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Microfludics-based Sensors for Healthcare
Microfluidics has emerged as a promising technology for medical and environmental testing.
The recent innovations in the field of microfluidics applied to diagnostic/medical devices and point-of-care medicine
For more information please read the article
https://www.frontiersin.org/research-topics/55654/microfluidics-based-sensors-for-one-health
Artificial Intelligence in Smart Futuristic Agriculture
Artificial Intelligence-driven Technologies in Agriculture
Artificial Intelligence in agriculture is the creation and study of computers and software’s capable of intelligent behavior which helps in creating ‘Self Learning Algorithms & Capabilities’, leading to automation on-ground agriculture practices. Farm activities such as field sowing, ploughing, fertilizer application, insecticide spray, harvesting, weeding and post-harvest land-replenishing can be carried out by the applications and processes developed around AI. AI comes as a great boon to the agricultural sector which is slowly but surely making its presence in agricultural sector.
Agriculture is a dynamic domain where solutions cannot be generalized to suggest a common solution. AI techniques have enabled us to capture the intricate details of each situation and provide a solution that is best fit for that particular problem. AI can be employed for agricultural product monitoring and storage control. Storage, drying and grading of the harvested crops are important aspects of agriculture. Hence, AI can be employed in addressing various food monitoring and quality control mechanisms. The crop yield prediction is very beneficial for marketing strategies and crop cost estimation.
Listen to this article on YouTube and Speechify.
Soil Nitrogen Sensors
An article in the recent issue (volume 2 issue 12, December, 2021) of Nature Food journal was published related to the development of point-of-use sensors for determination of soil nitrogen status in the field conditions.
Food Pathogen Detection: From Culture Media to Universal Detection Systems of Multiple Pathogens
The article explains the development in methodology for food pathogens detection from culture-based methods to culture-independent methods.
(Credit:BioExpert)
Please click the following links to explore further details about these techniques.
Innovative technical solutions for futuristic smart farming
Sensor Technology in Agriculture
Modern farming requires technical solutions for increasing production while reducing environmental impact by reducing the application of agrochemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the above mentioned goals. The explosive technological advances and development in recent years have facilitated the attainment of some of these objectives removing many barriers for their implementation, including the reservation expressed by farmers. Precision agriculture is an emerging area where sensor-based technologies play an important role. Farmers, researchers and technical manufactures are combining their efforts to find efficient solutions, improvements in production and reductions in cost.
Various area of agricultural system where sensors technology based on the requirement of farmers, according to the farming operations include crop health status determination; crop phenotyping, germination, emergence and determination of different growth stages of crops; non-destructive soil sensing; the detection, recognition and mapping of nutrient stress in crops; automated detection and mapping of crop enemies and threat situation of weed, fungi, virus and insects; detection of microorganisms and pest management; detection and identification of crops, and weeds and their control; volatile compounds detection, electronic noses and tongues; yields estimation and prediction; the detection of fruits and their quality; airborne sensor (UAV); hyperspectral, multispectral, fluorescence and thermal sensing based on optical sensor technology; robot navigation, localization and mapping and environmental awareness; robotic applications in crop management; positioning, navigation and obstacles detection; traceability systems in the field by using new technologies e.g. RFID, barcode, GPS, Zigbee; network in agriculture, wearable sensors, the Internet of Things (IoT); low energy, disposable, energy harvesting sensors; deep learning from sensor data in agriculture.
For more information
https://wordpress.com/page/gingerfingers.wordpress.com/1407
Prof. Dr. Dimitrios Moshou, www.mdpi.com
Huaimin Li et al. Sensors 2020, 20(10), 2894
https://doi.org/10.3390/s20102894 – 20 May 2020
Ginger Fingers 