Rice Science最新文献

英文中文

Identification of Germplasm with High Ratooning Ability and Genetic Analysis of Ratooning Ability in Rice 水稻高再生能力种质的鉴定及再生能力的遗传分析

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.06.006

Shouwu YU , Yujun XIE , Gengsheng TANG , Meizhen LI , Linyou WANG , Yifeng HUANG , Jinsong BAO

引用次数: 0

Enhanced Chlorophyll Accumulation is Early Response of Rice to Phosphorus Deficiency 叶绿素积累增强是水稻对缺磷的早期响应

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.08.004

Pattanapong Jaisue , Chalongrat Daengngam , Panuwat Pengphorm , Surapa Nutthapornnitchakul , Sompop Pinit , Lompong Klinnawee

Phosphorus (P) deficiency is a major constraint in rice production, causing significant reductions in growth and yield. While P deficiency typically decreases chlorophyll content in many plant species, our previous studies revealed an unexpected increase in chlorophyll content in P-deficient rice seedlings. Here, we investigated this phenomenon in KDML105 rice under various P regimes and analyzed the physiological mechanisms involved. We found that P-deficient rice seedlings significantly increased chlorophyll a, chlorophyll b, and carotenoid contents in young leaves while reducing photosystem II quantum yield and enhancing non-photochemical quenching. This response was specific to P deficiency and was not observed under other stress conditions such as salinity or copper toxicity, which induced oxidative stress. Time-course experiments revealed that increased chlorophyll accumulation was an early adaptive response that occurred primarily in young leaves, while older leaves eventually developed chlorosis under prolonged P deficiency. The increased chlorophyll content may be attributed to reduced leaf width and altered leaf morphology under P-limited conditions. Furthermore, using custom hyperspectral imaging analysis coupled with machine learning classification, we successfully differentiated P status in rice leaves with 98.96% accuracy in older leaves. This study demonstrates that enhanced chlorophyll accumulation is a characteristic early response to P deficiency in rice, rather than a typical general stress response observed in other conditions. Our findings highlight the limitations of relying solely on chlorophyll-based indices as indicators of plant health in precision agriculture, especially regarding phosphorus (P) nutrition management. This underscores the need for a more comprehensive approach and lays the groundwork for developing advanced remote sensing technologies aimed at accurately assessing P status in rice cultivation.

磷(P)缺乏是制约水稻生产的主要因素，造成水稻生长和产量的显著下降。虽然磷缺乏通常会降低许多植物物种的叶绿素含量，但我们之前的研究显示，缺磷水稻幼苗的叶绿素含量出乎意料地增加。本文研究了不同施磷水平下KDML105水稻的这一现象，并分析了其中的生理机制。我们发现缺磷水稻幼苗显著增加了幼叶叶绿素a、叶绿素b和类胡萝卜素含量，同时降低了光系统II量子产量，增强了非光化学猝灭。这种反应是磷缺乏所特有的，而在其他胁迫条件下，如盐或铜中毒，诱导氧化应激没有观察到。时间过程试验表明，叶绿素积累的增加主要发生在幼叶中，而在长期缺磷条件下，老叶最终发生黄化。叶绿素含量的增加可能与限磷条件下叶片宽度的减小和叶片形态的改变有关。此外，利用自定义高光谱成像分析与机器学习分类相结合，我们成功地以98.96%的准确率区分了水稻叶片中P的状态。本研究表明叶绿素积累增强是水稻对缺磷的特征性早期反应，而不是在其他条件下观察到的典型的一般胁迫反应。我们的研究结果强调了在精准农业中仅依赖基于叶绿素的指标作为植物健康指标的局限性，特别是在磷营养管理方面。这强调了需要一种更全面的方法，并为开发旨在准确评估水稻种植中磷状况的先进遥感技术奠定了基础。

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引用次数: 0

Physical and Physicochemical Classification of Parboiled Rice Using VNIR-SWIR Spectroscopy and Machine Learning 利用VNIR-SWIR光谱和机器学习对煮熟大米进行物理和物理化学分类

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.08.007

Nairiane dos Santos Bilhalva , Paulo Carteri Coradi , Rosana Santos de Moraes , Dthenifer Cordeiro Santana , Larissa Ribeiro Teodoro , Paulo Eduardo Teodoro , Marisa Menezes Leal

The classification of parboiled rice into types can be optimized through the use of machine learning (ML) algorithms, resulting in greater speed and accuracy in data processing. The objectives of this study were: (i) to investigate the spectral behavior of different types of parboiled rice (Types 1–5 and Off-type); (ii) to identify the most effective ML algorithm for classifying parboiled rice types; (iii) to determine the best kernel configuration and preprocessing methods for spectral data; and (iv) to recommend a protocol for implementing this technique in the rice storage industry. Samples were selected based on the maximum defect limits tolerated for each type, according to the Technical Rice Regulation. Spectral data were acquired using a spectroradiometer in the range of 350–2500 nm and subsequently processed with different methods, including baseline correction, standard normal variate, multiplicative scattering correction, combinations of these techniques with Savitzky-Golay smoothing, and the application of the first derivative of Savitzky-Golay smoothing. The data were analyzed using six different ML algorithms: Artificial Neural Network, Decision Tree, Logistic Regression, REPTree, Random Forest, and Support Vector Machine. Rice types were treated as output variables, while spectral features served as input variables. Logistic Regression and Support Vector Machine algorithms showed the best classification performance, with accuracy rates above 97%, F-scores around 0.98, and Kappa values exceeding 0.97. Spectral preprocessing did not yield substantial improvements and incurred high computational costs; therefore, using raw data was a viable and efficient alternative. For practical implementation in the rice storage industry, we recommend acquiring a VNIR-SWIR (visible near-infrared and shortwave infrared) hyperspectral sensor (350–2500 nm) and developing a classification model based on the Support Vector Machine algorithm with a linear kernel trained on representative local samples. Additionally, we recommend implementing an automated real-time classification system, a representative sample collection protocol, and detailed reporting for inventory and logistics optimization.

通过使用机器学习（ML）算法，可以优化半熟米饭的分类，从而提高数据处理的速度和准确性。本研究的目的是：(i)研究不同类型的半熟大米（1-5型和off型）的光谱行为；（ii）找出最有效的机器学习算法来分类煮熟的米饭种类；（iii）确定光谱数据的最佳核配置和预处理方法；（iv）建议在大米储存行业实施该技术的协议。根据《水稻技术条例》的规定，样品的选择是基于每种类型的最大缺陷容忍限度。利用光谱辐射计获取350 ~ 2500 nm范围内的光谱数据，随后采用基线校正、标准正态变量、乘法散射校正、这些技术与Savitzky-Golay平滑的组合以及Savitzky-Golay平滑的一阶导数的应用等不同方法进行处理。使用六种不同的机器学习算法对数据进行分析：人工神经网络、决策树、逻辑回归、REPTree、随机森林和支持向量机。水稻类型作为输出变量，光谱特征作为输入变量。Logistic回归和支持向量机算法的分类效果最好，准确率在97%以上，f值在0.98左右，Kappa值超过0.97。光谱预处理没有产生实质性的改进，并且产生了很高的计算成本；因此，使用原始数据是一种可行且有效的替代方法。为了在大米储存行业中实际实施，我们建议获取VNIR-SWIR（可见近红外和短波红外）高光谱传感器（350-2500 nm），并开发基于支持向量机算法的分类模型，该算法具有代表性的局部样本训练的线性核。此外，我们建议实施一个自动化的实时分类系统，一个有代表性的样本收集协议，以及详细的库存和物流优化报告。

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引用次数: 0

Designing Climate-Resilient Rice Production Systems: Leveraging Genomics for Low-Emission Rice Varieties 设计适应气候变化的水稻生产系统：利用基因组学研究低排放水稻品种

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.08.003

Kossi Lorimpo Adjah , Vimal Kumar Semwal , Nana Kofi Abaka Amoah , Isaac Tawiah , Negussie Zenna , Raafat Elnamaky , Koichi Futakuchi , Elliott Ronald Dossou-Yovo , Shailesh Yadav

Rice cultivation contributes up to 12% of global anthropogenic methane (CH₄) emissions, making it a significant climate concern. With rice demand projected to double by 2050, achieving the required 2.4% annual genetic gain must be balanced with emission reduction. This review synthesizes recent progress in three key areas: (1) mitigation strategies such as alternate wetting and drying and direct-seeded rice, which can reduce CH₄ emissions by 30%–40%; (2) identification of physiological and molecular traits, such as short duration, high harvest index, improved nitrogen use efficiency, optimized root architecture, and stress tolerance with reduced greenhouse gas (GHG) footprints; and (3) the potential of genomics-assisted breeding and high-throughput phenotyping to accelerate the development of climate-resilient rice varieties with lower CH₄ emissions. Specifically, we highlight how the synergistic integration of high-throughput phenotyping, genomic selection, and marker-assisted breeding can substantially improve the efficiency and precision of breeding programs targeting the development of climate-resilient rice varieties with reduced CH₄ emissions. This is exemplified through successful case studies utilizing multi-omics approaches, including the development of Green Super Rice varieties (GSR 2 and GSR 8), which have demonstrated up to a 37% reduction in GHG emissions. Crucially, we propose a stratified trait profile for low-GHG rice development and provide guidelines and metrics for integrating these traits into mainstream breeding pipelines. We conclude by proposing a strategic framework integrating carbon-efficient breeding, climate-adapted agronomy, and policy support, which is essential for scaling low-GHG rice systems globally.

水稻种植贡献了全球人为甲烷（CH4）排放量的12%，使其成为一个重大的气候问题。预计到2050年，大米需求将翻一番，实现所需的2.4%的年遗传增益必须与减排相平衡。本文综述了三个关键领域的最新进展：(1)干湿交替和直接播种水稻等缓解策略，可减少30%-40%的CH4排放；(2)短生育期、高收获指数、提高氮素利用效率、优化根系构型、减少温室气体（GHG）足迹等生理和分子性状的鉴定；(3)基因组学辅助育种和高通量表型分析在加速培育低甲烷排放的气候适应型水稻品种方面的潜力。具体来说，我们强调了高通量表型、基因组选择和标记辅助育种的协同整合如何显著提高育种计划的效率和精度，以开发具有减少甲烷排放的气候适应型水稻品种。利用多组学方法的成功案例研究证明了这一点，包括绿色超级稻品种（GSR 2和GSR 8）的开发，这些品种已证明温室气体排放量减少了37%。重要的是，我们提出了低温室气体水稻发育的分层性状概况，并为将这些性状整合到主流育种管道中提供了指导和指标。最后，我们提出了一个整合碳高效育种、气候适应农学和政策支持的战略框架，这对于在全球推广低温室气体水稻系统至关重要。

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引用次数: 0

HS1 Enhances Rice Heat Tolerance Through Maintenance of Chloroplast Function and Reactive Oxygen Species Homeostasis HS1通过维持叶绿体功能和活性氧稳态增强水稻耐热性

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.08.010

An Wang , Zhengji Shao , Ying Liu, Guangheng Zhang, Li Zhu, Jiang Hu, Qian Qian, Deyong Ren

引用次数: 0

Comparing Genotype and Climate Change Effects on Simulated Historical Rice Yields Using AquaCrop 利用AquaCrop比较基因型和气候变化对模拟历史水稻产量的影响

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.09.001

Fazli Hameed , Shah Fahad Rahim , Anis Ur Rehman Khalil , Ram L. Ray , Xu Junzeng , Alhaj Yousef Hamoud , Akhtar Ali , Ning Tangyuan

Rice production, essential for global food security, is increasingly impacted by climate variability and genetic improvements. However, limited research has systematically quantified the individual contributions of climate change and genetic advancements to rice yield trends, particularly in high-latitude regions such as Harbin city, Heilongjiang Province, China. This study addresses this gap by using the AquaCrop model to partition the effects of climate change and genetic enhancements on rice yields over recent decades. The objectives were to evaluate the relative influences of climate and genotype on yield trends, assess irrigation efficiency under continuous flooding (CF) and alternate wetting and drying (AWD), and identify optimal transplanting dates for yield and water productivity. Four years of paddy field data were used to calibrate and validate AquaCrop for three rice varieties (V₁, V₂, and V₃) under CF and AWD irrigation. Historical climate data were sourced for simulations. Key findings indicated that climate change accounts for 60%‒70% of yield improvements, while genotype contributes 30%‒40%. AWD achieved grain yields within 1% of CF, while improving water productivity by up to 7% in later (V₂ and V₃) varieties and with delayed transplanting dates. Additionally, 15 May was identified as the optimal transplanting date, yielding up to 7.53 t/hm² under CF with biomass reaching 18.35 t/hm². These findings highlight strategies for sustainable rice production in water-scarce regions and emphasize the role of genotype development in climate adaptation.

对全球粮食安全至关重要的水稻生产日益受到气候变异和遗传改良的影响。然而，有限的研究系统地量化了气候变化和遗传进步对水稻产量趋势的个别贡献，特别是在高纬度地区，如中国黑龙江省哈尔滨市。本研究通过使用AquaCrop模型来划分近几十年来气候变化和基因增强对水稻产量的影响，从而解决了这一差距。目的是评估气候和基因型对产量趋势的相对影响，评估连续淹水（CF）和干湿交替（AWD）条件下的灌溉效率，并确定产量和水分生产力的最佳移栽日期。利用4年稻田数据，对3个水稻品种（V1、V2和V3）在CF和AWD灌溉条件下的AquaCrop进行了标定和验证。历史气候数据用于模拟。主要研究结果表明，气候变化对产量提高的贡献率为60%-70%，而基因型对产量提高的贡献率为30%-40%。AWD在CF的1%内实现了粮食产量，而在后期（V2和V3）品种和延迟移栽日期中提高了高达7%的水分生产力。5月15日为最佳移栽日期，CF条件下产量可达7.53 t/hm2，生物量可达18.35 t/hm2。这些发现突出了缺水地区可持续水稻生产的策略，并强调了基因型发展在气候适应中的作用。

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引用次数: 0

Identification of Rice Leaf Width Gene FLW11 Through Genome-Wide Association Study and Functional Analysis 水稻叶宽基因FLW11的全基因组关联研究及功能分析

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.06.004

Yulu YANG , Yanfang ZHANG , Xiong LIU , Lihua ZHANG , Jingfen HUANG , Lixing SHEN , Huibo ZHAO , Lan SHEN , Qiang ZHANG , Li ZHU , Jiang HU , Deyong REN , Zhenyu GAO , Guojun DONG , Weihua QIAO , Qian QIAN , Guangheng ZHANG

引用次数: 0

Genetic Regulation of Phytic Acid Biosynthesis in Rice: Pathways and Breeding Approaches for Low-Phytate Varieties 水稻植酸生物合成的遗传调控：低植酸品种的途径和选育途径

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.10.003

Lishali Desingu , R.L. Visakh , R.P. Sah , Uday Chand Jha , R.V. Manju , Swapna Alex , Radha Beena

Phytic acid (PA), or myo-inositol 1,2,3,4,5,6-hexakisphosphate, is the main storage form of phosphorus (P) in seeds, accounting for 65% to 85% of their total P content. The negative charge of PA attracts metal cations, forming insoluble salts called phytates. These phytates, contain six negatively charged ions, can bind divalent cations such as Fe²⁺, Zn²⁺, Mg²⁺, and Ca²⁺, preventing their absorption in monogastric animals. To overcome P deficiency in non-ruminants, phytase is usually given as a supplement, which then results in excess P excretion, leading to environmental problems such as eutrophication. Improved fertilizer management, food processing techniques, and the development of low-PA crops through plant breeding are envisioned as effective ways to improve P-utilization and lessen the environmental impact while minimizing the effect of PA. A better understanding of the molecular and physiological basis of PA biosynthesis, grain PA distribution, the effects of genetic and environmental factors on PA accumulation, and methods to increase micronutrient bioavailability by lowering the effects of PA is essential for developing low-PA crops.

植酸（PA）或肌醇（1,2,3,4,5,6-己基磷酸）是种子中磷(P)的主要储存形式，占其总磷含量的65% ~ 85%。PA的负电荷吸引金属阳离子，形成称为植酸盐的不溶性盐。这些植酸盐含有6个带负电荷的离子，可以结合二价阳离子，如Fe2+、Zn2+、Mg2+和Ca2+，阻止它们在单胃动物体内的吸收。为了克服非反刍动物的缺磷问题，通常会给植酸酶作为补充物，这会导致磷的过量排泄，从而导致富营养化等环境问题。改良肥料管理、食品加工技术和通过植物育种开发低磷作物被认为是提高磷利用率和减少环境影响的有效途径，同时最大限度地减少磷的影响。了解籽粒PA合成的分子和生理基础、PA分布、遗传和环境因素对PA积累的影响，以及通过降低PA效应来提高微量营养素生物利用度的方法，对开发低PA作物至关重要。

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引用次数: 0

OsABCG2 Controls Cadmium Accumulation in Rice Grains OsABCG2控制水稻籽粒镉积累

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.06.008

Haipeng Yu , Kaizhen Zhong , Zhen Zhang , Mingxue Chen , Weixing Zhang , Huijuan Li , Guanrong Huang , Zengying Huang , Lu Tang , Pengfei Yang , Zhengzheng Zhong , Guocheng Hu , Guoping Yu , Dezhi Wu , Hanhua Tong , Peng Zhang

引用次数: 0

Ecological Stoichiometric and Homeostatic Characteristics of Rice Soil under Different Ratios of Biochar Fertilizers 不同比例生物炭肥料对水稻土壤生态化学计量学和稳态特性的影响

IF 6.1 2区农林科学 Q1 AGRONOMY

Rice Science

Pub Date : 2025-11-01 DOI: 10.1016/j.rsci.2025.10.001

Yuqi Chen , Guanghua Wang , Jinbiao Zhao , Shilong Yu , Min Jiang , Zujian Zhang , Lifen Huang

引用次数: 0

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