scholarly journals Development of weather based prediction model for leaf roller population of Sesame in Bundelkhand zone of Madhya Pradesh

MAUSAM ◽  
2021 ◽  
Vol 61 (2) ◽  
pp. 229-232
Author(s):  
M. P. GUPTA ◽  
A. K. SRIVASTAVA ◽  
M. K. NAYAK
Keyword(s):  
Prediction Model ◽  
Agricultural Research ◽  
Weather Data ◽  
Research Station ◽  
Regression Equations ◽  
Larval Population ◽  
Leaf Roller ◽  
Multiple Regression Technique ◽  
Weather Parameters ◽  
The Impact

Field experiment was conducted during twelve consecutive Kharif seasons from 1995 to 2006 at Zonal Agricultural Research Station, Tikamgarh to find out the impact of weather parameters on the incidence and activity of Antigastra catalaunalis (Dupnocbel) in Sesame cv JT-7. The analysis revealed that the pest activity started to buildup from 30th standard meteorological week and remained up to 40th standard meteorological weeks (SMW). Larval population has been correlated with weather data and correlation coefficient, regression equations were worked out for development of weather based prediction model. Significant positive correlation with maximum and mean temperature (maximum, minimum) and negative relationships with rainfall was observed. Best fitted polynomial models were developed using the whole season data which explained 60 to 90 per cent variability due to weather parameters. The multiple regression technique has been used for developing predictive model using larval population and weather data not only for the corresponding week but also for preceding weeks. The prediction model for leaf roller explained 88% variability of the pest population. The model predicted peak larval population was in good agreement with observed peak larval population.  

scholarly journals DIGONESTIC ENVIRONMENTAL MONITERING SYSTEM IN A POULTRY HOUSE

2017 ◽  
Vol 48 (3) ◽  
Author(s):  
Al-Chalabi & et al
Keyword(s):  
Body Weight ◽  
Agricultural Research ◽  
Body Weight Gain ◽  
Ventilation System ◽  
Winter Season ◽  
Research Station ◽  
Feed Conversion ◽  
Poultry House ◽  
Productive Traits ◽  
The Impact

This experiment was conducted at a closed poultry house , Poultry Research Station , office of Agricultural Research, Ministry of Agriculture, Baghdad, Iraq, for the period from 2/9 to 14/03/2016 for total rearing of 35 days. To diagnose and monitoring the Environmental factors such as temperature, humidity , density, and the carbon dioxide levels inside the house during winter season, and its impact on the productive performance of broiler chickens Rose 308 breed .The dimensions of the house was ,length 35 m x width 7.5 m x Height 2.5 m, by total space volume 3656.25 m3. The ventilation system in the house was (negative pressure type). The house is totally closed, small fans for (minimum ventilation) in the winter are functioned, and large fans for ventilation in the evaporative cooling operation were used in the summer. 1000 sexed birds were used in this experiment imported through commercial hatchery in Abu Ghraib. The house was divided into three thermal Zones in order to find out whether heterogeneity in environmental conditions is existed in the house and at bird level .as a result the impact on the homogeneity in the weights of marketed birds . The treatments have been distributed into 32 rearing cages by the following order: 8 cages with the density of 50 birds / cage, the remaining 24 cages were divided into the density of 25 birds / cage. The results showed that there were significant differences between the treatments in the rate of body weight ,body weight gain, feed intake and feed conversion efficiency among   densities and the three thermal zones due to the presence of cool air leaks into the house at the front ,End of the house, and its sides especially when fans are on , along with dead Air pockets that were identified in many places in the middle of the housed, yet this Zone was the one that had the best productive traits in comparison with the other two zones. The purpose of this experiment is to study environmental parameters homogeneity  inside the shed in addition to impact of CO2 levels and impact of birds density on productive traits.

scholarly journals Population dynamics of stem fly and defoliator pests of soybean and their natural enemies in relation to weather parameters

2021 ◽  
Vol 17 (AAEBSSD) ◽  
pp. 17-26
Author(s):  
R. Bala Muralidhar Naik ◽  
K. Vijaya Lakshmi ◽  
M. Venkataiah ◽  
C. Srinivas ◽  
G. Uma Devi ◽  
...  
Keyword(s):  
Natural Enemies ◽  
Insect Pests ◽  
Agricultural Research ◽  
Growth Stages ◽  
Research Station ◽  
Peak Activity ◽  
Lepidopteran Insect ◽  
Weather Parameters ◽  
Lepidopteran Pest ◽  
Tobacco Caterpillar

The field experiment was carried out at Polasa Farm, Regional agricultural research station Jagtial during the Kharif, 2014-15 and 2015-16. Study about pre dominant lepidopteran insect –pests in soybean crop noticed that the tobacco cut worm, (Spodptera exigua Hubner), green semi looper(Crysodexis acuta Walker), and tobacco caterpillar (Spodoptera litura Fab) along with stemfly, (Melanagromyza obtusa Zehnter) as non lepidopteran pest were noticed at various growth stages of cropgrowth. The peak activity of stem fly (37.84%) was observed during 37th standard week per meter row) for the year 2014 and for the year 2015 to a maximum infestation of 35.70 per cent during 30th std.week. The peak activity of caterpillar pests i.e., S. litura (7.6 larvae per meter row) for the year 2014 was observed during 34th std.week and for the year 2015 (12.4 per meter row during 36th std.week and C. acuta (0.7 larvae per meter row) during 36th std. week for the year 2014 and for the year 2015 (2.20 larvae/mrl on 37th std week. S. exigua (1.6 larvae per meter row) for both the years 2014 and 2015 was observed during 32th std.week Among the natural enemies, one predators namely, spiders (Oxyopes sp. was observed to prey on the insect pests.The biocontrol agent’s one species, lynx spider, Oxyopes sp. population recorded on the crop during Kharif , 2014 ranged from 0.15 to 0.40 /mrl and 0.15 to 0.60/ mrl during Kharif, 2015.

scholarly journals A Comparative Study of Ensemble Classifiers for Paddy Blast Disease Prediction Model

2020 ◽  
Vol 8 (7) ◽  
pp. 09-17
Author(s):  
Varsha M., Dr. Poornima B.
Keyword(s):  
Prediction Model ◽  
Minimum Temperature ◽  
Blast Disease ◽  
Weather Data ◽  
Maximum Temperature ◽  
Research Station ◽  
Disease Prediction ◽  
Features Selection ◽  
Ensemble Classifiers ◽  
Epidemic Disease

Paddy blast has become most epidemic disease in many rice growing countries. Various statistical methods have been used for the prediction of paddy blast but previously used methods failed in predicting diseases with good accuracy. However the need to develop new model that considers both weather factors and non weather  data called blast disease data that influences paddy disease to grow. Given this point we developed ensemble classifier based paddy disease prediction model taking weather data from January 2013 to December 2019 from Agricultural and Horticulture Research Station Kathalgere Davangere District. For the predictive model we collected 7 kinds of weather data and 7 kinds of disease related data that includes Minimum Temperature, Maximum Temperature, Temperautre Difference,Relative Humidity, Stages of Paddy Cultivation, Varities of seeds, Season of cropping and so on. It is observed and analyzed that Minimum Temperature, Humidity and Rainfall has huge correlation with occurrence of disease. Since some of the variables are non numeric to convert them to numeric data one hot encoding approach is followed and to improve efficiency of ensemble classifiers  4 different filter based features selection methods are used such as Pearson’s correlation, Mutual information, ANNOVA F Value, Chi Square. Three different ensemble classifiers are used as predictive models and classifiers are compared it is observed that Bagging ensemble technique has achieved  accuracy of 98% compared to Adaboost of 97% and Voting classifier of 88%. Other classification metrics are used evaluate different classifiers like precision, recall, F1 Score, ROC and precision recall score. Our proposed ensemble classifers for paddy blast disease prediction has achieved high precision and high recall but when the solutions of model are closely looked bagging classifier is better compared to other ensemble classifers that are proposed in predicting paddy blast disease.

Effect of weather parameters on the population dynamics of White backed planthopper, Sogatella furcifera (Horvath) in rice

2021 ◽  
Vol 58 (1) ◽  
pp. 15-20
Author(s):  
ADVSLP Anand Kumar ◽  
N Mallikharjuna Rao ◽  
CV Rama Rao ◽  
S Krishnam Raju
Keyword(s):  
Population Dynamics ◽  
Andhra Pradesh ◽  
Agricultural Research ◽  
Abiotic Factors ◽  
Research Station ◽  
Sogatella Furcifera ◽  
Correlation Studies ◽  
Weather Parameters ◽  
Two Peaks ◽  
Second Peak

A field experiment on the population dynamics of White backed planthopper (WBPH), Sogatella furcifera (Horvath) carried out during kharif and rabi 2016-17 at Regional Agricultural Research Station, Maruteru, West Godavari District of Andhra Pradesh, India revealed that the incidence of WBPH was observed during 36th SMW (September 3-9). Its activity increased during successive weeks up to 44th SMW with two peaks, first peak at 38th SMW (September 17-23) with population of 46/10 hills and second peak at 42nd SMW (October 15-21) with population of 170/ 10 hills during kharif 2016, while WBPH was first noticed during 7th SMW (February 12-18) and population increased gradually during successive weeks and attained peak number during 13th SMW (March 26-April 1) in rabi 2016-17. Correlation studies revealed that WBPH had significant negative relation with morning relative humidity of current week during kharif 2016. None of the abiotic factors has showed significant relationship with the population of WBPH during rabi 2016-17.

scholarly journals Multispecies weed competition and their economic threshold on the wheat crop

2010 ◽  
Vol 28 (2) ◽  
pp. 239-246 ◽  
Author(s):  
J. Gherekhloo ◽  
S. Noroozi ◽  
D. Mazaheri ◽  
A. Ghanbari ◽  
M.R. Ghannadha ◽  
...  
Keyword(s):  
Field Experiments ◽  
Agricultural Research ◽  
Wheat Crop ◽  
Yield Reduction ◽  
Weed Competition ◽  
Research Station ◽  
Regression Equations ◽  
Wheat Grain ◽  
Economic Threshold ◽  
Wheat Field

Two field experiments were conducted to evaluate the effects of multispecies weed competition on wheat grain yield and to determine their economic threshold on the crop. The experiments were conducted in 2002, on two sites in Iran: at the Agricultural Research Station on Ferdowsi University of Mashhad (E1) and on the fields of Shirvan's Agricultural College (E2). A 15 x 50 m area of a 15 ha wheat field in E1 and a 15 x 50 m area of a 28 ha wheat field in E2 were selected as experimental sites. These areas were managed like other parts of the fields, except for the use of herbicides. At the beginning of the shooting stage, 30 points were randomly selected by dropping a 50 x 50 cm square marker on each site. The weeds present in E1 were: Avena ludoviciana, Chenopodium album, Solanum nigrum, Stellaria holostea, Convolvulus spp., Fumaria spp., Sonchus spp., and Polygonum aviculare. In E2 the weeds were A. ludoviciana, Erysimum sp., P. aviculare, Rapistrum rugosum, C. album, Salsola kali, and Sonchus sp. The data obtained within the sampled squares were submitted to regression equations and weeds densities were calculated in terms of TCL (Total Competitive Load). The regression analysis model indicated that only A. ludoviciana, Convolvulus spp. and C. album, in E1; and A. ludoviciana, S. kali, and R. rugosum, in E2 had a significant effect on the wheat yield reduction. Weed economic thresholds were 5.23 TCL in E1 and 6.16 TCL in E2; which were equivalent to 5 plants m-2 of A. ludoviciana or 12 plants m-2 of Convolvulus spp. or 19 plants m-2 of C. album in E1; and 6 plants m-2 A. ludoviciana, 13 plants m-2 S. kali and 27 plants m-2 R. rugosum in E2. Simulations of economic weed thresholds using several wheat grain prices and weed control costs allowed a better comparison of the experiments, suggesting that a more competitive crop at location E1 than at E2 was the cause of a lower weed competitive ability at the first location.

scholarly journals Effect of irrigation methods and mulching on growth and yield parameters of chilli (Capsicum annum L.) in arid condition

1970 ◽  
pp. 81
Author(s):  
R L Bhardwaj, M M Sundria, S R R Kumhar, N Kumar
Keyword(s):  
Drip Irrigation ◽  
Agricultural Research ◽  
Research Work ◽  
Fruit Rot ◽  
Growth And Yield ◽  
Cost Ratio ◽  
Research Station ◽  
Plastic Mulch ◽  
Irrigation Methods ◽  
The Impact

The research work was carried out to study the impact of various irrigation methods and mulching on plant growth, production and profitability of chilli cv. R.Ch. 1 at Agricultural Research Station, Mandor, Jodhpur during July, 2016 to February, 2017. The results of surface irrigation were compared with drip irrigation system under no mulch and in conjunction with plastic mulch. The results revealed that the crop was irrigated by drip irrigation on raise bed with 100 micron Linear Low Density Poly Ethylene plastic mulch (T8 treatment) exhibited significantly higher seedling survival at 15 and 30 days after transplanting (95.16% and 91.70%), highest plant height (47.10 cm at 45 DAT and 54.60 cm at harvest), highest number of branches (14.93) plant-1, maximum stem girth (2.32 cm) number of roots plant-1 (138.5), highest fruit set (38.47%), length of fresh fruit (12.56 cm), diameter of fruit (3.52 cm) and fresh weight of fruit-1 (8.42g) was observed. The maximum number of fruits plant-1(125), highest yield plant-1 (1052.5g), yield ha-1 (337.63q) and premier fruit quality score (9.11) with maximum net return (Rs.326407.28) and benefit: cost ratio (3.41) was also reported in same treatment. Comparatively minimum time (15 hours) required for one hectare irrigation was also reported in drip irrigation on raise bed with plastic mulch. This led to lower population of white fly plant-1 (4.53), minimum weed infestation (1.53 weed m-2), leaf curl (5.50%) and fruit rot (5.0%) incidence than other treatment combinations. The minimum growth, yield and profitability were reported in check basin method of irrigation without mulch (T1 treatment).

scholarly journals (27) Effect of Plant Stand Density and Pesticide Application Technology on Insect Pests and Diseases of Bell Peppers

HortScience ◽  
2006 ◽  
Vol 41 (4) ◽  
pp. 1075B-1075
Author(s):  
Salvador Vitanza ◽  
Celeste Welty ◽  
Mark Bennett ◽  
Sally Miller ◽  
Richard Derksen
Keyword(s):  
European Corn Borer ◽  
Agricultural Research ◽  
Stand Density ◽  
Research Station ◽  
Pesticide Application ◽  
Application Technology ◽  
Corn Borer ◽  
Full Rate ◽  
Plant Stand ◽  
The Impact

The impact of pesticide application technology and crop stand density on bell pepper production was evaluated in a series of field trials, during 2004 and 2005, at the North Central Agricultural Research Station, Fremont, Ohio. In 2004, one trial tested three sprayers, at a speed of 8 and 4 mph, using insecticides at half the recommended rate and one treatment at full rate. Sprayers evaluated included an air-assisted electrostatic sprayer, a Cagle sprayer equipped with AI-11005 or AI-110025 nozzles, and an air-blast sprayer with XR-1003-VS or XR-110015-VS nozzles. In 2005, one experiment tested the interaction of two application technologies, three planting distances within row, and single vs. twin rows. Another experiment compared the Cagle sprayer (with TJ60-11003 or AI-110025 nozzles) and the airblast sprayer (with XR-110015-VS nozzles), at a speed of 4 mph, and insecticides at half the recommended rate. In 2004, the Cagle sprayer with air-induction nozzle, half rate, at 8 mph obtained the highest fruit yield. There was not significant improvement in European corn borer control by applying insecticides at full rate with the Cagle sprayer and all treatments achieved significantly better bacterial soft rot control than the untreated control. In 2005, the trials were terminated early due to crop destruction by Phytophthora capsici. Red fruit weighed less at high than at medium or low plant stand densities. Clean yield of red fruit was significantly greater in single rows than in twin rows. Marketable yield of green fruit was greater using the TJ60-11003 than using the AI-110025 nozzles.

scholarly journals A Comparative Study of Ensemble Classifiers for Paddy Blast Disease Prediction Model

2020 ◽  
Vol 8 (9) ◽  
pp. 05-13
Author(s):  
Varsha M., Dr. Poornima B.
Keyword(s):  
Prediction Model ◽  
Minimum Temperature ◽  
Blast Disease ◽  
Weather Data ◽  
Maximum Temperature ◽  
Research Station ◽  
Disease Prediction ◽  
Features Selection ◽  
Ensemble Classifiers ◽  
Epidemic Disease

Paddy blast has become most epidemic disease in many rice growing countries. Various statistical methods have been used for the prediction of paddy blast but previously used methods failed in predicting diseases with good accuracy. However the need to develop new model that considers both weather factors and non weather  data called blast disease data that influences paddy disease to grow. Given this point we developed ensemble classifer based paddy disease prediction model taking weather data from January 2013 to December 2019 from Agricultural and Horticulture Research Station Kathalgere Davangere District. For the predictive model we collected 7 kinds of weather data and 7 kinds of disease related data that includes Minimum Temperature, Maximum Temperature, Temperautre Difference,Relative Humidity, Stages of Paddy Cultivation, Varities of seeds, Season of cropping and so on. It is observed and analyzed that Minimum Temperature, Humidity and Rainfall has huge correlation with occurrence of disease. Since some of the variables are non numeric to convert them to numeric data one hot encoding approach is followed and to improve efficiency of ensemble classifiers  4 different filter based features selection methods are used such as Pearson’s correlation, Mutual information, ANNOVA F Value, Chi Square. Three different ensemble classifiers are used as predictive models and classifiers are compared it is observed that Bagging ensemble technique has achieved  accuracy of 98% compared to Adaboost of 97% and Voting classifier of 88%. Other classification metrics are used evaluate different classifiers like precision, recall, F1 Score, ROC and precision recall score. Our proposed ensemble classifers for paddy blast disease prediction has achieved high precision and high recall but when the solutions of model are closely looked bagging classifier is better compared to other ensemble classifers that are proposed in predicting paddy blast disease.

scholarly journals Impacts of sulphur levels on yield, storability and economic return of onion

1970 ◽  
Vol 33 (4) ◽  
pp. 539-548 ◽  
Author(s):  
MH Ullah ◽  
SMI Huq ◽  
MDU Alam ◽  
MA Rahman
Keyword(s):  
Weight Loss ◽  
Agricultural Research ◽  
Control Treatment ◽  
Research Station ◽  
Gross Margin ◽  
Marginal Rate ◽  
Economic Return ◽  
Effect On Yield ◽  
The Impact ◽  
Bulb Yield

The experiments were carried out at the Regional Agricultural Research Station, Rahmatpur, Barisal during the rabi seasons of 2001-2002 and 2002-2003 to study the impact of different sulphur levels on bulb yield, storability and economic return of onion. Sulphur application had significant effect on yield components and bulb yield of onion. The highest bulb yields (19.75 and 19.88 t/ha) were obtained from sulphur levels between 60 and 75 kg/ha in two consecutive years. Both the cumulative weight and rotten loss were significantly influenced by sulphur fertilization. The maximum weight loss (40.78%) was recorded after 180 days of storage in S60 kg/ha and the minimum (31.40%) was found in S45 kg/ha. The bulbs stored in bamboo platform were found in acceptable condition after 6 months of storage showing 31.40% of weight loss. The maximum rotten bulbs (63.75%) were observed in control treatment (without S) and the minimum rotten bulbs (37.04%) were observed in S45 kg/ha after 180 days of storage because application of sulphur enhanced the storability of onion bulbs. The highest (9146 %) marginal rate of return (MRR) with gross margin of Tk. 181844/ha was obtained from the sulphur level S60 kg/ha. Key Words: Sulphur, yield, storability, economic return, onion. doi: 10.3329/bjar.v33i4.2286 Bangladesh J. Agril. Res. 33(4) : 539-548, December 2008

Advanced prediction to facilitate biocontrol of the mealybug Rastrococcus iceryoides (Hemiptera: Pseudococcidae) in organic mango (Anacardiaceae) orchards

2017 ◽  
Vol 150 (1) ◽  
pp. 116-119
Author(s):  
Nagalakshmi R Gujjar ◽  
Abraham Verghese ◽  
Devi Thangam Suresh ◽  
Rakshitha Mouly ◽  
Sunil Joshi
Keyword(s):  
Biological Control ◽  
Prediction Model ◽  
Agricultural Research ◽  
Maximum Temperature ◽  
Gear Up ◽  
Reasonable Accuracy ◽  
Independent Variables ◽  
Independent Variable ◽  
Weather Parameters ◽  
Horticultural Research

AbstractPredicting mango mealybug, Rastrococcus iceryoides (Green) (Hemiptera: Pseudococcidae), populations in an organic mango (Mangiferaindica Linnaeus; Anacardiaceae) ecosystem well in advance with reasonable accuracy, will facilitate biological control. In this study, an attempt was made to predict the population of mango mealybug using abiotic weather parameters as independent variables. The study was conducted at the Indian Council of Agricultural Research – Indian Institute of Horticultural Research, Bengaluru, India (12°8'N; 77°35'E). Among the abiotic variables, maximum temperature was found relevant for predicting the population of the mealybug based on significant correlations. It was found that a prediction model using maximum temperature as independent variable with R2 is most ideal. This prediction model, when considered three to four weeks in advance of an infestation, could help farmers to gear up with biological control.

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