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:
The advantages of precision land leveling and broad bed furrow (BBF) planting technique have been established in terms of increasing yields, income and water productivity, and saving of irrigation water and resources. To see the impact of these improved technologies, on-farm trials were conducted on precision land leveling and BBF seeding technique of pigeonpea in Morena district of Madhya Pradesh under FFP project during 2017-18 and 2018-19. An on-farm study was conducted under Farmer FIRST Programme at six selected villages in Morena district of Madhya Pradesh state for 2 consecutive years (2017-18 to 2018-2019). The pigeonpea varieties ‘Pusa 992’ and ‘ICPL 88039’ were used in precision land leveling and BBF trial respectively. The technology was demonstrated in an area of 0.4 ha for each farm families and total 30 farm families and 52 farm families were covered under precision land leveling and BBF trial, respectively. The fertilizers (20:60:20 kg NPK/ha) and plant protection were used as per recommendation for the region. The results indicated that 15.1 and 15.7% higher yield of pigeonpea and water productivity increased by 16.67 % and 11.90% in precision land leveling and BBF system, respectively over farmers’ practice. The economics analysis showed that net returns increased by Rs. 16,494 and Rs. 18,077 in precision land leveling and BBF system, respectively as compared to farmer’s practice. This study suggests that precision land leveling and BBF planting of pigeonpea are more productive and profitable in rainfed areas of central India.
An experiment was conducted to screen twenty four different okra genotypes for their susceptibility to E. vittella under field condition Agricultural College Farm, Agricultural College, Bapatla during rabi 2020-21 and rabi 2021-2022. Observations of shoot infestation on twenty four genotypes of okra during rabi 2020-2021 and rabi 2021-2022 varied from 5.81 to 19.72 and 5.84 to 20.36 per cent respectively. Out of twenty four okra genotypes, on the basis of shoot infestation as regards to the level of resistance no genotype was found as resistant, but eleven genotypes i.e., Abelmoschus tetraphyllus var. tetraphyllus (5.65%), 1685 (6.04%), IC-0117024 (6.72%), IC-0112502 (6.96%), IC-0112196 (9.20%), IC-0117331 (10.07%), IC-0117343 (11.16%), IC-0117028 (12.37%), IC-0116967 (12.61%), IC-0601433 (12.89%), IC-0112499 (13.43%), IC-0116966 (14.18%), IC-0022283 (14.75%), IC-0057733 (13.24%) and IC-0601182 (14.67%) were found to be moderately resistant. However twelve genotypes i.e., IC-0042491 (15.31%), IC-0039140 (16.87%), IC-0601411 (16.12%), IC-0117319 (16.78%), A. Anamika (15.68%), IC-0602982 (17.55%), IC-0601181 (18.29%), IC-0039139 (18.72%) and A. Abhay (18.96%) were found as moderately susceptible genotypes.
The field trial was carried out to find out at Horticultural Research Station, Bidhan Chandra Krishi Viswavidyalaya, Mondouri, Nadia, West Bengal during 2012-13 and 2013-14 to evaluate the response of different levels of soil application of potassium and recommended dose of nitrogen and phosphorous along with nitrogen 2% foliar spray once and twice and their interactions on plant nutrient content and soil fertility status after harvest. The design of the experiment was two factorial R.B.D with 8 treatments and three replications. The treatments consisted of four levels of potassium (K2O @ 80, 120, 160, and 200 kg/ha) and two spray schedules of N @ 2% as a foliar spray of urea to know the role of potassium and nitrogen on plant nutrient content and soil fertility status after harvest. The plant analysis of the leaves of turmeric showed improvement in leaf N, P, and K concentration with the application of potassium and nitrogen. The N, P, and K content were comparatively highest in K2O @ 200kg/ha + N @ 2% double spray, followed by the sole application of potassium (K2O @ 200kg/ha). The soil analysis after harvest of turmeric indicated better building of soil nutrient status i.e, N, P, and K with the application of potassium and nitrogen. The soil pH (7.07%), organic carbon (0.83%), nitrogen (269.69 kg/ha), potassium (315.11 kg/ha) and water holding capacity (56.10%) was recorded maximum with application of K2O @ 200kg/ha + N @ 2% double spray. The phosphorous content of the soil was however recorded maximum with K2O @ 160kg/ha + N @ 2% double spray (56.44%), however application of K2O @ 80kg/ha + N @ 2% single spray showed minimum soil nitrogen, phosphorous and potassium concentration. It appears from the results that application of K2O @ 200kg/ha + N @ 2% double spray proved most effective.
Integrated nutrient management is the adjustment of plant nutrient supply to an optimum level for sustaining the desired crop productivity. In this study, a field experiment was conducted during two consecutive years 2019-20 and 2020-21 at High- tech unit, Department of Horticulture, Udaipur. The experiment consisting fourteen treatments under randomized block design with three replications. Application of different doses of farm yard manure, chemical fertilizers and silicon increased the yield, quality parameters and economics of cauliflower over the control. The results showed that maximum yield (277.53 q/ha), colour value (L* 87.05, a* 1.849 and b* 29.78), compactness of curd (9.21), TSS content (7.34 %), ascorbic acid content (75.26 mg/100g) and gross return (416292.00 Rs/ha) were recorded in treatment T14 (50 % RDN by FYM + 50 % RDF + 100 kg silicon/ha), while the maximum net return (325066.14 Rs/ha) and B:C ratio (4.10) were found in treatment T10 (75 % RDF + 100 kg Si/ha) as compared to control. It is concluded that the integrated use of silicon along with manures and chemical fertilizers enhanced growth, yield and quality parameters of cauliflower.
Disease forecasting and early warning are essential for better management of plant diseases. Being an important component of the disease triangle, weather parameters and soil characteristics are to be critically considered for developing prediction models for soil-borne diseases. An experiment was conducted during summer, kharif and rabi of 2020 to study the seasonal variation of the natural occurrence of sesame root rot disease, their correlation with weather factors and the derivation of a prediction model. Variations in root rot pathogen inoculum concerning soil depth, season, nutrient content and interaction with other rhizosphere microbes were studied. The experiment revealed that the disease initiated after 3 weeks of sowing and appeared throughout the seasons ranging from 5.00% to 34.6%, 0- 19.8% and 0-26% in summer, kharif and rabi season respectively with an increasing trend towards maturity. High disease incidence was recorded in summer when temperature ranged from 32.1℃ to 42℃ coupled with less to no rainfall followed by rabi and Kharif. Temperature showed a positive correlation with the disease incidence in all the seasons whereas rainfall is negatively correlated. The pathogen inoculum was observed more at 5-10 cm soil depth in the summer season. Prediction models were developed to forecast the disease by employing weather data and current disease incidence using statistical tools. Disease forecast using proposed models can be considered as a prototype for early warning of root rot disease.