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 (2025)
27 Nov 2025 (Vol - 56 , Issue- 11 )
30 Nov 2025 (Vol - 56 , Issue 11 )
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
Perception of Input dealers on Diploma in Agricultural Extension Services for Input Dealers (DAESI) program
Agriculture and allied industries are major contributors to India’s wealth and GDP. Public extension services aim to support farmers but have limited reach. With the help of input dealers, farmers can access modern techniques. Strengthening these services is vital to doubling farmers’ income. The study was conducted in 2025 to analyze the perception of agricultural input dealers towards the DAESI program and to determine the direct, indirect, and largest indirect effects of their profile characteristics on perception. Fifty DAESI input dealers trained by DATC, Davanagere during 2018–2022 were selected as respondents. The results revealed that 46.00 per cent of the dealers had a better perception, 30.00 per cent had a good perception, and 24.00 per cent had a poor perception of the DAESI program. Based on direct effects, entrepreneurial orientation (X13), mass media exposure (X14), and extension participation (X12) were ranked as the top three influencing factors. Similarly, for indirect effects, mass media exposure, entrepreneurial orientation, and extension participation occupied the first three ranks. Path analysis indicated that these three variables had the most significant direct, indirect, and largest indirect effects on enhancing perception. The study suggests that improving classroom teaching, practical sessions, record maintenance and assignments can further enhance input dealers’ perception of the program. Additionally, organizing regular entrepreneurship development training and involving DAESI-trained dealers in extension activities such as demonstrations and farmer interactions can strengthen their engagement and perception towards the DAESI program.
Host Plant Resistance of Rice genotypes against Brown Spot disease under Field Conditions
Rice (Oryza sativa L.) plays a pivotal role in ensuring food security, particularly in Asia, where it sustains a majority of the population. Brown spot, caused by Drechslera oryzae, is a significant foliar disease affecting rice productivity, especially under rainfed and humid conditions. Effective screening and identification of resistant genotypes remain vital for developing durable resistance. In this context, a field study was conducted during Kharif 2023 at Bihar Agricultural University, Sabour, to evaluate 208 rice genotypes of the Donor Screening Nursery (DSN) for resistance to brown spot. Genotypic screening revealed substantial variation in disease reaction. None of the genotypes exhibited complete immunity (disease score ‘0’), while 17 genotypes- KNM115, KNM15361, KNM15236, 19202, 19026, 19027, 680-2, RP-Patho-1, RP-Bio-Patho-10, BPT 5204, C101LAC, C101A51, RNR 31581, RTCNP-10, RTCNP-138, NLRBL-8, and NLR 3595—were identified as resistant (disease score ‘1’). Additionally, 42 genotypes were moderately resistant, 68 moderately susceptible, 61 susceptible, and 20 highly susceptible. The identification of resistant sources through such large-scale screening forms the foundation for resistance breeding and informs integrated disease management strategies to mitigate brown spot impact in rice-growing regions of Eastern India.
Molecular identification and Phylogenetic Relationships of Erysiphe pisi causing Powdery mildew of Fieldpea (Pisum sativum L.)
Powdery mildew fungi, primarily belonging to the genus Erysiphe, are among the most destructive obligate biotrophic pathogens, infecting a wide range of plants and causing significant yield losses worldwide. Accurate species-level identification is essential for understanding host specificity, disease epidemiology, and devising management strategies. However, morphological features used in traditional taxonomy are often insufficient, as conidial morphology and chasmothecial characters may be variable or absent under natural conditions. Molecular tools, especially sequencing of the internal transcribed spacer (ITS) region, have greatly improved the resolution of fungal taxonomy and are widely applied in powdery mildew systematics. In the present study, we analyzed 17 Erysiphe isolates collected from Fieldpea in Central U.P region to assess their molecular diversity and phylogenetic affiliations. ITS sequences were subjected to BLAST searches, multiple alignment, and phylogenetic reconstruction using the Maximum Likelihood method with bootstrap support.. The isolates grouped into major clades, corresponding to known species such as E. pisi. The study demonstrates the presence of substantial sequence variation among Erysiphe isolates and underscores the utility of ITS-based molecular identification in resolving complex taxonomic relationships. Our findings contribute to the understanding of Erysiphe diversity in Central U.P region and provide a foundation for future studies on host–pathogen interactions and disease management.
In vitro evaluation of anthelmintic potential of aqueous and ethanolic leaf extracts of Azadirachta indica and Vitex negundo in benzimidazole-resistant Haemonchus contortus of sheep
This study aimed to evaluate the anthelmintic potential of aqueous and ethanoic leaf extracts of Azadirachta indica and Vitex negundo against benzimidazole-resistant Haemonchus contortus of sheep. A total of 560 dung samples collected from organized sheep farms in Salem, Karur, Kanniyakumari, Kancheepuram and Thiruvallur districts of Tamil Nadu were examined by FECRT to assess the development of resistance to benzimidazole (BZ). The samples from Kancheepuram and Thiruvallur districts showed resistance to benzimidazole by FECRT. The allele-specific PCR (AS-PCR) revealed amplification of a 250bp fragment which confirmed resistance to benzimidazole in samples from Kancheepuram and Thiruvallur districts. Aqueous leaf extracts (ALE) and Ethanolic leaf extracts (ELE) of A. indica and V. negundo at different concentrations viz., 5, 10, 20 and 50 mg/mL, were tested against resistant H. contortus of sheep reared in these farms with BZ resistance. The maximum of 35.42±1.87% inhibition of egg hatch was observed in aqueous leaf extracts (ALE) of A. indica with 50 mg/mL concentration compared to 26.67±1.23 % inhibition of egg hatch in ethanolic leaf extract (ELE). Whereas, the maximum efficacy (%) in egg hatch assay observed in ALE and ELE of V. negundo were 11.67±1.67 and 5.00±0.91, respectively in 50 mg/mL concentration. The maximum mean larval paralysis observed in ALE and ELE of A. indica were 28.89±1.11% and 26.67±1.23 % respectively in 50 mg/mL concentration at 60 min. Whereas, the maximum mean larval paralysis observed in 50 mg/mL concentrations of ALE and ELE of V. negundo were 13.44±1.41 and 7.23±0.55, respectively, at 60 min. It was observed that ALE and ELE of A. indica and V. negundo produced a dose-dependent increase in efficacy in the inhibition of egg hatch and mean larval paralysis. It is concluded that A. indica and V. negundo could be the promising phytomedicines for the alternative control strategy of benzimidazole-resistant nematodes of sheep.
A Review of GLCM, SVM, and MSVM for Early Disease Diagnosis in Sustainable Cotton Farming
This research paper takes a close look at how the grey-level co-occurrence matrix (GLCM), support vector machine (SVM), and multi-class support vector machine (MSVM) methods for texture analysis can be used to find diseases that affect cotton crops. In the field of agriculture, Cotton is vital as the world economy mostly depends on it. Still, the sensitivity of the cotton crop to several diseases seriously jeopardizes productivity and quality. Integration of sophisticated image processing and machine learning techniques has become a potential answer for early and accurate disease identification to handle this problem. The first part of this review emphasizes the need for cotton crops in agriculture and the need for strong disease-detecting techniques. A comprehensive examination of the GLCM approach is presented, focusing on its ability to extract textural features from images. The SVM method is then evaluated for its relevance to disease detection in cotton crops and its efficacy in classification tasks. This paper also discusses the MSVM, a sophisticated variation of the SVM that enables concurrent classification of many categories. Comparative studies are undertaken to assess the advantages and disadvantages of GLCM, SVM, and MSVM for disease detection in cotton crops. The review of significant studies and implementations facilitates comprehension of the beneficial outcomes of these strategies. Moreover, challenges and potential areas for improvement in current methodologies are discussed, setting the stage for future research directions. The overarching objective of this review is to offer a consolidated understanding of state-of-the-art techniques for detecting diseases in cotton crops and to guide researchers, practitioners, and policymakers in implementing effective and scalable solutions for sustainable cotton cultivation.