Disease Resistance in Sorghum

Das, I. K.; Rajendrakumar, P.

doi:10.1016/b978-0-12-804549-7.00002-0

Cited by 14 publications

(6 citation statements)

References 104 publications

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“…This led to the development of comprehensive research programs-a). Germplasm screening-Identifying resistant lines for major biotic stresses like shoot fly, stem borer, midge, aphids, shoot bug, grain mold, charcoal rot, and foliar diseases (Das and Padmaja 2016); b). Resistance traits-Identifying and characterizing traits associated with resistance; c).…”

Section: Breeding For Resistance To Biotic Stressesmentioning

confidence: 99%

“…In addition to grain mold, sorghum suffers from several foliar diseases, particularly destructive under warm and humid conditions (Das et al 2016). These include leaf spots caused by fungi like Bipolaris sorghicola, Cercospora sorghi, and Gloeocercospora sorghi, anthracnose caused by Colletotrichum sublineolum, rust caused by Puccinia purpurea, and various viral diseases.…”

Section: Foliar Diseasesmentioning

confidence: 99%

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Millets and pseudocereals: A treasure for climate resilient agriculture ensuring food and nutrition security

Nagaraja,

Parveen,

Aruna

et al. 2024

IJGPB

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Once, a staple food for civilizations and a popular feed for centuries, millets are a treasure trove of micronutrients and essential amino acids. Despite being side-lined during the Green Revolution, these small-seeded powerhouses are perfectly adapted to harsh dryland conditions such as low rainfall, drought, and high temperatures. The millets require minimal maintenance and thrive under stress, showcasing their rich genetic diversity and adaptability. However, boosting genetic gain and developing high-yielding varieties remains a challenge due to restricted research, limited genomic tools, poor market demand and accessibility to germplasm. As our climate and cropping systems are changing, millets offer a promising solution for diversification and adaptation. Beyond their impressive nutrition, they possess therapeutic benefits, making them valuable for medicinal purposes. However, the cultivation of millets, especially the minor millets, has declined due to their underutilization in daily diets. Genetic improvement and application of modern technologies are needed to increase production and integrate these millets as alternative food sources in Indian cuisine. Fortunately, growing awareness of their nutritional value, health benefits, and industrial uses is fuelling a revival. Recognizing their potential, national and international organizations are working to restore millet cultivation. The United Nations even declared 2023 as the “International Year of Millets" at Indian initiative. This review highlights the progress made in the genetic improvement of both major (sorghum, pearl millet, finger millet) and minor millets (foxtail, proso, kodo, barnyard, little and browntop millets). Additionally, pseudo-cereals like buckwheat and amaranth are included. The areas of future research have also been indicated for urgent attention and immediate action to make millets and pseudo-cereals a household food ensuring food and nutrition security and climate resilient agriculture in India.

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Section: Breeding For Resistance To Biotic Stressesmentioning

confidence: 99%

Section: Foliar Diseasesmentioning

confidence: 99%

Millets and pseudocereals: A treasure for climate resilient agriculture ensuring food and nutrition security

Nagaraja,

Parveen,

Aruna

et al. 2024

IJGPB

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“…This can result in adverse effects on forage productivity, quality, and grain yield. According to Das et al (2016), it has been observed that during severe epidemics, there is a significant reduction in grain yields, potentially reaching a decline of 50% or even more.…”

Section: Introductionmentioning

confidence: 99%

MCIP: Mining Crop Image Data On pysparkdataframe Using Feature Selection and Cluster Based Techniques

Chaudhary,

Pathak

2023

IJERR

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Crop-related problems such as pests and diseases in India lead to yearly losses exceeding $500 billion. Leaf blight is identified as the principal factor responsible for the substantial financial losses amounting to $500 billion. Farmers engaged in the cultivation of forage and grain sorghum experience the greatest degree of hardship. This disease has a significant impact on various crops, including maize, rice, tomato, potato, millet, and onion. The timely detection and evaluation of disease in plants can contribute to mitigating the extent of associated losses. However, the task presents difficulties as a result of variations in crop species, varieteis of crop diseases, and environmental factors. The current methodologies lack generalizability in their ability to classify and predict diseases. All of the techniques employed in this study are applied to a dataset with predetermined input values and corresponding output values. The current methodologies involve preprocessing the images and performing segmentation for extracting the appropriate characteristics. The process of segmentation necessitates the implementation of pre-processing techniques, such as dilation and edge detection. As a consequence, the loss of crucial information occurs, which subsequently leads to inaccurate classification. Furthermore, the methodologies employed thus far have not been designed to evaluate the performance of the algorithm on specialised or specific datasets. Deep learning methodologies are susceptible to the issue of overfitting. This paper proposed an approach for extracting and analysing crop image data using the PySpark (MCIP) data frame. The MCIP framework employs Principal Component Analysis (PCA) as a method for selecting pertinent features. The PCA features that have been gathered are subsequently employed to identify homogeneous subgroups through the utilisation of the K-means algorithm. The utilisation of a categorised predictive output facilitates the identification and detection of diseases present in potato leaves. The utilisation of the Multispectral Crop Imaging Platform (MCIP) extends beyond the examination of potatoes exclusively, as it possesses the capability to identify diseases present in the foliage of various agricultural crops. In order to validate our assertion, we conducted an experiment utilising the MCIP algorithm on a dataset pertaining to rice diseases. In order to assess the robustness of MCIP, we conducted an evaluation of its Accuracy, Silhouette score, speed, and F1 score. The MCIP model demonstrated high performance in terms of both speed and accuracy compared to existed approaches. The level of accuracy is remarkably near 100 percent. Index Terms— Agriculture, clustering, data mining, k-means, pca, pySpark

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“…Global climate changes, such as rising temperatures and rainfall, also support the development, spread, and changing patterns of pest and disease attacks (Rao and Kumar 2013;Doody 2020). Sorghum disease is also caused by fungi, viruses, bacteria, and nematodes, as is common in other crops (Das and Rajendrakumar 2016;Prom 2017). One of the diseases of sorghum is leaf rust caused by Puccinia purpurea (White et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Diversity of leaf rust resistance in Indonesian sorghum genetic resources

et al. 2022

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Abstract. Dinanty F, Wirnas D, Trikoesoemaningtyas, Nawangsih AA. 2022. Diversity of leaf rust resistance in Indonesian sorghum genetic resources. Biodiversitas 23: 2570-2579. Sorghum is an alternative source as a substitute for rice. Leaf rust (Puccinia purpurea) is a constraint in sorghum cultivation and resistance to rust disease is a condition for releasing sorghum varieties. This study aimed to screen sorghum accessions for resistance to leaf rust disease. The screening was carried out on 48 sorghum accessions and seven check varieties, namely Numbu, Kawali, Bioguma 1, Pahat, Soraya 1, Soraya 2, and Soraya 3. Evaluation of leaf rust resistance under field conditions was carried out in IPB University experimental field Cikarawang-Bogor (275 asl) from February 2021 to June 2021. The experiment was conducted in an augmented design with four replications for check varieties. Identification of leaf rust resistance was also carried out using molecular markers designed from the Lr34 and Rp1D genes. The results revealed that 5 genotypes, namely genotypes 31 (Demak 2), 24 (IS 18551), 43 (Lokal bima 3), 17 (ICSV 93036), and 33 (Demak 5) were resistant to leaf rust with high yield potential. The results of identification using molecular markers showed that all accessions had Lr34 and Rp1D gene fragments.

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Disease Resistance in Sorghum

Cited by 14 publications

References 104 publications

Millets and pseudocereals: A treasure for climate resilient agriculture ensuring food and nutrition security

Millets and pseudocereals: A treasure for climate resilient agriculture ensuring food and nutrition security

MCIP: Mining Crop Image Data On pysparkdataframe Using Feature Selection and Cluster Based Techniques

Diversity of leaf rust resistance in Indonesian sorghum genetic resources

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