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
Screening of potato cultivars and management approaches for early blight disease caused by Alternaria alternata in Afghanistan
Potato crop encounters many foliar diseases like early blight caused by Alternaria alternata Fr. (Keissler) which drastically decrease tuber yield. Management of this disease remains as a challenge. The present studies were carried out at Nangarhar University Agriculture Faculty Research Farm in 2020 and at Bati kot in 2021. Ten different potato cultivars of Afghanistan were screened to recognize resistance level against early blight under artificial epiphytotic conditions. Parameters like temperature and relative humidity, disease incidence (DI), disease severity (DS), percent disease reduction, number of tubers per plant and tuber yield were recorded. Lowest DI was recorded in Sabzgul (16.53%) followed by Suria (22.45%) and Surkhgul (24.8%). Minimum DS was found in Surkhgul (46.90%) and Sabzgul (46.30%) that grouped in moderately susceptible category. The cultivars Surkhgul and Suria had similar average tuber numbers (7.00), but highest yield was obtained from Surkhgul (3.40 kg). The experiment on fungicidal cum biological management of early blight was conducted in 2020 at Behsood Farmers Learning and Research center (FLRC) of Behsood, Nangarhar, and at Bati kot in 2021. Out of eight treatments, maximum reduction of DI (47.84%) and DS (64.08%) was achieved by foliar spraying of fungicides Cymoxanil + Mancozeb. In addition, this fungicide contributed maximum tuber numbers (4.50) and highest yield (2.80 kg). It was followed by Azoxystrobin + Difenconazole (2.50 kg), and the bio-control with Trichoderma viride (2.40 kg) in terms of tuber yield. The study was the first of its kind carried out in Afghanistan.
Overview of the lichens of the Ouled Brahim region, Saida (Algeria).
Lichens are rather special living creatures belonging to the cryptogam phylum. In fact, a lichen is an original being resulting from a symbiosis between an alga and a fungus. The aim of our work is to carry out an inventory of the Ouled Brahim region (Saida). To do this, we used the [4] method, which consists of applying a transparent 20x50 cm survey grid to the bark of trees, starting one metre above the ground. This grid is cut into 10 cm2 squares. We collected 8 charts, four for each station (Mimouna and AinKsab). A total of two lichen genera were identified, presented by 4 different species.
Clay Mineral Identification and Mapping Using the Airborne AVIRIS NG Hyperspectral Data in Nagarjuna Sagar Left Bank Canal area and Patancheru Area, Telangana, India
The study demonstrates the application of AVIRIS NG hyperspectral data to identify and map the dominant minerals of the Nagarjuna Sagar Left Bank Canal area and Patancheru area, Southern Telangana Zone, Telangana state, India. The individual AVIRIS NG Hyperspectral image strips were processed with ENVI 5.3 software geocoded, mosaicked and the data is subjected to MNF, performed PPI, n-D visualizer and classification (mapping) for secondary clay minerals was attempted using the Spectral Angle Mapper algorithm. Each mineral spectra have unique absorption value. Clay group (montmorillonite, kaolinite, illite) identified through AVIRIS-NG Hyperspectral remote sensing data, matched with USGS (standard spectral library) spectral library spectra. Using these pixels as end members, the classification of data for clay minerals is attempted and derived map of the clay minerals. Based on the spectral matching of sample points for smectite, kaolinite and illite, AVIRIS NG Hyperspectral image has been classified with SAM. Nagarjuna Sagar Left Bank Command area and Patancheru area, SAM classified image depicted that smectite> kaolinite >illite. The occurrence of these minerals was further confirmed by X-ray diffraction (XRD) analysis. The clay fraction of study area exhibited the characteristic peaks at smectite, kaolinite and illite/mica. Semi-quantitative analysis of clay minerals by means of X-ray diffraction also revealed that smectite was the dominant clay in both the study areas followed by kaolinite and illite/mica. The results of the study areas showed that spectral information data from the AVIRIS NG images can be used for generating the spectral reflectance of clay minerals and it can provide a cost effective method of identifying and mapping the clay minerals.
Assessment of Body Activity and Rumination Time for Early Detection of Heat Stress in Dairy Cows
Heat stress is a major challenge facing the dairy industry, negatively impacting cow health, milk production, and reproductive performance. Early detection of heat stress is critical for implementing timely mitigation strategies. This study evaluated the use of body activity and rumination time measured by HR-Tag sensors for early detection of heat stress in lactating Holstein cows. Cows (n=100) were housed in a free-stall barn and monitored during summer months. HR-Tag sensors measured body activity (bouts/hr) and rumination time (min/hr). Ambient temperature and humidity were recorded to calculate temperature-humidity index (THI). Mixed linear models analyzed relationships between THI and cow activity and rumination. As the temperature-humidity index (THI) increased, rumination time decreased significantly (r = -0.56, P < 0.001), while activity levels increased (r = 0.43, P < 0.05). Compared to normal conditions (THI < 68), cows under mild heat stress (68 ≤ THI < 72) spent an average of 31.59 minutes less per day ruminating (6.16% reduction) and exhibited a 5.1% increase in activity level. Under moderate heat stress (72 ≤ THI < 80), rumination time decreased by 59.55 minutes (11.42% reduction), and activity levels increased by 14.31%. Severe heat stress (THI ≥ 80) had the most pronounced effects, with cows spending 104.26 minutes less per day ruminating (20.35% reduction) and exhibiting a 24.26% increase in activity level compared to normal conditions. Automated monitoring of body activity and rumination time, especially in high producing cows, allows early detection of heat stress before reductions in milk yield and health issues arise. This enables producers to implement cooling and management changes proactively to mitigate negative impacts of heat stress.
FACTORS INFLUENCING OLIVE PRODUCTION FOR SUSTAINABLE DEVELOPMENT IN ARID ENVIRONMENTS OF ALGERIA
This study delves into uncovering the intricate correlations between diverse factors and olive production yields within the El Oued region, focusing on two distinct time frames : 2000 to 2010 and 2011 to 2021. Employing Pearson correlation coefficients as the analytical tool of choice, we explored the interrelationships between key variables namely, the average agricultural land area, land area specifically allocated for olive cultivation, quantities of utilized manure and fertilizer, average counts of temporary and permanent workers, and the average irrigated agricultural land area—against the backdrop of the average yield of olive cultivation. The outcomes of our investigation unveiled a spectrum of correlation strengths, encompassing both positive and negative associations, for each respective time period. These revelations underline the dynamic nature of the relationships between the examined factors and olive production yields, shedding light on potential influences shaping these agricultural outcomes. To unravel the complex interplay between these variables further, this study employed advanced statistical techniques. Multiple linear regression models were developed to tease apart the contributions of individual variables and their collective impact on olive yields. In parallel, a sophisticated random forest model was also harnessed, offering a comprehensive understanding of intricate interactions within the dataset. The culmination of our efforts yielded invaluable insights into the multifaceted determinants underpinning olive production within the El Oued region. By discerning the nuanced relationships between these factors and their cumulative effects on yields, our findings hold significant promise for enhancing agricultural practices and elevating productivity levels. This research contributes not only to the theoretical realm of agricultural science but also holds practical implications, potentially guiding future strategies to optimize olive cultivation in the El Oued region.