AMA, Agricultural Mechanization in Asia, Africa and Latin America
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.
WOS Indexed (2026)
07 May 2026 (Vol - 57 , Issue- 05 )
31 May 2026 (Vol - 57 , Issue 05 )
Aim and Scope :
AMA, Agricultural Mechanization in Asia, Africa and Latin America
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:
Agricultural and Biological Sciences
Electrical Engineering and Telecommunication
Electronic Engineering
Computer Science & Engineering
Civil and architectural engineering
Mechanical and Materials Engineering
Transportation Engineering
Industrial Engineering
Industrial and Commercial Design
Information Engineering
Chemical Engineering
Food Engineering
EFFECT OF PHOSPHORUS AND SULPHUR MANAGEMENT ON YIELD, NUTRIENT UPTAKE, AND NUTRIENT USE INDICES IN RICE BEAN (VIGNA UMBELLATA L.)
The Rice Bean (RB) (Vigna umbellata L.), which is native to South and Southeast Asia, is an annual underutilized grain legume crop that belongs to the family Fabaceae. It has a higher nutritional quality compared to many other legumes within the Vigna family. Yet, there is a lack of understanding of the impact of plant nutrients on the diverse attributes of RBs. Therefore, the research aims to examine the effect of diverse levels of Phosphorus (P) along with Sulphur (S) on the yield, Nutrient Uptake (NU), and nutrient use indices of RB crops. During the Kharif seasons of 2017-18 and 2018-19, a field experiment is conducted at an agricultural research farm in West Bengal. A total of 3 diverse levels of P and S are tested with Factorial Randomized Block Design (FRBD) (3×3+1 factorial). As per the outcome, an application of 30kg/ha S along with 80kg/ha P has recorded higher yield, nutrient content and uptake, and nutrient use indices of RB crop.
DEEP LEARNING-DRIVEN STREAM FLOW FORECASTING: A NOVEL APPROACH
Precise streamflow forecasting is essential for managing water resources, controlling flooding, planning irrigation, and guaranteeing agricultural sustainability. This study employs 38 years of monthly flow of the stream data from the Cholachagudda dam on the Malaprabha River, India, to evaluate and compare the performance of deep learning models, including CNN, RNN, LSTM, GRU, and a Transformer-based architecture. With the lowest RMSE (76.02), MAE, and quantile loss (20.72), the Transformer model performs better than alternative topologies, according to the dataIt overcomes the drawbacks of sequential models like LSTM and GRU by successfully identifying complicated temporal patterns and long-range relationships through its self-attention mechanism. This study highlights the challenges of predicting streamflow in non-linear hydrological systems, particularly for models limited to temporal data. By offering a thorough assessment, this study highlights the revolutionary potential of deep learning in hydrological forecasting and establishes the foundation for future developments in streamflow prediction techniques.
Characterization of Thanjavur Black Goats of Tamil Nadu
The habitat, distribution, morphology, morphometric and production performance of the Thanjavur Black goats were studied by a pretested interview schedule in the eastern districts of Tamil Nadu. A study was undertaken on 250 randomly selected goat flocks in Thanjavur, Nagapattinam, Thiruvarur, Tiruchirappalli and Pudukkottai districts of Tamil Nadu. Thanjavur Black goat is a compact, medium-sized, black-coloured animal. Coat is uniformly black and covered with short, straight black hair. The least squares means of height at withers, chest girth and body length of an adult goat were 61.59 ± 0.17, 59.71 ± 0.21 and 58.08 ± 0.25 cm respectively. The least squares means for body weight at birth, 3, 6, 9, 12 months and adult goats were 1.82 ± 0.02, 5.99 ± 0.05, 9.30 ± 0.07, 12.12 ± 0.09, 14.16 ± 0.08; and 22.63 ± 0.22 kg respectively. In all age groups of Thanjavur Black goats, the statistical analysis revealed a highly significant (P <0.01) effect of sex on body weight were observed. The overall dressing percentage was 51.02% at 20.63 months. The average age at first mating, age at first kidding and kidding intervals were 9.58 ± 0.10, 14.93 ± 0.10 and 7.89 ± 0.15 months respectively. The life time number of kidding in a doe was 6.66 ± 0.09. The average litter size of the does pooled over parities was 1.71 ± 0.03 and the incidence of multiple births was 57.21 per cent. This indigenous germplasm needs to be recognized by the NBAGR, Karnal as a separate breed.
Emergency Room Risk Assessment with L-Type Matrix
The commonly used definition of “risk” in the literature is the probability of an undesirable event/occurrence taking place within a specific time frame. This requires a comprehensive risk analysis to identify these undesirable events/occurrences, calculate the severity of the associated risk, and determine whether the risk is tolerable. While risk analysis is essential for all organizations regardless of their size, the type of risk analysis to be performed, the methodology to be used, and the development of solutions to risks are determined by the type of company. Healthcare facilities require special care when it comes to risk analysis practices, as they are crucial for the health and safety of both patients and staff. Because of this, picking the right methodology, figuring out the risks, and sorting them based on how serious they are is super important for hospital management. This study, which aims to provide services within the scope of this work, conducted a risk assessment for an Emergency Room (ER) employee at the third level healthcare institution using the Risk Assessment Matrix (L-Type Matrix) approach for the purposes mentioned above.
SEBACEOUS GLAND ADENOMA AND SEBACEOUS GLAND ADENOCARCINOMA IN DOGS: INCIDENCE AND PATHOLOGICAL DIAGNOSIS OF 54 CASES
Sebaceous gland tumours were diagnosed in 54 dogs through cytological and histopathological examination of samples obtained from tumour-suspected masses. Among these, sebaceous gland adenomas accounted for 24 cases, while sebaceous gland adenocarcinomas comprised 30 cases. In the breed, sex, age, and anatomical location-wise analysis, the highest incidence of sebaceous gland adenoma was recorded in Labradors, male dogs, within the 5–10 years age group, with a predilection for the limbs. Similarly, sebaceous gland adenocarcinoma showed the highest occurrence in Labradors, male dogs, of the same 5–10 years age group, but were more commonly located on the trunk and ears. Sebaceous gland adenomas exhibited clusters of neoplastic basal cells with round to oval nuclei, finely stippled chromatin, and vacuolated cytoplasm resembling mature sebocytes cytologically, and in histopathological examination, revealed clusters of neoplastic cells arranged in multiple lobules and basophilic reserve cells with hyperchromatic nuclei. Sebaceous gland adenocarcinomas revealed variably sized cell clusters with hyperchromatic nuclei, coarse chromatin, and foamy cytoplasm cytologically, and in histopathological examination, lobules of variably sized neoplastic cells exhibiting anisokaryosis, vesicular nuclei with prominent nucleoli, and frequent mitotic figures were seen.