scholarly journals Screening of South Indian Culinary Melon (Cucumis melo subsp. agrestis var. acidulus) Accessions for Downy Mildew Disease under Natural Epiphytotic Condition

2021 ◽  
Vol 8 (4) ◽  
pp. 211-216
Author(s):  
Ratnakar M. Shet ◽  
◽  
A. Prashantha ◽  
P. S. Mahanthesh ◽  
K. S. Sankarappa ◽  
...  
Keyword(s):  
Downy Mildew ◽  
Cucumis Melo ◽  
Tamil Nadu ◽  
Indian Subcontinent ◽  
Indian States ◽  
South Indian ◽  
The Family ◽  
Percent Disease Index ◽  
Moderately Resistant ◽  
Downy Mildew Disease

Culinary melon also known as non dessert cucumber (Cucumis melo subsp. agrestis var. acidulus) belongs to the family Cucurbitaceae. It is widely cultivated in Southern parts of Indian subcontinent. It is mainly utilized for preparation of lentil soup, sambar, dosa, palya and chutney. 70 accessions were collected from six South Indian states namely Karnataka, Kerala, Andhra Pradesh, Tamil Nadu, Telangana and Goa. The accessions were evaluated for incidence of downy mildew resistance during Kharif 2018 under natural condition. The percent disease index (PDI) for downy mildew ranged from 3.70 to 48.64%. 10 accessions showed resistance to downy mildew. Among them, accession MS21 showed resistance with average least PDI of 3.70 followed by MS 6 (6.54). 50 accessions were found to be moderately resistant with average PDI ranging from 20 to 39.80. 12 accessions were found susceptible with PDI ranging from 41 to 49. None of the accession was found highly susceptible to the disease. The resistant accessions can be utilized as donor parents for resistant breeding in the improvement of culinary melon as well as melon group of vegetables.

scholarly journals Evaluation of Oriental Pickling Melon (Cucumis melo L. Var. conomon) Genotypes for Pest and Disease Reaction under Northern Dry Zone of Karnataka

2016 ◽  
Vol 7 (1) ◽  
pp. 29
Author(s):  
Shruti Prakash. Gondi ◽  
V. M. Ganiger ◽  
Bhuvaneshwari. G ◽  
M. B. Madalageri ◽  
Y. K. Kotikal ◽  
...  
Keyword(s):  
Powdery Mildew ◽  
Field Experiment ◽  
Downy Mildew ◽  
Cucumis Melo ◽  
Fruit Fly ◽  
Disease Reaction ◽  
The Family ◽  
Dry Zone ◽  
Cucumis Melo L ◽  
Downy Mildew Disease

<p>Cucurbits are the group of vegetables belongs to the family Cucurbitaceae. Oriental pickling melon (<em>Cucumis melo </em>var. <em>conomon)</em> is one among the melon group vegetables belongs to <em>Cucurbitaceae</em> family<em> </em>with a chromosomal number 2n=24. It is also called as golden melon or culinary melon in English. In Karnataka it is called by local names as <em>Sambar Southe, Mogghe kayi or Mangalore southe</em>. A field experiment was carried out at University of Horticultural Sciences Bagalkot, Karnataka to study the reaction of oriental pickling melon to fruit fly pest, diseases like powdery mildew and downy mildew disease. The results revealed that least infestation of fruit fly was recorded in Sirsi Local (40.00 %) followed by BCMCO-01 (41.30 %), BCMCO-02 and BCMSO-03 (41.75 % each). Highest infestation of fruit fly was recorded in Sirsi-2-13 (65.07 %) followed by BCMSO-04 (59.90 %). Among the genotypes, none of them had showed resistant to infestation and found susceptible to fruit fly attack in unsprayed condition. Least infestation of powdery mildew was found in Mysore Local (37.71 %) followed by Sirsi Local (37.99 %) and BCMSO-03 (39.76 %). Whereas highest mildew in GR-3 (46.08 %) followed by Sirsi-1-13 (45.81 %) and BCMCO-02 (45.75 %). Least infestation of downy mildew was observed in BCMCO-02 (14.00 %) followed by Sirsi Local (16.29 %) and BCMSO-03 (17.43%). Highest infestation was found in GR-2-1 (27.07%) followed by GR-4 (26.58 %) and GR-4-1 (26.23 %). Most of the genotypes were moderately susceptible to downy mildew disease.</p>

scholarly journals Identification of new resistant sources against downy mildew disease from a selected set of cucumber germplasm and its wild relatives

2020 ◽  
Vol 80 (04) ◽  
Author(s):  
Jameel Akhtar ◽  
Dikshant Gautam ◽  
Ranjan Nath ◽  
A. B. Gaikwad ◽  
K. V. Bhat ◽  
...  
Keyword(s):  
Downy Mildew ◽  
Plant Disease ◽  
Mapping Population ◽  
Disease Index ◽  
Sources Of Resistance ◽  
Resistant Accession ◽  
Genomic Regions ◽  
Moderately Resistant ◽  
Agroclimatic Zones ◽  
Downy Mildew Disease

This study was undertaken to identify new sources of resistance against downy mildew of cucumber caused by Pseudoperonospora cubensis [(Berk. and Cart.) Rostow]. Pot experiments were conducted with 16 accessions each of Cucumis sativus and C. hardwickii during the years 2017 and 2018 using 12 isolates of P. cubensis representing different agroclimatic zones of India. The accession, IC331627 from Dehradun, Uttarakhand showed plant disease index (PDI) ranging from 5.55-20.35 per cent with an average PDI of 11.56 and 11.87 per cent during the years, 2017 and 2018, respectively. Hence, IC331627 was identified to be resistant against the five isolates of P. cubesis (Pc12, Pc17, Pc19, Pc21 and Pc24) and moderately resistant against one isolate (Pc22). This resistant accession C. hardwickii (IC331627) could be utilized to develop mapping population to map genomic regions conferring the resistance to downy mildew in cucumber.

scholarly journals Additional Evaluations of Cucumis melo L. Germplasm for Resistance to Downy Mildew

HortScience ◽  
1999 ◽  
Vol 34 (5) ◽  
pp. 920-921 ◽  
Author(s):  
C.E. Thomas
Keyword(s):  
Downy Mildew ◽  
Cucumis Melo ◽  
Disease Index ◽  
Reaction Type ◽  
Plant Introductions ◽  
Moderately Resistant ◽  
Cucumis Melo L

Field evaluations for resistance against downy mildew, incited by Pseudoperonospora cubensis (Berk. & M.A. Curtis) Rostovzev were conducted on 1076 U.S. Plant Introductions (PI) of Cucumis melo L. (melon). A disease index (DI) was calculated for each entry that had one or more resistant plants. Based on DI, PIs 271329 and 401644 were the most resistant overall (DI = 2.6 and 2.8, respectively). However, resistant plants exhibiting reaction type (RT) 3 were identified in 68 accessions, and 110 accessions had moderately resistant (RT 2) plants.

scholarly journals Crop Yield Prediction using XG Boost Algorithm

2020 ◽  
Vol 8 (5) ◽  
pp. 3516-3520
Keyword(s):  
Crop Yield ◽  
Tamil Nadu ◽  
Crop Yields ◽  
Absolute Error ◽  
Climatic Conditions ◽  
Support Vector ◽  
Yield Prediction ◽  
Indian States ◽  
South Indian ◽  
Proposed Model

The main objective of this research is to predict crop yields based on cultivation area, Rainfall and maximum and minimum temperature data. It will help our Indian farmers to predict crop yielding according to the environment conditions. Nowadays, Machine learning based crop yield prediction is very popular than the traditional models because of its accuracy. In this paper, linear regression, Support Vector Regression, Decision Tree and Random forest is compared with XG Boost algorithm. The above mentioned algorithms are compared based on R2 , Minimum Square Error and Minimum Absolute Error. The dataset is prepared from the data.gov.in site for the year from 2000 to 2014. The data for 4 south Indian states Andhra Pradesh, Karnataka, Tamil Nadu and Kerala data alone is taken since all these states has same climatic conditions. The proposed model in this paper based on XG Boost is showing much better results than other models. In XG Boost R2 is 0.9391 which is the best when compared with other models.

CORRELATES OF FEMALE STERILIZATION REGRET IN THE SOUTHERN STATES OF INDIA

2000 ◽  
Vol 32 (4) ◽  
pp. 547-558 ◽  
Author(s):  
MALA RAMANATHAN ◽  
U. S. MISHRA
Keyword(s):  
Tamil Nadu ◽  
Family Health ◽  
Quality Of Services ◽  
Child Loss ◽  
Indian States ◽  
Southern States ◽  
South Indian ◽  
Loss Experience ◽  
Using Data

This study analyses factors associated with the incidence of sterilization regret in the four south Indian states of Andhra Pradesh, Karnataka, Kerala and Tamil Nadu. Using data from the National Family Health Surveys, in all four states the incidence of regret was found to be less than 10% and the factors significantly associated with it were child loss experience and quality of services. Hence, there is a need to improve the quality of services, both in terms of counselling and service provision, and women need to be counselled about the permanent nature of sterilization in order to avoid future regret.

scholarly journals Decomposing the performance metrics of coconut cultivation in the South Indian States

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Shine Raju Kappil ◽  
Ranjan Aneja ◽  
Poonam Rani
Keyword(s):  
Local Governments ◽  
Tamil Nadu ◽  
Performance Metrics ◽  
Cocos Nucifera ◽  
Decomposition Analysis ◽  
Total Production ◽  
The South ◽  
Indian States ◽  
Growth Trends ◽  
South Indian

AbstractCoconut (Cocos nucifera) is extensively cultivated and used as a staple ingredient in Indian cuisines, especially in the South Indian cuisines. In India, other than edible purposes, coconut is widely used in religious practices and, it is considered as symbol of prosperity. Despite these facts, several upturns and downturns occurring in the growth trends of coconut in recent periods irrespective of geographical differences. This study attempts to decipher the growth trends in the area, the production and yield of coconut in major coconut producing states in India from 2000–2001 to 2017–2018. Kerala, Tamil Nadu and Karnataka are the states in India where coconut palms are extensively cultivated and produced in large quantities. These states together contribute to approximately 84 per cent of the total area for cultivation of coconut and account for over 87 per cent of total production in the country. We analyse the growth trends in coconut cultivation using appropriate growth equations to estimate the growth rates and instabilities in growth trends. Besides, we use decomposition analysis to find the role of area, price, yield and crop mix effects on coconut production. The results reveal that Karnataka secured high growth in coconut production and its productivity and recorded better acceleration but fluctuated heavily between the phases of years under investigation. It shows that the price effect and yield effect play a crucial role in the total change of coconut production among the selected states. Based on the results, we recommend the local governments and other dedicated authorities to ensure that coconut growers have better access to modern technology, quality inputs, marketing and credit facilities following local necessity. Eventually, these measures can attract and encourage many new farmers into coconut cultivation and thereby achieving better advances in coconut farming.

scholarly journals Description of a new species of Omyomymar Schauff from India with a key to Oriental species and first report of Palaeoneura markhoddlei Triapitsyn (Hymenoptera: Mymaridae) from the Indian subcontinent

2020 ◽  
Vol 12 (14) ◽  
pp. 17003-17008
Author(s):  
H. Sankararaman ◽  
S. Manickavasagam
Keyword(s):  
New Species ◽  
Tamil Nadu ◽  
Indian Subcontinent ◽  
Indian Species ◽  
Indian States ◽  
First Report ◽  
First Time ◽  
A New Species

Abstract: Omyomymar hayati sp. nov. (Hymenoptera: Chalcidoidea: Mymaridae) is described from Tamil Nadu, India and key to Oriental species of Omyomymar is updated.  Palaeoneura markhoddlei Triapitsyn, is reported from Indian subcontinent for the first time and key to Indian species is updated.  The following known species, viz., Acmopolynema incognitum (Narayanan, Rao & Kaur), Platystethynium glabrum Jin & Li, Polynema (Polynema) bengalense Rehmat & Anis and Palaeoneura vegis Amer & Zeya are recorded from the Indian states of Rajasthan, Karnataka, Kerala, and Tamil Nadu, respectively.  

scholarly journals Evaluation of Melon Germplasm for Resistance to Downy Mildew

HortScience ◽  
1992 ◽  
Vol 27 (5) ◽  
pp. 434-436 ◽  
Author(s):  
Claude E. Thomas ◽  
E.L. Jourdain
Keyword(s):  
Downy Mildew ◽  
Cucumis Melo ◽  
Disease Index ◽  
Pseudoperonospora Cubensis ◽  
Reaction Type ◽  
Plant Introductions ◽  
Resistant Reaction ◽  
Moderately Resistant

Field evaluations for resistance against downy mildew, incited by Pseudoperonospora cubensis [(Berk. and Cart.) Rostow], were conducted on 942 U.S. Plant Introductions (PI) of Cucumis melo L. (melon). A disease index (DI) was calculated for each entry. Based on DI, PI 124112 was highly resistant (DI = 3.7), and PIs 124111, 122847, 124210, 145594, and 165525 were resistant (DI = 3.0, 2.8, 2.6, 2.7, and 2.5, respectively). PIs 124111 and 124112 had one or more plants that exhibited a highly resistant reaction type (RT 4). Resistant (RT 3) plants were identified in 31 accessions, and 49 accessions bad moderately resistant (RT 2) plants.

scholarly journals Nexus between population density and COVID-19 pandemic in the south Indian states: A geo-statistical approach

2020 ◽  
Author(s):  
Mohammad Arif ◽  
Soumita Sengupta
Keyword(s):  
Population Density ◽  
Tamil Nadu ◽  
Spatial Relationship ◽  
The Novel ◽  
Global Public Health ◽  
Indian States ◽  
Health Crisis ◽  
South Indian ◽  
Novel Coronavirus

The unprecedented growth of the novel coronavirus (SARS-CoV-2) as a severe acute respiratory syndrome escalated to the 2019 coronavirus disease (COVID-19) pandemic. It has created an unanticipated global public health crisis. The virus is spreading rapidly in India which poses serious threat to 135 crore population. Population density poses some unforeseen challenges to control the COVID-19 contagion. In times of crisis, data is crucial to understand the spatial relationship between density and the infection. The article study the district wise transmissions of the novel coronavirus in five south Indian states until 6th June 2020 and its relationship with the respective population density. The five states are purposefully selected for better healthcare infrastructure vis-à-vis other states in India. We observed that corona virus spread depends on the spatial distribution of population density in three states especially in Tamil Nadu, Karnataka and Telangana. The results indicate that the long-term impacts of the COVID-19 crisis are likely to differ with demographic density. Policy initiatives aimed at reducing the health consequences of the COVID-19 pandemic should understand how vulnerabilities cluster together across districts.

Taxonomic position of Heissothignus and review of the species of Meschia (Hemiptera: Heteroptera: Meschiidae)

Zootaxa ◽  
2021 ◽  
Vol 5032 (2) ◽  
pp. 283-289
Author(s):  
M. B. MALIPATIL ◽  
H. M. YESHWANTH ◽  
ELŐD KONDOROSY
Keyword(s):  
Tamil Nadu ◽  
Andhra Pradesh ◽  
New South ◽  
Indian Subcontinent ◽  
New South Wales ◽  
Morphological Characters ◽  
Taxonomic Position ◽  
South Wales ◽  
The Family ◽  
New Synonymy

The New Guinean genus Heissothignus Slater & Brailovsky, 2006 (Hemiptera: Heteroptera: Meschiidae) possesses several morphological characters unique to family Meschiidae but not occurring in Heterogastridae, confirming its placement within the family Meschiidae. A key to the genera of the family Meschiidae is presented. The two species of the genus Meschia Distant, 1910 recorded from the Indian subcontinent are reviewed, and the following new synonymy is proposed: M. pugnax Distant, 1910 = M. quadrimaculata Distant, 1910, syn. nov. A revised key to the species of Meschia is provided. New country and state records are provided for M. pugnax (India: Andhra Pradesh, Karnataka, Meghalaya, Rajasthan, Tamil Nadu and Uttarakhand), Meschia barrowensis Malipatil, 2014 (Australia: New South Wales) and Meschia zoui Gao & Malipatil, 2019 (Thailand).  

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