Volume 12, No. 3, 2023 (In Progress)
Conjugation of Quantum Dot (CdS) with Antibodies for Identification of Ornithobacterium Rhinotracheale Tahreem Ahmed, Hadiya Amjad, Mehwish, Rahat Jamil and Ayesha Anwar Int J Agri Biosci, 2023, 12(3): 128-135. ![]() Abstract
Nanobiotechnology is an emerging field that has made its way towards medical imaging, pharmaceuticals, cancer treatment, diagnosis, tissue regeneration and implantation. Quantum dots are widely applicable in the fields of diagnostics, biomedical imaging, sensors and drug delivery. Quantum dots range in the size from 2-10nm. Quantum dots have ability to give specific fluorescence after binding with target. The synthesis of Quantum dots CdS nanoparticles required special inert conditions of high temperature and pressure by using reflux method up to 16 hours. 3.3×10 20 grams Quantum dots CdS nanoparticles per moles were calculated from stoichiometric analysis. The conjugation of cysteine with Quantum dots CdS nanoparticles required sulphur-sulphur bond (-S-S-). The development of maroon-purple color has confirmed this binding via Ninhydrin test. The bioconjugation of IgY with Quantum dots CdS nanoparticles and cysteine has occurred by glutaraldehyde method. This bioconjugation appeared between -NH- groups of the cysteine and IgY. FTIR analysis has confirmed conjugation of Quantum dots CdS nanoparticles to cysteine and further conjugation to IgY through its peaks. A UV-visible spectrum of Quantum dots CdS nanoparticles conjugated with cysteine has shown maximum absorbance of 0.818 at 245nm. UV-visible spectra of Quantum dots CdS nanoparticles with cysteine conjugated to IgY has shown maximum absorbance of 2.119 at 320nm. The absorption peaks of spectra have indicated that the size of nanaoparticles was around 100nm. A yellow color product has confirmed IgY through ELISA and brown coloration has confirmed IgY through immnuo-dot blot. The culture of ORT was obtained from Amber Lab. The binding of ORT with Quantum dots CdS nanoparticles gave green fluorescence under fluorescence microscope by using the scale of 100μm. The binding of QDs CdS conjugated with IgY has helped for the rapid in-vitro identification and diagnosis of ornitobacterium rhinotracheale caused by the infection of ORT. This diagnostic tool has helped poultry industry to save from massive economical losses. Keywords: Nanobiotechnology, Ornitobacterium Rhinotracheale, Poultry Industry. ![]() |
Natural Control Perspectives of Dermanyssus Gallinae in Poultry Saba Mehnaz, Rao Zahid Abbas, Kostadin Kanchev, Muhammad Nauman Rafique, Muhammad Arslan Aslam, Muhammad Bilal, Azhar Shabbir Ather, Ali Zahid and Tooba Batool Int J Agri Biosci, 2023, 12(3): 136-142. ![]() Abstract
Dermanyssus gallinae (Poultry red mite) is known to be the most dangerous ectoparasite of poultry. Specifically, it causes vascular damage, loss of blood, skin rashes in the host, and sometimes leads to death. D. gallinae has animal health and welfare issues but it mainly affects eggs-production industry. Global annual loss due to D. gallinae is 3.92 billion USD. Different chemical compounds and pesticides are used to control poultry red mites in poultry farms. However, the emergence of drug resistance against different chemical compounds and harmful drug residues in meat and eggs limit chemical control. In this scenario, there is a dire need to find alternatives to chemical control. This review mainly highlights the alternates of chemical control i.e. volatile compounds, pheromones, and kairomones. Pheromones and kairomones attract D. gallinae and hamper the parasite growth. While certain volatile compounds and plant extracts exert repellent effects on D. gallinae leading to decreased or no growth. Finally, effective treatments against D. gallinae are required to control infestation in poultry. In the future, different devices that have been tested on species of the Acari genus can be used to control poultry red mites. Keywords: Pheromones, Kairomones, Plant Extracts, Essential Oils, Poultry Red Mite. ![]() |
Genetic Variability Analysis for Achene Yield and Its Related Traits in Sunflower Rana Qammar Uz Zaman, Hafiza Sehrish Rana, Aneeta Rana and Ahmad Muneeb Anwar Int J Agri Biosci, 2023, 12(3): 143-152. ![]() Abstract
Pakistan is deficient in edible oil production. The sunflower being an important oilseed crop due to better oil composition, short duration as a cheapest source of energy and major component of our daily diet can be used for overcoming the gap. In this experiment combining ability was computed for achene yield and its related trait. 15 Genotypes of sunflower were crossed by using line × tester pattern. Out of 15 genotypes, A6, A7, A10, A11, A12, A17, A19, A20, A21 and A26 were taken as females (lines) and A8, A9, A16, A18 and A22 were taken as male (testers) in this experiment. 50 Crosses were made. The parental and F1 cross seeds was sown in randomized complete block design in 3 replications in next growing season. The data was recorded for number of leaves/plant, leaf area, plant height, head angle, fresh head diameter, dry head diameter, No of achenes/head, average yield/plant, 100 achene weight and harvest index. The recorded data was used to estimate the genetic variation among the genetic material. Line × tester analysis was used for estimating combining ability effects of sunflower genotypes. Analysis of variance, Line × Tester and Crosses vs parents showed highly significant differences among the sunflower accessions. Significant and positive GCA was found among lines A10, A21 for average yield and A17, A26 for 100 achene weight. Among testers significant and positive GCA values were found in A9 for average yield, A18 for 100 achene weight. Dominance variance represented that the ratio of GCA: SCA variance for all of the investigated traits is more than unity. All the lines had highest contribution to the total variance which indicated the presence of maternal effects. The findings suggest that crosses can produce heterotic effects which can be utilized for developing sunflower hybrids with high yield potential. Keywords: GCA, SCA, Dominance Variance, Maternal Effects. ![]() |