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)
30 Jun 2026 (Vol - 57 , Issue- 07 )
31 Jul 2026 (Vol - 57 , Issue 07 )
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
PROBLEMS AND SUGGESTIONS OF FARMERS FOR EFFECTIVE TANK IRRIGATION MANAGEMENT IN TELANGANA, INDIA
The study was conducted in Telangana state to know the problems and suggestions of farmers for effective tank irrigation management under mission kakatiya programme. Quasi-experimental research approach was followed for the study. The investigation was carried out in Karimnagar, Kamareddy, Mahabubnagar, Nalgonda, Siddipet and Badradri Kothhagudem districts of Telangana state. One mandal was selected from each district for the study. One village each selected randomly from each mandal separately for beneficiaries and non - beneficiaries. 30 farmers from each village were selected at random to make a sample of 180 respondents from beneficiary and non – beneficiary villages for the study. Findings with respect to problems and suggestions of farmers for effective tank irrigation management revealed that major problems elicited by the beneficiary farmers in tank irrigation management related to tank management were infestation of weeds in tanks, uneven distribution of tank silt among the farmers etc., related to tank irrigation management were poor knowledge of farmers on new irrigation technologies, Poor knowledge of tank users on crop planning etc. and related to group management lack of efficient leadership in farmers, lack of organization of regular group meetings etc. Problems elicited by the non-beneficiary farmers in tank irrigation management related to tank management were decreased water storage capacity of the tank due to siltation, infestation of weeds in tanks etc., related to tank irrigation management were poor knowledge of tank users on crop planning, unavailability of water during critical stages of crop growth period etc., and related to group management lack of efficient leadership in farmers, lack of organization of regular group meetings etc. Suggestions offered by the beneficiaries in tank irrigation management related to tank management were weeds should be removed frequently from the tank to keep the tank clean through involvement of community, officials should form groups for equal distribution of tank silt to the farmers, related to tank irrigation management All concerned departments should conduct the training programmes and method demonstration on new irrigation technologies, conduct the training programmes on crop planning and involves farmers in planning etc., and related to group management were select the efficient leader by conducting group discussion under facilitation of Extension officers, Organize the group meetings twice in month etc. Suggestions offered by non-beneficiary farmers related to tank management were Department of irrigation should implement the Mission Kakatiya programme to desilt the tanks, weeds should be removed frequently from the tank to keep the tank clean through involvement of community etc., related to tank irrigation management were conduct the training programmes on crop planning and involves farmers in Planning, release the water based on crop growth stages instead of rotational basis of water etc., and related to group management were select the efficient leader by conducting group discussion under facilitation of Extension officers, Organize the group meetings twice in month etc.
Evaluation of Azadirachta indica as a Plant-Based antimicrobial agent against Staphylococcus aureus
Staphylococcus aureus is an important Gram-positive pathogen responsible for a wide range of infections in humans and animals, including mastitis, skin infections, and systemic diseases. The increasing resistance of S. aureus to conventional antibiotics has encouraged the exploration of plant-based antimicrobial agents as potential alternatives. The present study evaluated the In-vitro antibacterial efficacy of aqueous leaf extract of Azadirachta indica against Staphylococcus aureus isolates obtained from small ruminants and their human handlers. Antibacterial activity of the neem extract was assessed using the agar well diffusion method, along with determination of the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). The neem extract demonstrated concentration-dependent antibacterial activity against S. aureus isolates, producing a maximum zone of inhibition of 15.5 mm at higher concentrations. Both MIC and MBC were recorded at 125 mg/mL, indicating a bactericidal effect of the extract. The findings suggest that Azadirachta indica possesses significant antibacterial activity against Staphylococcus aureus and may serve as a promising herbal alternative to conventional antibiotics. Further studies are required to isolate active phytochemicals and evaluate their therapeutic applicability.
Factors Affecting the Sugarcane Yield and Sucrose Accumulation Influencing Efficient Biofuel Production
The persistent reliance on fossil fuels, contributing significantly to global energy consumption and environmental degradation, necessitates alternative renewable energy sources such as biofuels. Sugarcane, a C4 crop with high biomass and sugar content, serves as a prime feedstock for first- and second-generation bioethanol production. This study evaluated ten diverse sugarcane genotypes at the Punjab Agricultural University Regional Research Station, Kapurthala, during 2022–23 to assess morphological and biochemical traits, including stalk length, sugar content, and fibre to infer bioethanol production potential of genotypes. Statistical analyses revealed genotype-dependent variability, underscoring the need for selecting high-yield, cost-effective carbohydrate sources for sustainable bioethanol production. Genotype CoPb18213 demonstrated superior performance in biomass yield and juice quality, making it a promising candidate for integrated first- and second-generation biofuel production. The findings underscore the importance of integrating high-yielding genotypes with efficient crop management and mechanization practices to enhance biomass utilization, reduce post-harvest losses, and improve overall biofuel production efficiency. This study provides valuable insights for the development of sugarcane varieties optimized for sustainable and economically viable bioenergy production.
EVOLUTION OF TIME SERIES MODELS FOR AGRICULTURAL FORECASTING: A REVIEW OF STATISTICAL, MACHINE LEARNING, AND DEEP LEARNING APPROACHES
Accurate forecasting of crop yields plays a pivotal role in ensuring food security, guiding policy decisions, and optimizing resource management. This review brings together more than fifty years of progress in time series forecasting for agriculture, tracing the evolution from classical statistical approaches (1970s–1990s) to advanced time series models (1990s–2010s), and most recently to deep learning architectures (2015–2025). The methods examined include multiple regression, principal component analysis (PCA), logistic regression, autoregressive integrated moving average (ARIMA) models, state space formulations, and a growing array of machine learning techniques such as long short-term memory (LSTM) networks, convolutional neural networks (CNN), and Transformer-based models. Through a structured comparative lens, this review assesses the strengths, limitations, data requirements, and computational demands of each methodological category. The findings underscore that no single approach is universally optimal; the choice of model depends on factors such as data availability, forecast horizon, computational capacity, and the specific agricultural context. Recent advances highlight the promise of hybrid models that integrate complementary techniques, offering improved predictive accuracy while preserving interpretability. A central challenge identified is climate non-stationarity, which calls for adaptive forecasting methods. At the same time, the convergence of advanced analytics, satellite remote sensing, IoT sensor networks, and climate science is opening unprecedented opportunities for agricultural prediction. Looking ahead, future research directions include the development of climate-adaptive forecasting systems, hybrid frameworks that combine mechanistic and learning-based approaches, and explainable artificial intelligence tailored to agricultural applications.
In vitro evaluation of fungicides against Sclerotinia sclerotiorum (Lib.) de Bary causing white mold of French bean (Phaseolus vulgaris L.)
White mold caused by Sclerotinia sclerotiorum is one of the most destructive diseases of French bean (Phaseolus vulgaris L.), leading to severe yield losses under favourable conditions. The present investigation was undertaken to evaluate the in vitro efficacy of selected fungicides against S. sclerotiorum with the objective of identifying the most effective fungicide for managing the disease. Six fungicides, viz. azoxystrobin 45% + chlorothalonil 40%, copper oxychloride 50% WP, mancozeb 75% WP, thiophanate methyl 70% WP, chlorothalonil 75% WP and hexaconazole 5% EC (considered as check), were tested at three concentrations (0.10, 0.20 and 0.30%) against the pathogen S. sclerotiorum using the poisoned food technique. Among the fungicides, azoxystrobin 45% + chlorothalonil 40% recorded complete (100%) inhibition of mycelial growth at all concentrations, followed by thiophanate methyl (57.78 %) and mancozeb (56.67%). Moderate inhibition was observed with chlorothalonil (54.44%), copper oxychloride (65.56%), and hexaconazole (70.00%). The strong inhibitory effect of azoxystrobin-based fungicide corroborates earlier reports on disruption of mitochondrial respiration in S. sclerotiorum. The study highlights the potential of the effective chemical for the management of white mold of French bean and provides baseline information for further validation under field conditions.