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 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)
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:
Experiments were conducted during three consecutive Kharif seasons at the Experimental Farm of Agricultural Research Station, Navgaon, Alwar (Rajasthan), to study the effect of commercially available insecticides formulations, Acetamaprid 20 % SP (1.0 gm/ litre of water), Imidacloprid 17.8 % SL (1.0 ml/ lit.), Quinalphos % 25 EC (2.0 ml/ lit.), Thiomethoxam 25 % WG (1.0 gm/ lit.), Neem oil 2% (20 ml/lit.), Karanj oil 2% (20 ml/lit.) against the White fly, Bemisia tabaci in Clusterbean. The descending order of most effective insecticides was: Imidacloprid > Thiomethoxam> Acetamaprid. During the 2015 year the maximum population reduction over control was found after 7 days of applying the second spray at 15 days of interval viz., 82.17 and 77.91 per cent due to Imidacloprid, Thiomethoxam, respectively. A similar trend was found in 2016 and 2017. Thus, Imidacloprid was found most effective against the White fly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae).
Induced mutagenesis in crop plants has created avenues for improving desirable genetic changes without altering the unique genetic background of the promising cultivars. A study was carried out to find the efficiency and effectiveness of 0.2% Ethyl Methane Sulfonate (EMS) mutagen on four popular but tall local aromatic rice landraces, Kalikati, Basumati, Gangabali and Karpurajeera by treating the calli initiated from their mature embryos for three different durations (2 hours, 4 hours and 6 hours). A reduced shoot regeneration efficiency was witnessed in Kalikati and Basumati (59.54% and 61.10% reduced respectively) while it increased in Gangabali and Karpurajeera (23.32% and 29.76 % increased respectively) with increasing treatment duration, compared to control. Among the four types of chlorophyll mutants observed, albina were most frequent in all the genotypes except Basumati, where virdis mutants followed by albina were highest whereas, in Kalikati, chlorina mutants were followed by albina in high frequency. In general, mutagenic effectiveness and efficiency were reduced with an increase in the duration of treatment in all the genotypes except in Basumati and Karpurajeera where mutagenic efficiency was highest at mid-treatment duration (4 hours). Mutation rate of 10.68 observed in Basumati was the highest among the genotypes indicated high mutagenic effect on the calli of this aromatic rice landrace. Genotypic differences in frequency of mutants, effectiveness and efficiency of the mutagen on the aromatic rice genotypes were clearly evident. This research will be useful in mutation breeding programmes, involving economically important crops, within a limited time and space.
The estimation of crop phenological distribution is of great importance for controlling time of thinning flowers. In order to improve the efficiency of flower thinning in modern orchard, a detection method of apple flower phenological distribution based on YOLO-CG network model is proposed to detect, which aims at improving incomprehensive and low-efficient manual traditional detection method of apple flower phenological distribution. First of all, the YOLO-CG network model is to integrate the CA mechanism into the YOLOv5 network, which could obtain more shallow features to improve network performance; Secondly, in order to improve the training speed to reduce the calculation amount of the network model, the Ghost-Bottleneck module is proposed to replace the Bottleneck module; Finally, the CIOU is used as the bounding box regression loss function to improve the stability of the target box regression. The model is fine-tuned and trained with manually-marked apple flower images in 4 phenological stages. The proposed method was compared with the detection models of YOLOv3, YOLO v4, YOLO v5 and Faster R-CNN, and the detection performance of apple flower under different shooting conditions are discussed, which proves the effectiveness of this method. Experimental results show that the mAP value of apple flower detection at different stages was 94.90%, an increase of 1.98%, 7.1%, 5.42% and 2.53% respectively compared with Faster R-CNN, YOLO v3, YOLO v4 and YOLO v5.
Root rot is a serious threat to the sesame crop, causing a significant yield loss in Odisha, India. Ten isolates were recovered from different geographical locations in Odisha, India, to understand the relationship among phenotypic characteristics, virulence, and genetic base of the pathogen Macrophomina phaseolina. Genetic diversity analysis using four ISSR primers generated twenty-seven bands with 71.9% polymorphism. The PIC value ranged from 0.59 to 0.663, with a maximum PIC value in ISSR9. UPGMA grouped isolates into three distinct clusters with 60 % genetic similarity. The ordination of isolates in the dendrogram and PCA analysis showed a consistent relationship of geographic origin with the genetic base of the pathogen. A similar grouping pattern was observed based on phenotypic traits and virulence of isolates. All isolates exhibited a significant variation in phenotype (colony colour, colony type, growth rate, aerial mycelium microsclerotia size, shape, colour, and abundance) and virulence (against cultivar VRI- 1). In addition, a negative correlation was observed between the sizes of microsclerotia with virulence. The findings confirm a considerable variation among the isolates and a strong relationship between phenotypic characteristics, virulence, and the genetic base of the pathogen. Knowledge of these characteristics may help to understand the population structure of the pathogen.
Internet of Things (IoT) has been a serious influence in agriculture since its application to the sector. This paper provides an in depth review of the employment of good technologies in agriculture and elaborates the progressive technologies for good agriculture together with, web of Things, cloud computing, machine learning, and computer science. The application in smart agriculture in crop production and post-harvesting is mentioned. The impact of climate change on agriculture is additionally thought-about. This paper contributes to information by iterating the challenges of good technology to agriculture whereas lightness the problems known from existing framework of smart agriculture. The authors determine several gaps in existing analysis affecting the application of IoT in smart agriculture, and counsel any analysis to boost the current food production globally, to supply higher food management and property measures across the world.