Food Research International
Crops, livestock and seafood are major contributors to global economy. Agriculture and fisheries are especially dependent on climate. Thus, elevated temperatures and carbon dioxide levels can have large impacts on appropriate nutrient levels, soil moisture, water availability and various other critical performance conditions. Changes in drought and flood frequency and severity can pose severe challenges to farmers and threaten food safety. In addition, increasingly warmer water temperatures are likely to shift the habitat ranges of many fish and shellfish species, ultimately disrupting ecosystems. In general, climate change will probably have negative implications for farming, animal husbandry and fishing. The effects of climate change must be taken into account as a key aspect along with other evolving factors with a potential impact on agricultural production, such as changes in agricultural practices and technology; all of them with a serious impact on food availability and price. This review is intended to provide critical and timely information on climate change and its implications in the food production/consumption system, paying special attention to the available mitigation strategies.
[学术文献] Agroview: Cloud-based application to process, analyze and visualize UAV-collected data for precision agriculture applications utilizing artificial intelligence 进入全文
Computers and Electronics in Agriculture
Traditional sensing technologies in specialty crops production, for pest and disease detection and field phenotyping, rely on manual sampling and are time consuming and labor intensive. Since availability of personnel trained for field scouting is a major problem, small Unmanned Aerial Vehicles (UAVs) equipped with various sensors can simplify the surveying procedure, decrease data collection time, and reduce cost. To accurate and rapidly process, analyze and visualize data collected from UAVs and other platforms (e.g. small airplanes, satellites, ground platforms), a cloud and artificial intelligence (AI) based application (named Agroview) was developed. This interactive and user-friendly application can: (i) detect, count and geo-locate plants and plant gaps (locations with dead or no plants); (ii) measure plant height and canopy size (plant inventory); (iii) develop plant health (or stress) maps. In this study, the use of this Agroview application to evaluate phenotypic characteristics of citrus trees (as a case study) is presented. It was found, that this emerging technology detected citrus trees with mean absolute percentage error (MAPE) of 2.3% in a commercial citrus orchard with 175,977 trees (1,871 acres; 39 normal and high-density spacing blocks). Furthermore, it accurately estimated tree height with 4.5% and 12.93% MAPE for normal and high-density spacing respectively, and canopy size with MAPE of 12.9% and 34.6% for normal and high-density spacing respectively. It provides a consistent, more direct, cost-effective and rapid method for field survey and plant phenotyping.