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 Kongzhi yu Juece/Control and Decision 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) Tobacco Science and Technology
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:
In order to study the influence of exogenous application of stress mitigating chemicals such as salicylic acid, thiourea and KNO3 to alleviate moisture stress in coriander to improve the morphological and yield attributes through irrigation scheduling, an experimentation was conducted at Vegetable Research Centre, Department of Horticulture, JNKVV, Jabalpur (M.P.) during Rabi season for two consecutive years (2020-21 and 2021-22). The trial was laid out in split plot design with IW:CPE (0.6, 0.8, 1.0 and 1.2) as main plot and stress mitigating chemicals (SA, thiourea and KNO3) as subplot with different concentrations. The pooled analysis carried out during the study substantiated that coriander variety JD-10 sown under IW:CPE 0.8 gave better vegetative growth and higher yield as was superior over the others. Foliar application of SA@150ppm significantly enhanced the morphological traits and yield components thus giving a maximum yield of 18.47q/ha by producing more number of umbels, umbellets and seeds per plant. Treatment combination I2C2 (IW:CPE 0.8 with foliar application of salicylic acid @ 150ppm) gave better growth as plant height reached to 106.27cm at crop harvest with 7.02 branches plant-1, maximum seed yield of 14.92 g plant-1 and highest seed yield of 19.61q/ha. Seed yield was found to be in positive correlation with number of umbels plant-1, umbellets plant-1, seeds per umbel and seed yield plant-1. Thus it can be concluded that coriander produced under optimum soil moisture with ascribed irrigation level along with suitable dose of salicylic acid is optimum for coriander production and ensures higher yield.
Food processing industry by products or food wastes is produced in large amounts in the food processing industries annually around the world. The plant based food processing industries such as fruits and vegetable processing, cereals and pulse processing, nuts and oil seed processing industries etc., mainly produce by products such as bran, husk, pomace, seed, peel, shell, seeds, stems, seed coat during processing. They are dumped as waste or utilized as cattle feed and land filling of these by products cause environment pollution and loss of valuable nutrient components. Food processing industry by products give a promising source of bioactive and functional compounds which may be utilized because of their favorable nutritional and therapeutic properties. Demand for novel functional foods is rising rapidly owing to the increasing health awareness among consumers. The functional foods are used to reduce health risks (Cardiovascular disease, cancer, osteoporosis, obesity, diabetes and metabolic disease, musculoskeletal disease) and improve health quality and health maintenance India is the second major producer of fruits and vegetables in the world. It contributes 10 % of world fruit production. Fruit wastes are rich in antioxidants and phyto-chemicals. Thus fruit processing wastes are useful in serving the functional properties. The aim of the study is to develop a sustaining and functional food products based on the by – products generated from the mango processing industries in Tamil Nadu. This research helps to use better economic utilization of mango processing industries. All these developed functional products have regular and expanding market both in India and foreign countries. This will pave a way to promote entrepreneurship in the area of fruit processing industries.
In the view of sustainable livestock production ample delivery of quality forage is very essential. A field experiment was conducted during 2012-13 to 2016-17 at Research Farm of Bihar Agricultural College; Sabour to identify the suitable forage based cropping system for quality fodder production to get sustainable agriculture production in round the year. The experiments is comprising of seven treatment in randomized block design (RBD), replicated thrice. The detail of all treatments were T1 (NB hybrid + Cowpea – Barseem - Lobia), T2 (Guinea grass + Cowpea - Barseem – Summer Bajra), T3 (Guinea grass + M. Sorghum- Barseem- Ricebean), T4 (Multicut Sorghum - Barseem – Maize + Cowpea), T5 (Sorghum- Barseem- Maize + Cowpea), T6 (Maize + Cowpea – Oat - Summer Bajra + Rice bean) and T7 (Sorghum + Cowpea – Oat – Summer Bajra + Rice bean). However in the cropping system the nutrient was supplied to different crop component on the basis of recommended dose of fertilizer as per treatment. The five years results revealed that Multicut Sorghum– Barseem - Maize + Cowpea cropping system under the treatment (T4) produced significantly higher Green fodder and dry fodder yield e. i. 1412 and 324.89 q/ha with higher net return (Rs. 2,29485) and benefit cost ratio (3.27) over the other treatments. The maximum average crude protein content was found in Napier Hybrid + Cowpea – Barseem– Lobia/cowpea cropping system (17.12%) which was significantly higher than that under all other treatments. Similarly, the maximum total crude protein yield was found in Multicut Sorghum – Barseem – Maize + Cowpea cropping system (25.78 q ha-1) followed by Sorghum – Barseem – Maize + Cowpea and Guinea grass + Cowpea – Barseem – Summer Bajra cropping systems e. i. 20.53 and 18.08 q ha-1 respectively. Inclusion of perennial grasses with annual forage provides continuous supply of green fodder round the year.
The aim of present investigation was to screen the microorganisms isolated from various samples such as soil, cattle dung and decaying woody material capable of degrading cellulose. A total 43 bacterial and 16 fungal isolates were retrieved from three different samples by serial dilution plating technique using carboxymethylcellulose (CMC) agar medium. All the bacterial and fungal isolates were screened for cellulase production on the basis of zone of hydrolysis on CMC agar medium. Out of 43 bacterial isolates, 13 bacterial isolates showed zone formation and three isolates i.e. SB2, SB4 and SB10 showed maximum zone of hydrolysis. Out of 16 fungal isolates, 10 fungi showed the zone formation on CMC agar medium and WF1 showed maximum zone. Cellulase activity of the isolates showing maximum zone i.e. SB4 and WF1 was determined and found to be 276.83 IU/mL and 230.62 IU/mL, respectively.
To address the problem that the basic convolutional neural network is susceptible to background interference and weak expression of important features in recognizing bollworm in apple orchards, an identification method of bollworm in apple orchard based on MC-Mask R-CNN (Mish and CBAM - Mask R-CNN) is proposed. Firstly, on the basis of Haar's traditional neural network, the apple orchard images collected by multiple sites are initial segmented iteratively. The bollworm individual image samples are extracted, and the sample is expanded in multiple ways to obtain the expanded sample data set for deep learning. Secondly, an MC-Mask R-CNN feature extraction network is built and the Mish function is selected as the activation function to avoid vanishing gradient and gradient explosion during back propagation. And meanwhile, an attention mechanism module CBAM combining channel attention and spatial attention is introduced to improve the model's ability to express the characteristics of apple orchard bollworm, which is conducive to extracting deep feature information. Lastly, the Mask R-CNN is used as the control model and the recognition average precision is used as the evaluation index. The ablation test results show: integrating both the Mish activation function and the attention mechanism module into the feature extraction network can improve the recognition average precision of the model; the recognition average precision of the proposed MC-Mask R-CNN model reaches 97.69%. Contrasted with the Mask R-CNN, the recognition average precision is 5.08% higher. The results indicate that MC-Mask R-CNN can accurately and effectively identify apple orchard bollworm and provide technical support for the green protection and control of apple orchard diseases and insect pests.