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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.

Submission Deadline
03 Jul 2022 (Vol - 53 , Issue- 07 )
Upcoming Publication
31 Jul 2022 (Vol - 53 , 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:

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 Interventional Pulmonology (middletown, de.)
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

Study on the Influence of PCA Pre-treatment on Pig Face Identification with RF

Paper ID- AMA-14-12-2021-10954

To explore the application of traditional machine learning model in the intelligent management of pigs, in this paper, the influence of PCA pre-treatment on pig face identification with RF is studied. By testing method, the parameter of two testing schemes, one adopting RF alone and the other adopting RF+PCA, were determined to be 65 and 70, respectively. With individual identification tests carried out on 10 pigs respectively, accuracy, recall, and f1-score were increased by 2.66, 2.76, and 2.81 percentage points, respectively. Except for the slight increase in training time, the test time was reduced to 75% of the old scheme, and the efficiency of the optimized scheme was greatly improved. It indicates that PCA pre-treatment had a positive effect on improving the efficiency of individual pig identification with RF. It provides experimental support for the mobile terminals and embedded application of RF classifiers.

The Levers For Improving Irrigated Durum Wheat Performances: Evidence from Jendouba region in North Tunisia

Paper ID- AMA-13-12-2021-10953

In Tunisia, despite the outstanding development of the production technologies, the achieved yields of the irrigated durum wheat are still under expectations. This work aims to establish an operational diagnosis of the irrigated durum wheat activity and to identify alternatives for improving its performance. In order to deal with this issue, a field survey was carried out among a sample of 77 farmers cultivating durum wheat. Using CROPSYST software, a crop model was developed and scenarios of good practices were simulated. The results showed that we are able to rise the yields up to 20% and to improve the water productivity and the gross Margin. Hence results proved that matching water intakes and crop rotation constitutes relevant practices to ensure better agronomical and economical performances. The concretization of these paths requires a concerted reflection between the actors to put forward suitable strategies according to the studied context.

Ethnobotanical approaches of local plants of lodhran district, Punjab, Pakistan.

Paper ID- AMA-13-12-2021-10952

The present study is conducted to gather the native awareness of therapeutic plants of Lodhran District, south Punjab, Pakistan, and documentation of remarkable wild plants. The area hasten been studied before for his purpose. The area is rich in medicinal plans and local people are using I for various ailments. This study was donein 2019. The information was collected through specific questionnaires and field trips and local health care professionals including Hakeems, Daii, and Peer (Spiritual Healers) were interviewed. Documented plants were further identified by Flora of Pakistan. An overall of 66therapeutic plants with 36 families was acknowledged through various field trips and with detailed interviews of the specific people in the community and their local names and folk uses are described along with their dosage forms.

Detection of peanuts mildew based on hyperspectral image

Paper ID- AMA-13-12-2021-10951

Peanut mildew can produce aflatoxin with strong toxicity. A nondestructive and rapid detection method of peanut mildew based on hyperspectral technology was proposed. Firstly, 600 Dabaisha peanuts purchased in the market were selected, and 200 peanuts were randomly selected for mildew treatment, while the remaining 400 peanuts were kept aseptically. After 30 days, the spectral images of all peanut samples were collected by using the Zhuoli Huanguang Hyperspectral Instrument and the SpaceView was used for black and white correction. Then the ROI of each peanut spectral image was extracted with ENVI5.1 software and the Mean spectral reflection value of the region was calculated to obtain the sample spectral data, the reflection curves of moldy peanuts and healthy peanuts were observed, and it was found that there were significant differences between 500nm-600nm, so the mold visualization of moldy peanuts was carried out within this interval. In order to eliminate the influence of non-quality factor information in the hyperspectral data, three spectral preprocessing methods were adopted to eliminate the noise in the original spectral data. XGBoost, LightGBM and RandomForest algorithms were run to model the characteristic bands and detect the moldy peanuts. In all models, the accuracy of the algorithm could reach 100%, the similarity indexes all reached 1, and the loss was all 0. In terms of FIT_TIME, XGBOOST had the best performance, only requiring 0.042s, which was significantly different from other algorithms. The results showed that XGBOOST model was the most suitable algorithm for detecting peanut mold. This study provides a strong theoretical basis and technical support for the monitoring and identification of healthy and moldy peanuts in peanut processing industry.

Responses of the Antioxidative enzymes of few Sub1 rice (Oryza Sativa) genotypes to prolonged submergence stress in Odisha

Paper ID- AMA-12-12-2021-10949

The present experiment was conducted in Department of Plant physiology, OUAT, Bhubaneswar during kharif 2017 and kharif 2019 to screen out the NILs rice genotypes for submergence adaptation traits under coastal regions of Odisha. The potential involvement of activated oxygen species by submergence stress was studied in twenty rice genotypes thirteen sub1 NILs, two tolerant checks with six susceptible checks. These rice genotypes were subjected to 17 days of complete submergence. Under 17 days of complete submergence and after the submergence, the genotypes IR-85086-Sub 33 -3-2-1 and IR-88760-Sub 93-3-3 showed lower lipid Peroxidation in terms of malondialdehyde (MDA) level and also showed lower levels of ACC Oxidase activity (AAO) and presented higher activities of antioxidative enzymes, superoxide dismutase (SOD), catalase (CAT), Peroxidase (POX) when compared to the susceptible checks. The levels of SOD activity indicated that detoxification of O2 - to H2O2 was maintained at a stable level throughout the submergence stress until up to 17 days in tolerant genotypes. These findings suggested that tolerance to submergence stress in rice might be proven by increased the capacity of antioxidative system. In addition, SOD and CAT activity has much higher affinity for scavenging H2O2 than POX. The present study evaluated thirteen pairs of Sub1 near-isogenic lines (NILs) together with FR13A and other check genotypes in pot culture conditions to assess the survival and growth processes occurring during submergence and recovery that are associated with Sub1.