Topic Review
3D Printed Electromagnetic Vibration Harvesters
Energy harvesting is the utilisation of ambient energy in order to power electronics such as wireless sensor nodes (WSN) or wearables without the need of batteries. This allows to operate the node over a much longer time period compared to battery-powered devices along with lower maintenance efforts. Furthermore, the low-maintenance requirements allow to operate these WSNs in environments with limited or no accessibility.
  • 894
  • 05 Nov 2021
Topic Review
Deep Learning for Image Annotation in Agriculture
The implementation of intelligent technology in agriculture is seriously investigated as a way to increase agriculture production while reducing the amount of human labor. In agriculture, recent technology has seen image annotation utilizing deep learning techniques. Due to the rapid development of image data, image annotation has gained a lot of attention. The use of deep learning in image annotation can extract features from images and has been shown to analyze enormous amounts of data successfully. Deep learning is a type of machine learning method inspired by the structure of the human brain and based on artificial neural network concepts. Through training phases that can label a massive amount of data and connect them up with their corresponding characteristics, deep learning can conclude unlabeled data in image processing. For complicated and ambiguous situations, deep learning technology provides accurate predictions. This technology strives to improve productivity, quality and economy and minimize deficiency rates in the agriculture industry.
  • 881
  • 27 Jul 2022
Topic Review
Solar Energy Potential and Solar Irrigation in Pakistan
Pakistan faces water scarcity and high operational costs for traditional irrigation systems, hindering agricultural productivity. Solar-powered irrigation systems (SPIS) can potentially provide a sustainable and affordable solution, but face technical, financial and policy barriers to adoption. 
  • 849
  • 06 May 2023
Topic Review
Deep Learning Algorithms in Agriculture
The field of agriculture is one of the most important fields in which the application of deep learning still needs to be explored, as it has a direct impact on human well-being. In particular, there is a need to explore how deep learning models can be used as a tool for optimal planting, land use, yield improvement, production/disease/pest control, and other activities. The vast amount of data received from sensors in smart farms makes it possible to use deep learning as a model for decision-making in this field. In agriculture, no two environments are exactly alike, which makes testing, validating, and successfully implementing such technologies much more complex than in most other industries. 
  • 815
  • 18 Mar 2022
Topic Review
Irrigation-Water and Cotton
A decrease in water resources, as well as changing environmental conditions, calls for efficient irrigation-water management in cotton-production systems. Cotton (Gossypium sp.) is an important cash crop in many countries, and it is used more than any other fiber in the world. 
  • 788
  • 06 Feb 2022
Topic Review
Non-Destructive Quality-Detection Techniques for Cereal Grains
Grain quality involves the appearance, nutritional, and safety attributes of grains. With the improvement of people’s living standards, problems pertaining to the quality of grains have received greater attention. Modern quality detection techniques feature unique advantages including rapidness, non-destructiveness, accuracy, and efficiency in detecting grain quality.
  • 787
  • 09 Jan 2023
Topic Review
Forest Rescue Point System
Forest work is dangerous. In particular, manual or motor manual work still exists in large parts of both the professional sector and in the management of small private forests. For example, Germany has a large number of forest owners, estimated at approx. 2,000,000. Accidents that happen in the forest often involve severe injuries. In 2020, 4834 (2019: 5257) accidents during forestry work were reported in Germany. 1533 (2019: 1680) people were so seriously injured that they were unable to work for more than three days. 26 (2019: 36) people lost their lives while working in the forest. The system of fixed rescue points has been established in some areas of Germany for a long time. For example, a system of fixed rescue meeting points was established in the Bavarian state forest as early as the 1990s. In addition to establishing a clear meeting point for the rescue service, providing the fastest route to a landline telephone also played a major role at that time. With the current predominant use of smartphones, the role of the rescue meeting points has changed.
  • 777
  • 23 Feb 2022
Topic Review
Ridge Gourd (Luffa acutangula (L.) Roxb.)
Ridge gourd (Luffa acutangula (L.) Roxb.) or Luffa is a multi-harvest vegetable crop grown in the South Asian region. It is commonly called “Torai” in rural areas of India.
  • 756
  • 09 Feb 2022
Topic Review
Microtransfer Printing Methods
In recent years, with the rapid development of the flexible electronics industry, there is an urgent need for a large-area, multilayer, and high-production integrated manufacturing technology for scalable and flexible electronic products. To solve this technical demand, researchers have proposed and developed microtransfer printing technology, which picks up and prints inks in various material forms from the donor substrate to the target substrate, successfully realizing the integrated manufacturing of flexible electronic products.
  • 753
  • 18 Nov 2021
Topic Review
‘Helete Güneşi’, a New Walnut Cultivar
‘Helete Güneşi’ was selected among different genotypes obtained from crossing ‘Maraş 18’ × ‘Chandler’ in Turkey. The present study compares phenological and pomological traits of ‘Helete Güneşi’ with those of its parents so as to scale their performances. ‘Helete Güneşi’ staged leaf out on 22 April, whereas its parents, ‘Chandler’ and ‘Maraş 18’, did on 20 and 12 April, respectively. The harvest date of ‘Helete Güneşi’ was as early as 17 September, whereas ‘Chandler’ and ‘Maraş 18’ began to be harvested on 5 October and 15 September, respectively. Defoliation in ‘Helete Güneşi’ occurred about 1 month earlier than ‘Chandler’. The nut weight and kernel percentage of ‘Helete Güneşi’ were 13.41 g and 53.39%, respectively, whereas in ‘Chandler’ the values were 12.73 g and 48.23%, respectively, but were 14.62 g and 53.76% in ‘Maraş 18’. ‘Helete Güneşi’ had a higher yield value compared to its parents. The results demonstrated that ‘Helete Güneşi’ has superior traits in being selected for late leafing date, early harvest date, high yield, and good nut quality. Therefore, it can be considered as a valuable genetic resource in future breeding programs around the world.
  • 747
  • 02 Dec 2021
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