, as these can produce a greater number of grains and thus significantly enhance the main yield 18,19 . Correlation and path analyses indicated a complex relationship between yield and yield components in the ratoon season, with panicles per m², grain filling rate, and 1000-grain weight showing significant positive correlations with the ratoon yield, differing from previous studies 5,7,13 . Their results showed that the panicles per unit land area [ 8 ], panicles per unit land area and spikelets per panicle 13 , spikelets per panicle, panicles per unit land area, and grain filling rate 7 were the critical components for the ratoon yield. This variation can be attributed to our study's use of 136 widely cultivated rice cultivars over a six-year field experiment in the same region, obtaining more comprehensive results. To achieve high yields in the ratoon season, it is crucial to enhance the panicles per unit area, grain filling rate, and grain weight. Previous research has shown that the main factors influencing the panicles per unit area of the ratoon season include variety type 17 , nutrient management 5,20 , different stubble heights 10,21 , and mechanical compression 22 . To increase the panicles per unit area in the ratoon season, two approaches can be adopted: firstly, selecting varieties with strong regenerative capacity 13 ; secondly, implementing effective cultivation measures, including reduced mechanical compression during the main season's rice harvest 23 ; and timely application of sprout-promoting fertilizer 9 . The heading and grain filling stages are critical periods affecting the grain filling rate and grain weight of the ratoon season. Over 70% of rice yield is derived from dry matter accumulated through leaf photosynthesis during this period 24,25 . Temperature 26 and water management 27 are key factors in the accumulation and transportation of dry matter during those periods, affecting the grain filling rate and grain weight. High temperature reduces the rate of dry matter transport to the panicle, decreasing the accumulation of dry matter in the panicle and thus lowering the grain filling rate 28 . Alternate wetting and drying irrigation can significantly increase the grain filling rate and shorten the grain filling period 29 . This is particularly important for improving the grain weight and uniformity of grain filling in ratoon rice. Moreover, efficient water management can increase grain weigh 30,31 . Therefore, to enhance the grain filling rate and grain weight of the ratoon season, strategies such as water management and avoiding damage from low temperatures during the heading and grain filling stages of ratoon rice can be adopted to promote substance transport. Conclusions In summary, by suggesting a combination of breeding and cultivation measures, selecting large-panicle cultivars for high yield in the main season and pairing them with agronomic measures, higher panicles per unit area, grain filling rate, and grain weight can be achieved in the ratoon season, thereby realizing a high annual yield. Declarations Acknowledgments: Authors gratefully acknowledge the help of anonymous reviewers for improving this article. Author Contributions: H.H., H.B. have made substantial contributions to the conception, design of the work, drafting the work, revising it critically for important intellectual content. L.Q., W.Q. and Q.Y. contributed to the acquisition, analysis, and interpretation of data for the work. H.B. contributed to the agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors have read and agreed to the published version of the manuscript. Data Availability Statement: All obtained data is enclosed with this manuscript [and its supplementary information files]. Institutional Review Board Statement: Not applicable. Conflicts of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict. Funding: The study was financially supported by the Earmarked Fund for China Agriculture Research System (CARS-01-27); scientific research fund of Hunan provincial education department (22B0202); the science and technology innovation Program of Hunan Province (2023NK2003). Informed Consent Statement: Not applicable. References Huang, M., Yang, L., Qin H.D., Jiang, L.G. & Zou, Y.B. Quantifying the effect of biochar amendment on soil quality and crop productivity in Chinese rice paddies. Field Crops Res. 154 , 172-177 (2013). 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Supplementary Files Appendix1.docx Cite Share Download PDF Status: Published Journal Publication published 05 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 20 Jun, 2024 Reviews received at journal 19 Jun, 2024 Reviews received at journal 28 May, 2024 Reviewers agreed at journal 19 May, 2024 Reviewers agreed at journal 17 May, 2024 Reviewers invited by journal 17 May, 2024 Editor assigned by journal 17 May, 2024 Editor invited by journal 22 Mar, 2024 Submission checks completed at journal 21 Mar, 2024 First submitted to journal 10 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4065524","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":282670415,"identity":"0ee4e924-702a-4e4b-bb9f-b398ffefe005","order_by":0,"name":"Hui He","email":"","orcid":"","institution":"Hunan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"He","suffix":""},{"id":282670416,"identity":"c25f706a-4365-47d5-b14d-2be2d046ff09","order_by":1,"name":"Linqiong Song","email":"","orcid":"","institution":"Hunan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Linqiong","middleName":"","lastName":"Song","suffix":""},{"id":282670417,"identity":"55abaec0-2f29-482d-b870-cc8b408006e4","order_by":2,"name":"Weiqin Wang","email":"","orcid":"","institution":"Hunan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Weiqin","middleName":"","lastName":"Wang","suffix":""},{"id":282670418,"identity":"c7b4d565-f32d-4152-a45a-930a107a3937","order_by":3,"name":"Huabin Zheng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACAwkGNhAtZwAVYGwgVosx6VoSNxCtxVy6/dmDjztq07dL5B78zMNgI7vhAPOzB/i0WM45kG4488zx3J0z8pKleRjSjDccYDM3wKfF4EbCMWnetmO5G27kGAC1HE7ccICHTQK/lsQ26b9tx9INbuQY/+Zh+E+MlmQ2aca2mgSgFjOgLQeI0HLnGJtkb9sBww1n3phZzjFINp55mM0Mv5bb7c8kfrbVyRsczzG+8abCTrbvePMzvFqg4DDMBCBmJkI9ENQRp2wUjIJRMApGJgAAHcVLZXr4mC0AAAAASUVORK5CYII=","orcid":"","institution":"Hunan Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Huabin","middleName":"","lastName":"Zheng","suffix":""},{"id":282670419,"identity":"18645217-c79c-464e-be4f-46964c0b18ef","order_by":4,"name":"Qiyuan Tang","email":"","orcid":"","institution":"Hunan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Qiyuan","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2024-03-10 14:17:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4065524/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4065524/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-74836-0","type":"published","date":"2024-10-05T15:57:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53382283,"identity":"85d1758b-5497-441b-acab-e9a26a740ee5","added_by":"auto","created_at":"2024-03-25 10:22:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":168910,"visible":true,"origin":"","legend":"\u003cp\u003eMain yield (A) and ratoon yield (B). The dashed line horizontally displayed indicates the mean value of the dataset. The smaller figure embedded within illustrates a frequency distribution histogram of the data.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4065524/v1/b44af2bf9e9f0e9107d43d08.png"},{"id":53382280,"identity":"05970e8c-0938-4388-9608-7f97b125e575","added_by":"auto","created_at":"2024-03-25 10:22:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":257273,"visible":true,"origin":"","legend":"\u003cp\u003eThe main yield to panicles per m² (A), spikelets per panicle (B), grain filling rate (C), and 1000-grain weight (D); the ratoon yield to panicles per m² (E), spikelets per panicle (F), grain filling rate (G), and 1000-grain weight (H), spikelets per panicle (F), spikelets per panicle (F), grain filling rate (G), and 1000-grain weight (H). In the box-and-whisker plots, the highest value is represented by the topmost point of the vertical line, the 75th percentile by the upper boundary of the box, the mean by a square inside the box, the 25th percentile by the lower boundary of the box, and the lowest value by the bottommost point of the vertical line.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4065524/v1/30f039b0d23b34aca2142fcb.png"},{"id":53382279,"identity":"40dbdfe2-b217-4995-8d90-0012edfda263","added_by":"auto","created_at":"2024-03-25 10:22:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":729514,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships of the main yield to panicles per m² (A), spikelets per panicle (B), grain filling rate (C), and 1000-grain weight (D); relationships of the ratoon yield to panicles per m² (E), spikelets per panicle (F), grain filling rate (G), and 1000-grain weight (H).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4065524/v1/b341241b148ca5e780f77507.png"},{"id":66096727,"identity":"73df2a4c-7145-41bb-adbd-a63078796438","added_by":"auto","created_at":"2024-10-07 16:08:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1478350,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4065524/v1/00c067c8-9f88-40d9-b3a4-0c95f79050d1.pdf"},{"id":53382281,"identity":"e005b51f-bbeb-447d-8841-d6d2c4c87e66","added_by":"auto","created_at":"2024-03-25 10:22:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33444,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4065524/v1/1cb4987253c6ec9f388c349c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Critical Yield Components for Achieving High Grain Yield in Ratoon Rice","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRice, as one of the most critical global food crops, plays a vital role in ensuring human food security and nutritional health\u003csup\u003e1\u003c/sup\u003e. However, faced with challenges posed by climate change and the growth of the global population, enhancing rice yield and efficiency has become a prominent focus. In this context, ratoon rice has emerged as a sustainable agricultural practice. It utilizes the axillary buds left after the main season rice harvest to sprout new panicles, thereby yielding additional production\u003csup\u003e2,3\u003c/sup\u003e. This practice not only increases the annual yield per unit area but also optimizes resource utilization and reduces planting costs\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRice yield is determined by its four yield components: panicles per unit land area, spikelets per panicle, grain filling rate, and grain weight. Previous research has indicated that the average main yield ranged from 8.2 to 10 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Key factors affecting the main yield include panicles per unit land area\u003csup\u003e5\u003c/sup\u003e and spikelets per panicle\u003csup\u003e6,7\u003c/sup\u003e; spikelets per panicle and grain weight also influence the main yield\u003csup\u003e8\u003c/sup\u003e; grain filling rate and grain weight are additional factors\u003csup\u003e9\u003c/sup\u003e. For the ratoon season, the average yield is between 2.4 and 3.3 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1 10,11\u003c/sup\u003e. Critical components for ratoon yield include panicles per unit land area\u003csup\u003e8,12,13,14\u003c/sup\u003e; panicles per unit land area and spikelets per panicle are also important for ratoon yield\u003csup\u003e9,16,13\u003c/sup\u003e; additionally, spikelets per panicle, panicles per unit land area, and grain filling rate impact the ratoon yield\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrevious studies have demonstrated inconsistent insights into the determinants of ratoon rice yield and its yield components. This may be due to the limited duration, different cultivars, complex environments, etc. Hence, our study, using 136 widely cultivated rice cultivars over a six-year field experiment in the same region, aimed to obtain more comprehensive results. Aimed to decipher the relationship between the yield components and the yield in ratoon rice, as well as to assess the influence of these components on yield. These findings are instrumental in developing strategies for breeding and growing high-yielding cultivars of ratoon rice.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cb\u003eExperimental Site and Cultivars.\u003c/b\u003e The experiment was conducted from 2016 to 2021 in the northern region of Hunan Province, China, which has a subtropical monsoon climate with an average annual temperature of 16.1\u0026deg;C to 16.9\u0026deg;C and annual rainfall of 1230 to 1700 mm. The experimental field has moderate fertility, with convenient irrigation and drainage. In this study, a total of 136 rice cultivars were used for testing. These cultivars were extensively collected and are all approved varieties, voluntarily provided by seed companies and research institutions, which have granted us permission for their use for experimental purposes. All collected varieties comply with the relevant international, national, and/or institutional guidelines, ensuring the legality and ethical integrity of the research. A detailed list of the cultivars can be found in Appendix 1.\u003c/p\u003e \u003cp\u003e \u003cb\u003eField Experimental Design and Agronomic Management Practice.\u003c/b\u003e The experimental design was a randomized block arrangement with three replications per cultivar, each plot measuring 13.4 m\u003csup\u003e2\u003c/sup\u003e; sowing was done around April. For the main season, fertilization included nitrogen (N) at a total of 195 kg ha\u003csup\u003e-1\u003c/sup\u003e, phosphorus pentoxide (P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e) at 90 kg ha\u003csup\u003e-1\u003c/sup\u003e, and potassium oxide (K\u003csub\u003e2\u003c/sub\u003eO) at 180 kg ha\u003csup\u003e-1\u003c/sup\u003e. The N was split into 90 kg ha\u003csup\u003e-1\u003c/sup\u003e as base fertilizer, 70 kg ha\u003csup\u003e-1\u003c/sup\u003e at the tillering stage, and 35 kg ha\u003csup\u003e-1\u003c/sup\u003e as a later addition. The P was equally divided between the base and tillering stages. In the ratoon season, the N was applied at 105 kg ha\u003csup\u003e-1\u003c/sup\u003e and the P at 27 kg ha\u003csup\u003e-1\u003c/sup\u003e. The N was equally divided between sprouting fertilizer (20 days after the main season's panicle initiation) and seedling fertilizer, with all the P applied as seedling fertilizer.\u003c/p\u003e \u003cp\u003eAt the maturity of the main season, manual harvesting was done by variety with a stubble height of 30 cm. Within three days after harvesting, shallow water irrigation was combined with the application of seedling fertilizer for the ratoon season. Throughout the growth stage, local high-yield rice cultivation techniques were used for the control of diseases and pests like rice blast and leaf folder.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObservation Indexes and Methods\u003c/b\u003e. All crops were manually harvested and sun-dried for yield calculation. Ten rice plant samples were collected to determine yield components.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical Analysis.\u003c/b\u003e The yield and yield components data were calculated, processed, and graphically represented using Excel 2010. Path analysis was conducted using DPS, and correlation analysis was performed using SPSS 26.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFollowing a six-year field experiment, an analysis of data from 136 samples was conducted. The main yields ranged from 5.9 to 10.9 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with an average of 8.73 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA); panicles per m\u0026sup2; ranged from 154 to 350, averaging 237.7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA); spikelets per panicle varied from 90 to 266, with an average of 169.7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB); grain filling rate ranged from 67.3\u0026ndash;98.8%, with an average of 83.6% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC); 1000-grain weight ranged from 15.7 to 28.8 g, with an average of 23.2 g (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The ratoon yields were 1.8\u0026ndash;7.1 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with an average of 4.7 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB); panicles per m\u0026sup2; ranged from 136 to 587.3, averaging 333.9 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE); spikelets per panicle varied from 22 to 123, with an average of 66.0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF); grain filling rate ranged from 31.6\u0026ndash;94.9%, averaging 70.3% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG); 1000-grain weight ranged from 13.7 to 27.2 g, with an average of 22.1 g (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the main season, only panicles per m\u0026sup2; showed a highly significant positive correlation with the main yield (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-D). Path analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed that spikelets per panicle had the largest direct positive contribution to the main yield (1.075), and even after offsetting by the indirect contributions of the other three yield components, the total contribution remained the highest (0.518). Although panicles per m\u0026sup2; had a direct positive contribution to the main yield of 0.620, it was almost offset by the indirect contribution of spikelets per panicle, resulting in a lower total contribution. In the ratoon season, panicles per m\u0026sup2;, grain filling rate, and 1000-grain weight all showed a highly significant positive correlation with yield (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-H). Path analysis revealed that the direct contributions of yield components to the ratoon yield were 1000-grain weight (0.405)\u0026thinsp;\u0026gt;\u0026thinsp;panicles per m\u0026sup2; (0.374)\u0026thinsp;\u0026gt;\u0026thinsp;grain filling rate (0.278). However, the negative indirect contribution of panicles per m\u0026sup2; offset part of the positive direct contribution of 1000-grain weight to the ratoon yield, while grain filling rate had positive indirect contributions both to and from panicles per m\u0026sup2;, resulting in total contributions of grain filling rate (0.432)\u0026thinsp;\u0026gt;\u0026thinsp;panicles per m\u0026sup2; (0.417)\u0026thinsp;\u0026gt;\u0026thinsp;1000-grain weight (0.341), aligning with the correlation analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-H).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eContributions of yield components to the main yield and ratoon yield\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYield \u003c/p\u003e \u003cp\u003e(t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYield components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDirect contribution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eIndirect Contribution via X\u003csub\u003ei\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(i\u0026thinsp;=\u0026thinsp;1, 2, 3, 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal contribution\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eX\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eX\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eX\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMain\u003c/p\u003e \u003cp\u003eyield\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRatoon yield\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eThe factors X\u003csub\u003e1\u003c/sub\u003e, X\u003csub\u003e2\u003c/sub\u003e, X\u003csub\u003e3\u003c/sub\u003e, and X\u003csub\u003e4\u003c/sub\u003e correspond to panicles per m\u0026sup2;, spikelets per panicle, grain filling rate, and 1000-grain weight, in that order.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA six-year field experiment involving 136 cultivars of ratoon rice has revealed essential characteristics of their yields. The average yield of the main season stands at 8.73 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, aligning with the outcomes of prior studies\u003csup\u003e11,15\u003c/sup\u003e. It indicates that under existing cultivars and cultivation methods, the main yield has reached a stable level. The average yield of the ratoon yield was 4.7 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, higher than the previously reported average of 2.4 to 3.3 t. ha\u003csup\u003e\u0026minus;\u0026thinsp;1 15,11\u003c/sup\u003e. This can be attributed to the use of a high-yield culture technique which ensured high and stable yields in the ratoon season\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis research corroborates that spikelets per panicle were the critical component for the main yield, in agreement with certain studies\u003csup\u003e8,18\u003c/sup\u003e. To improve the main yield, prioritizing the selection and cultivation of large-panicle cultivars is imperative, as these can produce a greater number of grains and thus significantly enhance the main yield\u003csup\u003e18,19\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCorrelation and path analyses indicated a complex relationship between yield and yield components in the ratoon season, with panicles per m\u0026sup2;, grain filling rate, and 1000-grain weight showing significant positive correlations with the ratoon yield, differing from previous studies\u003csup\u003e5,7,13\u003c/sup\u003e. Their results showed that the panicles per unit land area [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], panicles per unit land area and spikelets per panicle\u003csup\u003e13\u003c/sup\u003e, spikelets per panicle, panicles per unit land area, and grain filling rate\u003csup\u003e7\u003c/sup\u003e were the critical components for the ratoon yield. This variation can be attributed to our study's use of 136 widely cultivated rice cultivars over a six-year field experiment in the same region, obtaining more comprehensive results. To achieve high yields in the ratoon season, it is crucial to enhance the panicles per unit area, grain filling rate, and grain weight.\u003c/p\u003e \u003cp\u003ePrevious research has shown that the main factors influencing the panicles per unit area of the ratoon season include variety type\u003csup\u003e17\u003c/sup\u003e, nutrient management\u003csup\u003e5,20\u003c/sup\u003e, different stubble heights\u003csup\u003e10,21\u003c/sup\u003e, and mechanical compression\u003csup\u003e22\u003c/sup\u003e. To increase the panicles per unit area in the ratoon season, two approaches can be adopted: firstly, selecting varieties with strong regenerative capacity\u003csup\u003e13\u003c/sup\u003e; secondly, implementing effective cultivation measures, including reduced mechanical compression during the main season's rice harvest\u003csup\u003e23\u003c/sup\u003e; and timely application of sprout-promoting fertilizer\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe heading and grain filling stages are critical periods affecting the grain filling rate and grain weight of the ratoon season. Over 70% of rice yield is derived from dry matter accumulated through leaf photosynthesis during this period\u003csup\u003e24,25\u003c/sup\u003e. Temperature\u003csup\u003e26\u003c/sup\u003e and water management\u003csup\u003e27\u003c/sup\u003e are key factors in the accumulation and transportation of dry matter during those periods, affecting the grain filling rate and grain weight. High temperature reduces the rate of dry matter transport to the panicle, decreasing the accumulation of dry matter in the panicle and thus lowering the grain filling rate\u003csup\u003e28\u003c/sup\u003e. Alternate wetting and drying irrigation can significantly increase the grain filling rate and shorten the grain filling period\u003csup\u003e29\u003c/sup\u003e. This is particularly important for improving the grain weight and uniformity of grain filling in ratoon rice. Moreover, efficient water management can increase grain weigh\u003csup\u003e30,31\u003c/sup\u003e. Therefore, to enhance the grain filling rate and grain weight of the ratoon season, strategies such as water management and avoiding damage from low temperatures during the heading and grain filling stages of ratoon rice can be adopted to promote substance transport.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, by suggesting a combination of breeding and cultivation measures, selecting large-panicle cultivars for high yield in the main season and pairing them with agronomic measures, higher panicles per unit area, grain filling rate, and grain weight can be achieved in the ratoon season, thereby realizing a high annual yield.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e Authors gratefully acknowledge the help of anonymous reviewers for improving this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e H.H., H.B. have made substantial contributions to the conception, design of the work, drafting the work, revising it critically for important intellectual content. L.Q., W.Q. and Q.Y. contributed to the acquisition, analysis, and interpretation of data for the work. H.B. contributed to the agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors have read and agreed to the published version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e All obtained data is enclosed with this manuscript [and its supplementary\u003c/p\u003e\n\u003cp\u003einformation files].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The study was financially supported by the Earmarked Fund for China Agriculture Research System (CARS-01-27); scientific research fund of Hunan provincial education department (22B0202); the science and technology innovation Program of Hunan Province (2023NK2003).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHuang, M., Yang, L., Qin H.D., Jiang, L.G. \u0026amp; Zou, Y.B. 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Reflection on China\u0026rsquo;s rice production strategies during the transition period. \u003cem\u003eSci. Sin. (Vit.)\u003c/em\u003e. \u003cstrong\u003e44\u003c/strong\u003e, 845-850 (2014).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWang, E.T., Wang, J.J, Zhu, X.D, Hao, W., Wang, LY., Li, Q., Zhang, L.X., He, W., Lu, B.R., Lin, H.X., Ma, H., Zhang, G.Q. \u0026amp; He, Z. Control of rice grain-filling and yield by a gene with a potential signature of domestication. \u003cem\u003eNat. gene.\u003c/em\u003e\u003cstrong\u003e4\u003c/strong\u003e, 1370-1374 (2008).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHuang, J.W., Pan, Y.P., Chen, H.F., Zhang, Z.X., Fang, C.X., Shao, C.H., Amjad, H., Lin, W.W. \u0026amp; Lin, W.X. Physiochemical mechanisms involved in the improvement of grain-filling, rice quality mediated by related enzyme activities in the ratoon cultivation system. \u003cem\u003eField Crops Res.\u003c/em\u003e\u003cstrong\u003e258\u003c/strong\u003e, 107962 (2020).\u003c/li\u003e\n \u003cli\u003eYuan, M.M., Zhu, J.G., Sun, Y.X., Wang, W.L. \u0026amp; Liu, G. Elevated CO\u003csub\u003e2\u003c/sub\u003e concentration elevated temperature rice yield grain position grain plumpness.\u003cem\u003e\u0026nbsp;J. Agro. Environ. Sci.\u0026nbsp;\u003c/em\u003e38 (2019).\u003c/li\u003e\n \u003cli\u003eCai, Q.H., Lin, Q., Zhu, Y.S., Xie, Z.X., Chen, L.J., Xie, H.A., Jiang, Z.W. \u0026amp;Zhang, J.F. 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Food Syst.\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e6\u003c/strong\u003e, 802267 (2022).\u003c/li\u003e\n \u003cli\u003eZheng, C., Wang, Y., Yuan, S., Xiao, S., Sun, Y., Huang, J.\u0026nbsp;\u0026amp; Peng, S. Heavy soil drying during mid\u0026ndash;to\u0026ndash;late grain filling stage of the main crop to reduce yield loss of the ratoon crop in a mechanized rice ratooning system. \u003cem\u003eCrop J.\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e10\u003c/strong\u003e, 280\u0026ndash;285 (2021).\u003c/li\u003e\n \u003cli\u003eNatalia, S. A., Negishi, H.\u0026nbsp;\u0026amp; Shiotsu, F. Effects of Different Water Managements on Grain Yield and Grain Quality in Ratoon Rice Cultivation. \u003cem\u003eOpen Agric. J.\u003c/em\u003e\u003cstrong\u003e17\u003c/strong\u003e, 1874-3315 (2023).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"main season, ratoon rice, ratoon season, yield components.","lastPublishedDoi":"10.21203/rs.3.rs-4065524/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4065524/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRatoon rice is considered an eco-friendly and resource-efficient method for rice cultivation, providing innovative strategies to mitigate the global food crisis. To clarify the critical yield components for achieving high grain yield in ratoon rice, data from 136 widely cultivated rice cultivars were collected through a six-year field experiment. The study analyzed the correlations between yield components and yields for both the main season and the ratoon season, indicating that main yields vary between 5.9 and 10.9 t. ha\u003csup\u003e-1\u003c/sup\u003e, exhibiting a highly significant positive correlation with spikelets per panicle; ratoon yields range from 1.8 to 7.1 t. ha\u003csup\u003e-1\u003c/sup\u003e, showing a highly significant positive correlation with panicles per m², grain filling rate, and 1000-grain weight. Path analysis reveals that, in terms of contributing to ratoon yields, the grain filling rate is the most influential component, followed by panicles per m², and 1000-grain weight. Therefore, by selecting large-panicle cultivars in the main season and enhancing panicles per m², grain filling rate, and grain weight in the ratoon season, high annual yields in ratoon rice can be realized.\u003c/p\u003e","manuscriptTitle":"Critical Yield Components for Achieving High Grain Yield in Ratoon Rice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-25 10:22:13","doi":"10.21203/rs.3.rs-4065524/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-20T15:38:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-20T00:28:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-28T22:57:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"281979399689649702087282831151744842245","date":"2024-05-19T21:15:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167422350757139101222124995274891553397","date":"2024-05-17T22:18:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-17T12:26:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-17T11:45:58+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-22T10:30:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-21T08:58:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-03-10T13:34:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0cb3b08f-d7fa-4b58-81d9-998a8021e2ff","owner":[],"postedDate":"March 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":29763128,"name":"Biological sciences/Plant sciences/Plant biotechnology/Field trials"},{"id":29763129,"name":"Biological sciences/Plant sciences/Plant breeding"}],"tags":[],"updatedAt":"2024-10-07T15:59:26+00:00","versionOfRecord":{"articleIdentity":"rs-4065524","link":"https://doi.org/10.1038/s41598-024-74836-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-05 15:57:02","publishedOnDateReadable":"October 5th, 2024"},"versionCreatedAt":"2024-03-25 10:22:13","video":"","vorDoi":"10.1038/s41598-024-74836-0","vorDoiUrl":"https://doi.org/10.1038/s41598-024-74836-0","workflowStages":[]},"version":"v1","identity":"rs-4065524","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4065524","identity":"rs-4065524","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}