The demand for mobile applications in agriculture is increasing as smartphones are continuously developed and used for many purposes; one of them is managing pests and diseases in crops. Using mobile applications, farmers can detect early infection and improve the specified treatment and precautions to prevent further infection from occurring. Furthermore, farmers can communicate with agricultural authorities to manage their farm from home, and efficiently obtain information such as the spectral signature of crops. Therefore, the spectral signature can be used as a reference to detect pests and diseases with a hyperspectral sensor more efficiently than the conventional method, which takes more time to monitor the entire crop field. This review aims to show the current and future trends of mobile computing based on spectral signature analysis for pest and disease management. In this review, the use of mobile applications for pest and disease monitoring is evaluated based on image processing, the systems developed for pest and disease extraction, and the structure of steps outlined in developing a mobile application. Moreover, a comprehensive literature review on the utilisation of spectral signature analysis for pest and disease management is discussed. The spectral reflectance used in monitoring plant health and image processing for pest and disease diagnosis is mentioned. The review also elaborates on the integration of a spectral signature library within mobile application devices to obtain information about pests and disease in crop fields by extracting information from hyperspectral datasets. This review demonstrates the necessary scientific knowledge for visualising the spectral signature of pests and diseases using a mobile application, allowing this technology to be used in real-world agricultural settings.

Weeds are plants that compete for nutrients, space, and light and exert many harmful effects by reducing the quality and quantity of crops if the weed population is uncontrolled. The direct yield loss has been estimated to be within the range of 16–86%, depending on the type of rice culture, weed species, and environmental conditions. Currently, farmers apply herbicides at the same rate to control weeds. Excessive chemical usage will negatively affect the environment, crop productivity, and the economy. A map-based system can help in directing the herbicide sprayer to specific areas. Producing a weed map is very challenging due to the similarity of the crops and the weeds. Therefore, using UAVs and multispectral imagery solves the weed detection problem in a paddy field. The objective of this study project is to detect weeds in rice fields using a UAV and multispectral imagery. Multispectral imagery was used to identify the condition of the crops. It can be an indicator to determine weeds and paddy plants based on the spectral resolution in the imagery. This study was performed at Tunjang, Jitra, Kedah, which has a total area of 0.5 ha. The two types of data collections of this study are ground data and aerial data collection. Ground data were collected using the Soil Plant Analysis Development (SPAD) meter, which can read the chlorophyll value of the area. For aerial data, an unmanned aerial vehicle (UAV) was used, attached with a multispectral camera, Micasense, and a Red Green Blue (RGB) camera. Aerial data collection was conducted on the same day as ground data collection, on 30 June 2020 (the day after sowing (DAS) 34). A correlation between these two data was conducted. The study output is a weed map developed from the RGB image and multispectral imagery normalized difference vegetation index (NDVI) map. The correlation of the NDVI value with the UAV with SPAD data was weak. It has a positive, but not significant.

HRMARS is well established journal publisher based in Pakistan. It is publishing prominent journals in social sciences since 2011.

Since the beginning of the 21st century, urban agriculture has been weighed as a strategy to address the loss of urban livability. This study will address three key aspects: 1) urban ecosystem services in Southeast Asia; 2) sustainable urban agriculture in Southeast Asia; and 3) enhancing urban ecosystem services through Southeast Asian urban agriculture. In the literature on environmental protection, the importance placed upon urban environments has been relatively limited as compared with other habitats such as wetlands or forests. Currently, urban agriculture is complementary to rural development (mainly by providing perishable goods such as fruits, meat, and eggs), and it is now well-established that it is developing community food supply networks. These and related issues call for a deeper understanding of the relationships between plants, city dwellers and the urban climate, which will help set the foundations for permanently upgradable structures capable of adjusting to a world that changes every day. Keywords: agriculture, urban ecology, sustainable ecosystem, sustainable development, environmental management

As the world population grows, it is crucial that food production is linearly proportional to the growing demands of food across the globe. The agriculture sector has many opportunities as well as challenges in the upcoming years. Many innovations have been achieved in the previous years and there are more technologies being researched annually. To automize agriculture, unmanned aerial vehicles (UAV) are extensively being studied to be applied in agriculture. This technology is being explored by integrating it with other sciences as well such as vegetation indices. Vegetation indices allow extensive analysis to be done on the images taken through the UAV. Currently, there are many studies that are done to monitor crops using information obtained from vegetation indices derived from aerial imagery. The crops that are monitored are also geotagged so that precise information can be extracted. This paper will be assessing the usage of aerial imagery, vegetation indices as well as geotagging to monitor crops.