Crop Design最新文献

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Comparative interactomics build the bridges from micromolecules to biological behaviour and morphology 比较相互作用组学架起从微观分子到生物行为和形态的桥梁
Crop Design Pub Date : 2024-11-01 DOI: 10.1016/j.cropd.2024.100078
Jinwen Chen
{"title":"Comparative interactomics build the bridges from micromolecules to biological behaviour and morphology","authors":"Jinwen Chen","doi":"10.1016/j.cropd.2024.100078","DOIUrl":"10.1016/j.cropd.2024.100078","url":null,"abstract":"<div><div>Behaviour, morphology and responses to stimuli in biological systems are determined by the genetic information of different types of biomolecules and the interactions between them. Comparative interactomics, the discipline devoted in comparing two or more interaction networks that happen in different species or under different cellular conditions, is a powerful tool for understanding systems evolution and the complex relationships that control cellular processes. This review provides an overview of data sources and research methods for comparative interactomics and the current directions in the application of comparative interactomics are summarised in brief. We also highlight the potential challenges of comparative interactomics in terms of interaction detection, noise delineation, alignment algorithms and quantitative network upgrading. We provide insights for future studies of network evolution using more accurate experimental and informative methodologies, with the hope that comparative interactomics to be further developed and build the study bridges from micromolecules to biological phenotypes.</div></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100078"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Strategizing pigeonpea for enhancing health-benefitting traits: A path to nutritional advancements 制定鸽子豆战略,增强有益健康的性状:营养进步之路
Crop Design Pub Date : 2024-11-01 DOI: 10.1016/j.cropd.2024.100068
Jwala Pranati , Vaishnavi Chilakamarri , Ashwini Kalyan , H.B. Shruthi , Naresh Bomma , Kalenahalli Yogendra , Prakash Gangashetty
{"title":"Strategizing pigeonpea for enhancing health-benefitting traits: A path to nutritional advancements","authors":"Jwala Pranati ,&nbsp;Vaishnavi Chilakamarri ,&nbsp;Ashwini Kalyan ,&nbsp;H.B. Shruthi ,&nbsp;Naresh Bomma ,&nbsp;Kalenahalli Yogendra ,&nbsp;Prakash Gangashetty","doi":"10.1016/j.cropd.2024.100068","DOIUrl":"10.1016/j.cropd.2024.100068","url":null,"abstract":"<div><div>Nutritional security is the key objective of India's 2030 Vision and UN Sustainable Development Goal 3. Although the world has made progress towards food security, there is still work to be done in assuring nutrition for all. While millions of people worldwide suffer from protein energy malnutrition and micronutrient deficiencies, providing nutrient-rich foods offers a long-term solution. Pigeonpea is a major daily diet of developing and undeveloped nations covering Asian and African households and increasing its protein and micronutrient (iron and zinc content) is a feasible approach. Thus, this review focusses on strategizing how pigeonpea could provide nutritional assurance in the coming decade. It primarily summarizes the dietary profile, health advantages, and anti-nutritional factors that hinder pigeonpea. Furthermore, it delineates the current progress through conventional breeding and molecular tools, while providing strategies to amalgamate advances in transgenics, omics and rapid generation advancement platforms to enhance health-benefitting traits and tackling the anti-nutritional factors contributing potentially towards the nutritional security.</div></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100068"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141851295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Genetic improvement of medicinal and aromatic plant species: Breeding techniques, conservative practices and future prospects 药用和芳香植物物种的遗传改良:育种技术、保守做法和未来前景
Crop Design Pub Date : 2024-11-01 DOI: 10.1016/j.cropd.2024.100080
Nazarul Hasan , Rafiul Amin Laskar , Shahabab Ahmad Farooqui , Neha Naaz , Nidhi Sharma , Megha Budakoti , Dinesh Chandra Joshi , Sana Choudhary , Mahendar Singh Bhinda
{"title":"Genetic improvement of medicinal and aromatic plant species: Breeding techniques, conservative practices and future prospects","authors":"Nazarul Hasan ,&nbsp;Rafiul Amin Laskar ,&nbsp;Shahabab Ahmad Farooqui ,&nbsp;Neha Naaz ,&nbsp;Nidhi Sharma ,&nbsp;Megha Budakoti ,&nbsp;Dinesh Chandra Joshi ,&nbsp;Sana Choudhary ,&nbsp;Mahendar Singh Bhinda","doi":"10.1016/j.cropd.2024.100080","DOIUrl":"10.1016/j.cropd.2024.100080","url":null,"abstract":"<div><div>Throughout history, herbal medicine has played a vital role in understanding and treating various ailments in humans and animals. The medicinal aromatic plant species, with their chemical compounds, offer potential solutions for addressing numerous diseases. Enhancing the genetic makeup of these plant species for both medicinal and economic purposes is now imperative. Mutation breeding is a significant strategy, having led to the development of nearly 3500 plant species. Polyploidy induction, doubling chromosomes, can result in larger and more valuable plant parts with medicinal and economic value. Plant tissue culture (PTC) is a crucial breeding technique, allowing for artificial polyploidy and Agrobacterium-mediated gene transformation to manipulate medicinal plant genomes, producing pharmaceutical secondary metabolites. The introduction of the third-generation clustered regularly interspaced short repeats (CRISPR)-Cas9 gene editing system has enabled the correction of defects seen in the first- and second-generation gene editing technologies, which relied on synthetic endonucleases like zinc finger endonuclease (ZFN) and transcription activator-like receptor nuclease (TALEN). These gene editing methods facilitate the manipulation of secondary metabolite pathways in medicinal plants. Virus-induced gene silencing (VIGS) based on short interfering RNA-mediated RNA silencing provides a rapid alternative for knocking out gene expression in medicinal and aromatic plant species that may not easily undergo stable genetic transformation. This article offers an overview of global trends, advancements, and prospects in conserving and breeding of medicinal aromatic plants, and helping as a valuable reference for sustainable resource utilization.</div></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100080"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Smart farming: Leveraging IoT and deep learning for sustainable tomato cultivation and pest management 智能农业:利用物联网和深度学习实现可持续番茄种植和病虫害管理
Crop Design Pub Date : 2024-09-10 DOI: 10.1016/j.cropd.2024.100079
Md Rakibul Hasan , Md. Mahbubur Rahman , Fahim Shahriar , Md. Saikat Islam Khan , Khandaker Mohammad Mohi Uddin , Md. Mosaddik Hasan
{"title":"Smart farming: Leveraging IoT and deep learning for sustainable tomato cultivation and pest management","authors":"Md Rakibul Hasan ,&nbsp;Md. Mahbubur Rahman ,&nbsp;Fahim Shahriar ,&nbsp;Md. Saikat Islam Khan ,&nbsp;Khandaker Mohammad Mohi Uddin ,&nbsp;Md. Mosaddik Hasan","doi":"10.1016/j.cropd.2024.100079","DOIUrl":"10.1016/j.cropd.2024.100079","url":null,"abstract":"<div><p>Since the world's population is rising continuously, more cultivable land is being utilized for their dwellings. As a result, the amount of food supply is decreasing day by day. In order to address the food shortage, a proper plan and technological breakthroughs is must. Tomato is a kind of vegetable which has the healthy ingredients and essential for our daily food list. The proposed system suggests an IoT based tomato cultivation and pest management system, with the help of deep learning methods. In the IoT implementation, camera module and moisture sensor are used to collect images of tomato plant, soil condition respectively. Based on the moisture content, the water pump will supply the water when it necessary. Besides, the real-time images of tomato leaf will be sent to the server to identify and classify natural enemies like various insect species. In the proposed system seven types of pests are identified with the help of ten deep learning models like InceptionV3, Xception, InceptionResNetV2, MobileNet, MobileNetV2, MobileNetV3Large, MobileNetV3Small, DenseNet121, DenseNet169, DenseNet201. This study has trained with leaves and insects separately to identify whether an image from a tomato plant is insectoid or not. 458 images of pests and 912 images of leaves are utilized in the proposed architecture. The accuracy of classifying insects or leaves using DenseNet201 is 100 ​%. The highest accuracy of 94 ​% is obtained to classify the different insects using the DenseNet201 model.</p></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100079"},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772899424000284/pdfft?md5=ab87dbf1526aea0dc25c64f64cff8542&pid=1-s2.0-S2772899424000284-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel multi trait genotype ideotype distance index (MGIDI) for genotype selection in plant breeding: Application, prospects, and limitations 用于植物育种中基因型选择的新型多性状基因型表意型距离指数(MGIDI):应用、前景和局限性
Crop Design Pub Date : 2024-09-02 DOI: 10.1016/j.cropd.2024.100074
Pinki Debnath , Kakon Chakma , M. Shafi Ullah Bhuiyan , Reshma Thapa , Ronghui Pan , Delara Akhter
{"title":"A novel multi trait genotype ideotype distance index (MGIDI) for genotype selection in plant breeding: Application, prospects, and limitations","authors":"Pinki Debnath ,&nbsp;Kakon Chakma ,&nbsp;M. Shafi Ullah Bhuiyan ,&nbsp;Reshma Thapa ,&nbsp;Ronghui Pan ,&nbsp;Delara Akhter","doi":"10.1016/j.cropd.2024.100074","DOIUrl":"10.1016/j.cropd.2024.100074","url":null,"abstract":"<div><p>The Multitrait Genotype Ideotype Distance Index (MGIDI) is a strong and adaptable technique for choosing superior genotypes of diverse crops based on numerous attributes. It is a multivariate selection indicator that incorporates different characteristic information into a single value and ranks genotypes based on their distance from an ideal genotype. Breeders can use variable selection criteria including weighting traits and assessing genetic strengths and weaknesses. It organizes attributes into components and chooses optimal genotypes based on many traits using principal component analysis. This review covered the available information regarding the background, applications, prospects, and limitations of MGIDI for crop improvement and breeding in this research. We discussed the significant discoveries and consequences of several studies that used MGIDI to enhance the productivity, excellence, and flexibility of numerous crops, such as bush yam, barley, cassava, cucumber, guar, lentil, maize, rice, bean, soybean, wheat, etc. Additionally, we talked about some of the potential applications of MGIDI for breeding and crop improvement, such as tolerance to salinity, stability analysis, tolerance to waterlogging, mechanism of drought response, performance in agronomy and tuber quality, nutritional value and productivity, adaptability, increased yield, early maturity, and stress resistance etc. Following the upward trend, MGIDI can be considered as a valuable index technique for selection of crop genotypes that can address food security, climate change, and nutritional quality problems worldwide. We expect that this study will spark more research and use of MGIDI in different crops characteristics, contributing to the improvement of plant breeding science.</p></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772899424000235/pdfft?md5=738e11c856be8307a5041292adf13221&pid=1-s2.0-S2772899424000235-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Decoding post-translational modifications for understanding stress tolerance in plant 解码翻译后修饰,了解植物的抗逆性
Crop Design Pub Date : 2024-08-30 DOI: 10.1016/j.cropd.2024.100077
Anuradha Pandey, Dipak Gayen
{"title":"Decoding post-translational modifications for understanding stress tolerance in plant","authors":"Anuradha Pandey,&nbsp;Dipak Gayen","doi":"10.1016/j.cropd.2024.100077","DOIUrl":"10.1016/j.cropd.2024.100077","url":null,"abstract":"<div><p>Plants undergo deteriorating stress situations, which has an adverse effect on their overall growth, maturation, and development. To mitigate these situations plants undergo regulatory cellular mechanisms including epigenetic changes at both genomic as well as protein levels. Post-transcriptional as well as translational modifications of proteins enhance its dynamics and complexity along with orchestrating several cellular functions in response to external stimuli. One of the most crucial roles of Post Translational Modification is under the stress tolerance mechanisms in plants. PTM creates a fine-tuning between all regulatory networks and serves as a highly responsible phenomenon. Illustrative analysis of post-translational modification in various signaling pathways has generated new insight for designing crop cultivars towards better development with higher yield and increased tolerance. In this review, we have first introduced post-translational modification and their types. Later, we discussed the prevalent biotic-abiotic stress, plants adaptation to the stress response mechanism, and the participation of PTMs in these stress conditions to highlight better agricultural productivity.</p></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100077"},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772899424000260/pdfft?md5=2d21151ca4f70ac33815356a00c4ce00&pid=1-s2.0-S2772899424000260-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Harnessing image processing for precision disease diagnosis in sugar beet agriculture 利用图像处理对甜菜农业进行精准疾病诊断
Crop Design Pub Date : 2024-08-29 DOI: 10.1016/j.cropd.2024.100075
Varucha Misra , A.K. Mall
{"title":"Harnessing image processing for precision disease diagnosis in sugar beet agriculture","authors":"Varucha Misra ,&nbsp;A.K. Mall","doi":"10.1016/j.cropd.2024.100075","DOIUrl":"10.1016/j.cropd.2024.100075","url":null,"abstract":"<div><p>Sugar beet, a sugar crop, faces a persistent threat from foliar and root diseases, leading to substantial yield losses. Traditional methods of disease identification and severity assessment are often time-consuming, error-prone, and impractical, particularly in large production areas. In response to this challenge, researchers have recently turned to innovative solutions involving image processing and machine learning techniques for efficient disease detection in sugar beet plants. Image processing technology has emerged as a rapid and precise disease identification technology in sugar beet. By capitalizing on the ability of image processing to differentiate coloured objects, this approach facilitates the accurate determination of disease severity, enabling timely intervention measures. The urgency of developing faster and more practical methods becomes evident, highlighting the need to decrease human errors in identifying plant diseases and assessing their severity and progression. This review showcases the potential of image processing technology in revolutionizing disease detection strategies for sugar beet crops. The ability to swiftly and accurately determine disease outbreak, severity, and progression addresses a critical gap in current agricultural practices. Image processing technology holds promise as a practical and efficient solution for large-scale disease management in sugar beet cultivation, paving the way for sustainable and high-yield sugar production.</p></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100075"},"PeriodicalIF":0.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772899424000247/pdfft?md5=ae186814fb085bc0a759f6c0475af60d&pid=1-s2.0-S2772899424000247-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Unveiling the protective role of chitosan in Plant Defense: A comprehensive review with emphasis on abiotic stress management 揭示壳聚糖在植物防御中的保护作用:以非生物胁迫管理为重点的全面综述
Crop Design Pub Date : 2024-08-27 DOI: 10.1016/j.cropd.2024.100076
Pravallika Sree Rayanoothala , Tuward J. Dweh , Sunita Mahapatra , Salma Kayastha
{"title":"Unveiling the protective role of chitosan in Plant Defense: A comprehensive review with emphasis on abiotic stress management","authors":"Pravallika Sree Rayanoothala ,&nbsp;Tuward J. Dweh ,&nbsp;Sunita Mahapatra ,&nbsp;Salma Kayastha","doi":"10.1016/j.cropd.2024.100076","DOIUrl":"10.1016/j.cropd.2024.100076","url":null,"abstract":"<div><p>In agricultural scenario, chitosan, a naturally occurring biopolymer derived from chitins, has the ability to function as both a bio-stimulant and an elicitor. Chitosan is produced from chitins. It is suitable for a wide range of uses because it is non-toxic, does not contaminate the environment, and is biocompatible with living things. It improves physiological reactions and lessens the negative effects of abiotic stimuli through the stress transduction pathway and the use of secondary messengers. Through nitric oxide and hydrogen peroxide-based signalling pathways, chitosan treatment activates antioxidant enzymes. Additionally, it stimulates the production of organic acids, carbohydrates, amino acids, and other metabolites needed for osmotic regulation, stress signalling, and other processes. Additionally, it can combine with heavy metals to produce compounds, and it is used in both phytoremediation and biological remediation of polluted soil. Additionally, this is applied topically to a variety of plants as an anti-transpirant agent, which reduces the quantity of water needed while also providing protection from other negative effects. Due of chitosan's exceptional properties and the way the climate is changing, sustainable farming practises are increasingly incorporating it. Our study is a compendium of current chitosan research that emphasises abiotic stress reactions. These responses could be helpful in upcoming initiatives to increase crop productivity.</p></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 4","pages":"Article 100076"},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772899424000259/pdfft?md5=f016241954b838cfa452e5fc934d78c5&pid=1-s2.0-S2772899424000259-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142099472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancing rangeland weed detection through convolutional neural networks and transfer learning 通过卷积神经网络和迁移学习增强牧场杂草探测能力
Crop Design Pub Date : 2024-08-01 DOI: 10.1016/j.cropd.2024.100060
{"title":"Enhancing rangeland weed detection through convolutional neural networks and transfer learning","authors":"","doi":"10.1016/j.cropd.2024.100060","DOIUrl":"10.1016/j.cropd.2024.100060","url":null,"abstract":"<div><p>The detection of weed species in rangeland environments is a challenging task due to various factors such as dense, variable species vegetation, ocular occlusion, and a wide variety of plant morphology. Most research in weed detection, however, focuses on croplands. This research addresses the need for accurate rangeland weed detection models by leveraging convolutional neural network (CNN) models enhanced with transfer learning applied to the DeepWeeds data set taken in situ in regional North Eastern Australia. It investigates the effectiveness of transfer learning across seven popular models, utilizing data augmentation and fine-tuning. The performance of these models was evaluated using accuracy metrics and compared against each other. The results demonstrated that transfer learning, coupled with fine tuning, could be a viable solution for generating efficient weed plant detection models with lower demands on computational resources and smaller datasets, despite the challenging conditions of rangeland environments. EfficientNetV2B1 had the highest classification accuracy of 94.2 ​%, and lowest training times. Moreover, high levels of accuracy were also achieved using InceptionV3, VGG16, and Densenet121, albeit with a training time penalty. This research provides insights into the performance of CNN models in challenging rangeland environments, demonstrates the potential of using transfer learning to enhance weed detection models, and underscores the significance of model selection in agricultural applications of CNNs.</p></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 3","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772899424000090/pdfft?md5=b5ed423e593946c009845b48ef4441bf&pid=1-s2.0-S2772899424000090-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141414283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modeling reveals synergies among root traits for phosphorus acquisition in pearl millet 建模揭示珍珠粟根性状对磷获取的协同作用
Crop Design Pub Date : 2024-08-01 DOI: 10.1016/j.cropd.2024.100059
{"title":"Modeling reveals synergies among root traits for phosphorus acquisition in pearl millet","authors":"","doi":"10.1016/j.cropd.2024.100059","DOIUrl":"10.1016/j.cropd.2024.100059","url":null,"abstract":"<div><p>Pearl millet is a key food security grain crop in the world's drylands due to its tolerance to abiotic stresses. However, its yield remains low and is negatively impacted by climate change. Root phenes are potential targets to improve crop productivity and resilience to environmental stress. However, the sheer number of combinations resulting from interactions of multiple phenes is a challenge for empirical research. <em>In silico</em> approaches are a plausible alternative to assess the utility of different phene combinations in varying states over diverse environmental contexts. Here, we developed an implementation of the functional-structural plant/soil model – OpenSimRoot, for pearl millet in typical sub-Sahelian soil and environmental conditions. Root architectural, anatomical, and physiological parameters were measured using a popular pearl millet variety (Souna 3) and implemented in the model. The above-ground biomass and root length density predicted by the model were similar to data from field trials. The utility of different root phenes was then evaluated for improved phosphorus uptake and plant growth in P deficient soils. Doubled root hair length and density, shallower root angle (−15°) and doubled long lateral root density were found to improve plant growth by 76 ​%, 33 ​% and 33 ​% respectively under low P conditions. Moreover, these phenes showed synergism when combined <em>in silico</em> and led to optimal biomass production in low P supply conditions that resulted in a 75 ​% loss of biomass in the reference variety. Our study suggests that these phenotypes could be targeted to improve biomass production in pearl millet and consequently its yield in low-P availability conditions.</p></div>","PeriodicalId":100341,"journal":{"name":"Crop Design","volume":"3 3","pages":"Article 100059"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772899424000089/pdfft?md5=5549435158853fc7a243a39138f2ab18&pid=1-s2.0-S2772899424000089-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141394433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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