AMA, Agricultural Mechanization in Asia, Africa and Latin America (AMA) (issn: 00845841) is a peer reviewed journal first published online after indexing scopus in 1982. AMA is published by Farm Machinery Industrial Research Corp and Shin-Norinsha Co. AMA publishes every subjects of general engineering and agricultural engineering. Azerbaijan Medical Journal Gongcheng Kexue Yu Jishu/Advanced Engineering Science Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Interventional Pulmonology Kongzhi yu Juece/Control and Decision Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) Zhonghua yi shi za zhi (Beijing, China : 1980) Tobacco Science and Technology
AMA, Agricultural Mechanization in Asia, Africa and Latin America (ISSN: 00845841) is a peer-reviewed journal. The journal covers Agricultural and Biological Sciences and all sort of engineering topic. the journal's scopes are in the following fields but not limited to:
Black tomatoes are typically classified according to their ripeness immediately after harvesting to maintain optimal quality and minimize the loss caused by uneven ripening. The ripeness of black tomatoes is traditionally evaluated either visually or using a colorimeter. The visual observation technique is time- and labor-intensive and may yield unreliable results, and the colorimeter-based technique can be implemented for only a small number of tomatoes. To address these problems, this paper proposes a method to effectively classify the ripeness of black tomatoes based on machine vision and YOLOv4. A total of 4,080 digital images of Black Change, a variety of black tomatoes, were collected by capturing the top, bottom, left side, and right side of each sample in illuminance conditions of 570 lx, 1,240 lx, and 2,780 lx. The results showed that the model trained with images gathered under a single illuminance condition could effectively classify the ripeness for images with the same condition. When images with mixed lighting conditions were used, the model achieved a classification performance of nearly 100%. However, its performance deteriorated when the model trained with an independent illuminance condition applied to the images for other conditions. The model trained with over 1632 images in mixed illuminance conditions for over 3000 iterations achieved a classification accuracy of at least 96.00%, and time required for image collection, labeling, and training was minimized.
This study was aimed at finding an optimum pre-treatment method and parameters for convective drying of pumpkin for preparation of flour to maximize the retention of nutrients, for the production of pumpkin flesh powder. Artificial Neural Network (ANN) was employed for modeling of drying conditions to obtain powders with desired properties. For this, the pumpkin (Cucurbita moschata) flesh was subjected to blanching (90ᵒ C for 5 minutes) and citric acid treatment (0.1% acid for 30 minutes). Then they were subjected to cabinet drying at temperature and drying time varied at five levels. ANN modeling was performed using three different training functions and at two levels of hidden layers. The physico-chemical analysis had shown that blanching treatment came out with best physical properties and higher retention of nutrients when compared to the control and acid treated samples. The values of co-efficient of determination (R2), Root mean square error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were used to determine the training function and hidden layer combination for each response variable for their prediction with highest accuracy.
Several empirical studies have assessed the impacts of transgenic crops on farms and overall in industrialized and developing nations, although there is significant opposition in the larger audience. Particularly, questions have been raised over the environmental, medical, and social impacts of transgenic crops in developing nations. By examining the consequences of insect-resistant transgenic cotton in India and drawing on several years' worth of data, this study fills in some of these knowledge gaps. The findings show that Bt technology is quite popular in India. By reducing their use of pesticides, increasing their yields, and increasing their profitability, adopting farmers have experienced tremendous gains. These results, which are based on a distinctive dataset, extend and confirm earlier research on the effects of Bt cotton in India and other poor nations. The majorities of growers were in favour of growing bt cotton and intended to continue doing so in the future. They believed that the intense bt cotton production would have significant social, economic, environmental, ethical, and biosafety ramifications in the near future. This data on bt cotton growers' perceptions and experiences will help researchers, extension workers, and policymakers develop effective strategies for both current bt cotton and upcoming transgenic crops.
The study was conducted in College of Horticulture, Venkataramannagudem, and College of Horticulture, Anantharajupeta, Dr.YSRHU, Venkataramannagudem in Andhra Pradesh state. The data collected from the graduates of two constituent colleges. Thus total 120 respondents were selected by using random sampling method. The majority of respondents were female, having rural background and had medium annual income ranged from Rs.1,51,832/- to 9,42,835/-, with marginal land holding. Majority of the respondent parents were in government service. Most of the respondents secured first class during their graduation with low participation in extra curricular activities. Majority of the respondents had medium level of decision making ability, achievement motivation, hortibussiness anxiety, innovativeness and risk orientation. Majority of respondents had medium level of personal entrepreneurship capability, sensitizations, and medium level of interest in studying the hortipreneurial concepts and medium level of tendency ie, level of inclination or likeliness towards hortipreneurship and they were having favorable attitude towards hortipreneurship.
The sustained rice yield plays an important role in the country’s GDP. Nowadays the key factors for enhanced growth and optimized yield of rice are often related to an appropriate crop establishment method (CEM), efficient nutrient fertilizer management (NFL), and sensible weed management practice (WMP). And therefore, the prime objective of this study was to standardize the CEM, NFL and WMP for sustained the optimized growth and yield of hybrid rice. The results disclosed that puddled transplanting rice (TPR) significantly enhanced rhizospheric and phyllospheric growth (plant height, tillers m-2, DMP, CGR, LAI, LAD, root volume and root biomass) and produced a significantly higher yield than un-puddled transplanting rice (UTPR) and dry direct seeding rice (DDSR). Application of 100% NFL registered the better growth with sustained yields though remained statistically identical with 125% NFL and both showed significant superiority over 75% NFL applied to the crop. However, herbicide layering (CW) of bispyribac-sodium 20g a.i. + pyrozosulfuron 20g a.i. was sprayed at 20 DAS/T in rice field had effectively controlled the weed flora associated though produced slightly a lesser yield productivity when compared to weed-free (HW) and both exhibited the maximum phyllospheric and rhizospheric growth with sustained yield over other two WMPs nonetheless failed to prove more remunerative than brown manuring (BM).