STUDIES ON EFFECT OF WEATHER ON TRADITIONAL PHOTOSENSITIVE PTB-L AND HIGH YIELDING JAYA VARIETIES BY CURVILINEAR TECHNIQUE AT PATTAMBI, KERALA

A SlU d)' wa... cond ucted with tradition al photosensitive PTR-I an d hijrh )ield ina Jaya varieties ofnet' j'rown duri n~ kharifcrop season in sanlly loem soil under rai n(C'tJ co nd ition at Pauambt.Th e a nalysis was basedon curvili near tech nique an d seasonal rain fall. max imum an d minimum temperatures a nd briahl hou rs ofsunsh inehave been used.Th e stull )' enshit's determination of respo nse of yield to l1ilTercni ranees ofweather factor s. From (hefinal cu rves de te rm ine d in till' IInnl)'si s it is also ru ~...ibl e 10 e S li m~ te yield for diffe rent mean values of theweather factorsThe stud) revealed that ramfull is not that important for Ja)·. variet y. It abo does not nenl la l'Je amount of su nshineCOmpDrN to PTD-1. For both va riet ies. a lUu imum temperature of 29-C appears ideal for opt imum)it"ld

Sensitivity of convective rainfall to the adjustment parameters in the Betts-Miller scheme

ABSTACT. Three numerical experiments are carried out to study the sensitivity of the convective rain fall to the adjustment parameters used in the Betts-Miller scheme of cumulus convection. The results of the numerical experiments indicate that the convective rainfall has considerable sensitivity to saturation pressure departure value (S) whereas the impact of stability weight (W) on the convective rainfall is marginal. The limiting S values are found to produce drying of the column.

Does the Rotating Convection Paradigm Describe Secondary Eyewall Formation in Idealized Three-dimensional Simulations?

The formation of a plausible secondary eyewall is examined with two principal simulation experiments that differ only in the fixed value of rain fall speed, one with a value of 70 m s−1 (approaching the pseudo-adiabatic limit) that simulates a secondary eyewall, and one with a value of 7 m s−1 that does not simulate a secondary eyewall. Key differences are sought between these idealized three-dimensional simulations. A notable expansion of the lower-tropospheric tangential wind field to approximately 400 km radius is found associated with the precursor period of the secondary eyewall. The wind field expansion is traced to an enhanced vertical mass flux across the 5.25-km height level, which leads, in turn, to enhanced radial inflow in the lower troposphere and above the boundary layer. The inflow spins up the tangential wind outside the primary eyewall via the conventional spin-up mechanism. This amplified tangential wind field is linked to a broad region of outwardly-directed agradient force in the upper boundary layer. Whereas scattered convection is found outside the primary eyewall in both simulations, the agradient force is shown to promote a ring-like organization of this convection when boundary layer convergence occurs in a persistent, localized region of super-gradient winds. The results support prior work highlighting a new model of secondary eyewall formation emphasizing a boundary layer control pathway for initiating the outer eyewall as part of the rotating convection paradigm of tropical cyclone evolution.

Topological Sustainability of Crop Water Requirements and Irrigation Scheduling of Some Main Crops Based on the Penman-Monteith Method

The following method was used to apply the topology of the current study of evapotranspiration ETo, net irrigation demand, irrigation schedules, and total effective rain fall of different crop models: using the Food and Agriculture Organization's (FAO) CROPWAT 8.0 standard software and the CLIMWAT 2.0 tool and the FAO-56 Penman-Monteith approach to examine the variable topology of evapotranspiration ETo. Due to high temperatures in summer with an annual mean of 6.33 mm/day, the topological demonstration of reference evapotranspiration (ETo) increases from 2.84 mm/day in January to a maximum of 9.61 mm/day in July. Effective rainfall fluctuates from 0 mm to 53.4 mm. Total irrigation topological indices requirements were 308.3 mm/dec, 335.9 mm/dec, 343.6 mm/dec, 853 mm/dec, and 1479.6 mm/dec for barley, wheat, maize, rice, and citrus, respectively. The physical topological indices due to low demand in winter and high demand in summer, the total net irrigation, and gross irrigation for clay loamy soils for wheat (210.6 mm and 147.4 mm), barley (176.6 mm and 123.6 mm), citrus (204.5 mm and 143.2 mm), and maize (163.9 mm and 114.7 mm), but not for rice. This topology demonstrates that wheat has 4, barley has 4, citrus has 12, maize has 4, and rice crop has 12 irrigation schedules in a year.

An accurate mathematical model predicting number of dengue cases in tropics

Dengue fever is a systemic viral infection of epidemic proportions in tropical countries. The incidence of dengue fever is ever increasing and has doubled over the last few decades. Estimated 50million new cases are detected each year and close to 10000 deaths occur each year. Epidemics are unpredictable and unprecedented. When epidemics occur, health services are over whelmed leading to overcrowding of hospitals. At present there is no evidence that dengue epidemics can be predicted. Since the breeding of the dengue mosquito is directly influenced by environmental factors, it is plausible that epidemics could be predicted using weather data. We hypothesized that there is a mathematical relationship between incidence of dengue fever and environmental factors and if such relationship exists, new cases of dengue fever in the succeeding months can be predicted using weather data of the current month. We developed a mathematical model using machine learning technique. We used Island wide dengue epidemiology data, weather data and population density in developing the model. We used incidence of dengue fever, average rain fall, humidity, wind speed, temperature and population density of each district in the model. We found that the model is able to predict the incidence of dengue fever of a given month in a given district with precision (RMSE between 18- 35.3). Further, using weather data of a given month, the number of cases of dengue in succeeding months too can be predicted with precision (RMSE 10.4—30). Health authorities can use existing weather data in predicting epidemics in the immediate future and therefore measures to prevent new cases can be taken and more importantly the authorities can prepare local authorities for outbreaks.

Documentation of the Major Insect Pest of Cabbage and Their Associated Natural Enemies in Bihar, North-eastern India

The present investigation was conducted at farm of ICAR-Research Centre for Eastern Region (ICAR-RCER), Patna, Bihar during 2020-21.Geographically, ICAR-RCER, Patna is located at 25o35`30`` N latitude, 85o05`03`` E longitude, at an altitude 52m above mean sea level. The climate of the region is warm and temperate which is characterized by extremes of the temperature both during summer and winter. During summer, temperature may rise as high as 390C and in winter it may fall as low as 2-30C.The total annual average rain fall is 1130mm. This region provides a safe long growing season for most of the crops. Diamond back moth was found to be the most serious insect pest of cabbage. The infestation appeared during first week of January (SMW1) at vegetative stage and remained present up to the harvesting of the crop i.e. 11th SMW. Among the natural enemies, two species of coccinellids (Coccinella septempunctata, C. transversalis), one larval parasitoid (Cotesia plutellae) and one Syrphid fly (Toxomerus geminatus) and one unidentified spider was observed during crop period.

Bean Anthracnose (Colletotrichum lindemuthianum) in Kashmir: Epidemiology and Yield Loss Assessment

Background: The present study is region specific carried out to see the relation of bean anthracnose with weather in Kashmir and also to assess the yield loss in bean vis-à-vis anthracnose. Such studies form basis for deciding disease suppressive crop geometry and also sowing date alterations besides helping in disease predictions. The yield loss study in particular reveals the importance of a disease before any management strategies are worked out. Methods: Epidemiology was conducted under natural epiphytotic conditions using a susceptible bean cv. Shalimar Rajmash-1 for recording disease development at weekly intervals. Yield loss assessment was also recorded on Shalimar Rajmash-1 where different disease levels were created by inoculating at different phonological stages after maturity the crop stand disease free. Conclusion: During cropping season, the incidence and intensity of bean anthracnose developed to the extent of 77.06 and 54.51 per cent, when average temperature, average RH and weekly rain fall ranged from 16.6-23.8oC, 62.2-76.5 per cent and 1.7-48.2 mm, respectively. However, the highest periodic increase in disease incidence (12.62%) was recorded during 24th standard metrological week which coincided with highest rain fall and the increase in periodic disease intensity was higher ( greater than 10%) when RH was above 70 per cent. The yield loss in bean vis-a-vis variable levels of disease as created by inoculating different unit population of bean plants at different phenological stages revealed significant and positive correlation of bean anthracnose and yield loss. Highest yield loss (68.42%) was recorded in populations where the disease started at 1st trifoliate stage which then reached maximum intensity of 81.09 per cent at physiological maturity. The terminal disease intensity in population where disease started at pod filling was significantly low (18.59%) and caused least yield loss of 10.95 per cent. The study reveals that bean anthracnose caused significant yield loss when it appeared at any stage upto flowering.

Awareness level of climate change among paddy farmers

This study examined the awareness level of paddy farmers on climate change. Among the 29 districts of Tamil Nadu, Nagapattinam district was selected to conduct the present study. This is situated in coastal area and very often subjected to natural calamities which were mainly reflected on the rice cultivation to the worst status. Data for the study were collected from 200 respondents selected through simple random sampling technique. The study revealed that majority (71.50 %) of the respondent had medium level of awareness of climate change followed by high (17.00 %) and low (11.50 %) category. More than eighty per cent of the respondents were aware about the issues viz., receipt of low rain fall (90.50 %), uneven distribution of rain fall (89.00 %), frequent cyclone (87.00 %) and reduction in number of rainy days (86.50 %). The awareness level was found to be minimum in the issues like acid rain (34.50 %), variation in wind speed and direction (44.50 %), increasing heat and cold waves (48.00 %). The study concluded that the majority of farmers were aware of climate change but some of them were lacked in detail information about climate change. Therefore, it is suggested that extension education should be strengthened to boost farmers’ awareness level on climate change in detailed and prepare them for adaptation measures and that appropriate technologies be promoted for adaptation by farmers.