A field experimental study was conducted during summer season (2023) at Eastern farm of Tamil Nadu Agricultural University, Coimbatore to evaluate suitable irrigation method for black gram. The experiment was laid out in a strip plot design which comprise main plot treatments such as M1 – Drip Irrigation, M2 –Micro sprinkler Irrigation, M3 – Rain hose Irrigation and M4 – Conventional Irrigation and subplot consists of different depths for placement of soil moisture sensor viz., D1 – 5 cm , D2 – 10 cm and D3 – 15 cm. The growth attributes viz., plant height, number of branches per plant, number of leaves per plant were significantly higher in drip irrigation system with sensor depth of 15cm. The root length and root dry weight were significantly greater in Rain hose irrigation with sensor placed at depth of 15 cm. The yield attributes viz., number of pods per plant, number of seeds per pod, number of seeds per plant, pod weight per plant, pod length, test weight, grain yield and haulm yield were significantly higher in drip irrigation with sensor placed at depth of 15 cm. The average grain yield of drip irrigation method is 31.7 per cent higher than the grain yield of conventional irrigation method. Higher grain yield of 1159 kg ha -1 was obtained in drip system with sensor placed at the depth of 15 cm. 

pdf/evaluation-of-suitable-smart-irrigation-system-for-black-3chk9p07jt.pdf

Evaluation of Suitable Smart Irrigation System for Black Gram

Accurate and timely pregnancy diagnosis is vital for efficient reproductive management and economic sustainability in buffalo husbandry. This study examines prevalence and determinants of false pregnancy diagnosis in buffaloes under field conditions across four major buffalo–rearing districts of Andhra Pradesh: Guntur, Prakasam, Krishna and Nellore. A multistage random sampling method yielded data from 240 dairy farmers and 415 buffaloes, capturing information on visual observation of estrus for pregnancy diagnosis (VOB) at 21±3–days intervals and rectal palpation (RP) conducted 60–120 days post-AI. The diagnostic accuracy of both methods was evaluated for sensitivity, specificity, predictive values and overall accuracy. VOB, though widely used, showed high sensitivity but low specificity, resulting in a considerable rate of false positives. In contrast, RP demonstrated significantly higher accuracy and reliability. Binary logistic regression was employed to identify factors influencing false diagnosis. For VOB, increased farmer experience and awareness significantly reduced false diagnosis risk, while larger herd sizes, poor body condition, reproductive disorders and high ambient temperatures elevated the risk. For RP, higher animal parity reduced false diagnosis odds, whereas poor body condition and specific seasonal contexts slightly compromised accuracy. 

pdf/prevalence-and-determinants-of-false-pregnancy-diagnosis-in-74hroowm2b4c.pdf

Prevalence and determinants of false pregnancy diagnosis in buffaloes: Field evidence from Andhra Pradesh, India

A field experiment was conducted at Wetland farm, Department of Agronomy, Tamil Nadu Agricultural University, Coimbatore during summer 2022 to study the effect of growth and yield parameters of greengram under different irrigation methods. The field experiment was laid out in randomized complete block design having seven treatments and replicated thrice. The treatment are T 1 : Check basin method (Line sowing), T 2 : Check basin method (Broadcasting), T 3 : Raised bed method (Line sowing), T 4 : Ridges and furrow method (Line sowing), T 5 : Drip irrigation system (Line sowing), T 6 : Drip irrigation system (Broadcasting) and T 7 : Sprinkler irrigation system (Line sowing). Experimental results showed that significantly higher plant height, number of branches plant -1 , number of pods plant -1 , pod weight plant -1 , number of seeds plant -1 , seed yield and haulm yield were recorded in drip irrigation system (Line sowing) in greengram which was on par with sprinkler irrigation system (Line sowing). Drip and sprinkler irrigation systems recorded the higher seed yield (42.1% and 36.1%, respectively) over check basin method (Broadcasting). This study revealed that the drip and sprinkler irrigation methods along with line sowing resulted better growth and yield parameters of summer greengram and enhanced its production.

Influence of different irrigation methods on growth and yield of summer greengram (Vigna radiata L.)

The impact of climate change is visually witnessed in the present environment by various natural disasters. This phenomenon of land surface temperature is one of the significant aspects to be estimated for the study of climate change. The increase in Land Surface Temperature (LST) may be due to ongoing developments in the field of urbanization and globalization. The objective of the study was to estimate the increase in the LST in relation to the Normalized Difference Vegetation Index (NDVI) and assess the spatial variation in the LST due to land use/land cover change. The study utilized Landsat 8 data to assess the land-use changes and their relation with LST in one of the main urbanized cities, i.e.  Coimbatore district of Tamil Nadu, using Landsat imagery due to the availability of various land cover types by using the mathematical expressions in ARCMAP software. This study compares the LST between 2015 and 2020 to observe the change in the NDVI and LST over a period of 5 years in the Coimbatore district. There was an increase of 1°C in 5 years and the area of high LST had been increased comparatively. The maximum LST was found to be 73°C in 2015, which increased to 74°C in the year 2020 ;and the minimum LST was found to be 15°C in 2015, which increased to 19°C in the year 2020 depicting the ongoing change in the land use of the district. The study findings will help promulgate sustainable urban land-use policies and can be used for mitigating climate change.

Estimation of land surface temperature for Coimbatore District using Landsat imagery

CLNet: a contactless fingerprint spoof detection using deep neural networks with a transfer learning approach

The parasympathetic vagus nerve supplies the heart and lung. The Parasympathetic activity modifies the heart rate and force of contraction in the heart and  Airway bronchial smooth muscle constriction and hypersecretion of mucus in the lungs. There is a link between these two components. Hence this study is designed to find the association between Spectral analysis of heart rate variability and pulmonary function tests in bronchial asthma patients. In this study, 30 asthmatic patients were recruited from the respiratory medicine outpatient department and 30 healthy volunteers were included. Pulmonary function tests and heart rate variability was recorded in the physiology department. The pulmonary function parameters were found significantly reduced in the asthmatic patient and it shows obstructive lung diseases. Heart rate variability parameters were found a statistically significantly decreased mean HR, VLF ms2, and LF ms2 in the asthmatic patients when compared to controls. HF ms2 was found significantly increased in the asthmatic patient. These HF ms2 were increased to represent parasympathetic hyperactivity. This study concluded there is parasympathetic dominance in asthmatic patients. The parasympathetic activity might be one of the reasons for increases the airway bronchoconstriction and hypersecretion of mucus. There is a negative correlation was found between FEV1 value and  HF ms2. A decrease in the FEV1 value leads to an increase in HF ms2.

Association between spectral analysis of heart rate variability and pulmonary function tests in bronchial asthma patients

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Influence of different irrigation methods on growth and yield of summer greengram (Vigna radiata L.)

Estimation of land surface temperature for Coimbatore District using Landsat imagery

CLNet: a contactless fingerprint spoof detection using deep neural networks with a transfer learning approach

Association between spectral analysis of heart rate variability and pulmonary function tests in bronchial asthma patients