A volcano can be defined as a complex system, not least for the hidden clues related to its internal nature. Innovative models grounded in the Artificial Sciences, have been proposed for a novel pattern recognition an...A volcano can be defined as a complex system, not least for the hidden clues related to its internal nature. Innovative models grounded in the Artificial Sciences, have been proposed for a novel pattern recognition analysis at Mt. Etna volcano. The reference monitoring dataset dealt with real data of 28 parameters collected between January 2001 and April 2005, during which the volcano underwent the July-August 2001, October 2002-January 2003 and September 2004-April 2005 flank eruptions. There were 301 eruptive days out of an overall number of 1581 investigated days. The analysis involved successive steps. First, the TWIST algorithm was used to select the most predictive attributes associated with the flank eruption target. During his work, the algorithm TWIST selected 11 characteristics of the input vector: among them SO<sub>2</sub> and CO<sub>2</sub> emissions, and also many other attributes whose linear correlation with the target was very low. A 5 × 2 Cross Validation protocol estimated the sensitivity and specificity of pattern recognition algorithms. Finally, different classification algorithms have been compared to understand if this pattern recognition task may have suitable results and which algorithm performs best. Best results (higher than 97% accuracy) have been obtained after performing advanced Artificial Neural Networks, with a sensitivity and specificity estimates over 97% and 98%, respectively. The present analysis highlights that a suitable monitoring dataset inferred hidden information about volcanic phenomena, whose highly non-linear processes are enhanced.展开更多
As a result of the fierceness of business competition, companies, to remaincompetitive, have to charm their customers by anticipating their needs and being able to rapidlydevelop exciting new products for them. To ove...As a result of the fierceness of business competition, companies, to remaincompetitive, have to charm their customers by anticipating their needs and being able to rapidlydevelop exciting new products for them. To overcome this challenge, technology forecasting isconsidered as a powerful tool in today's business environment, while there are as many successstories as there are failures, a good application of this method will give a good result. Amethodology of integration of patterns or lines of technology evolution in TRIZ parlance ispresented, which is also known as TRIZ technology forecasting, as input to the QFD process to designa new product. For this purpose, TRIZ technology forecasting, one of the TRIZ major tools, isdiscussed and some benefits compared to the traditional forecasting techniques are highlighted. Thena methodology to integrate TRIZ technology forecasting and QFD process is highlighted.展开更多
The authors investigate possible changes of monsoon rainfall and associated seasonal (June-JulyAugust) anomaly patterns over eastern China in the late 21st century under the Intergovernmental Panel on Climate Change (...The authors investigate possible changes of monsoon rainfall and associated seasonal (June-JulyAugust) anomaly patterns over eastern China in the late 21st century under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 emission scenario as simulated by a high-resolution regional climate model (RegCM3) nested in a general circulation model (FvGCM/CCM3).Two sets of multi-decadal simulations are performed at 20-km grid spacing for present day and future climate conditions.Results show that the RegCM3 reproduces the mean rainfall distribution;however the evolution of the monsoon rain belt from South China to North China is not well simulated.Concerning the rain pattern classifications,RegCM3 overestimates the occurrence of Pattern 1 (excessive rainfall in northern China) and underestimates that of Pattern 2 (increased rainfall over the Huai River basin).Under future climate conditions,RegCM3 projects less occurrence of Pattern 1,more of Pattern 2,and little change of Pattern 3 (rainfall increase along the Yangtze River).These results indicate that there might be increased rainfall over the Huai-Yellow River area and reduced rainfall over North China in the future,while rainfall over the lower reaches of the Yangtze River basin is not modified significantly.Uncertainties exist in the present study are also discussed.展开更多
In order to comprehend temporal pattern of the larvae population of the yellow rice borer, Tryporyza incertulas, and provide valuable information for its forecast model, the data series of the population for each gene...In order to comprehend temporal pattern of the larvae population of the yellow rice borer, Tryporyza incertulas, and provide valuable information for its forecast model, the data series of the population for each generation and the over-wintered larvae from 1960 to 1990 in Dingcheng District, Changde City, Hunan Province, were analyzed with geostatistics. The data series of total number, the 1st generation, the 3rd generation and the over-wintered larvae year to year displayed rather better autocorrelation and prediction. The data series of generation to generation, the 2nd generation and the 4th generation year to year, however, demonstrated poor autocorrelation, especially for the 4th generation, whose autocorrelation degree was zero. The population dynamics of the yellow rice borer was obviously intermittent. A remarkable cycle of four generations, one year, was observed in the population of generation to generation. Omitting the certain generation or interposing the over-wintered larvae only resulted in a less or slight change of autocorrelation of the whole data series generation to generation. Crop system, food, climate and natural enemies, therefore, played more important roles in regulating the population dynamics than base number of the larvae. The basic techniques of geostatistics applied in analyzing temporal population dynamics were outlined.展开更多
Recently, the National Typhoon Center （NTC） at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone （TC） track density from Jun...Recently, the National Typhoon Center （NTC） at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone （TC） track density from June to October. This model is the first approach to target seasonal TC track clusters covering the entire western North Pacific （WNP） basin, and may represent a milestone for seasonal TC forecasting, using a simple statistical method that can be applied at weather operation centers. In this note, we describe the procedure of the track-pattern-based model with brief technical background to provide practical information on the use and operation of the model. The model comprises three major steps. First, long-term data of WNP TC tracks reveal seven climatological track clusters. Second, the TC counts for each cluster are predicted using a hybrid statistical-dynamical method, using the seasonal prediction of large-scale environments. Third, the final forecast map of track density is constructed by merging the spatial probabilities of the seven clusters and applying necessary bias corrections. Although the model is developed to issue the seasonal forecast in mid-May, it can be applied to alternative dates and target seasons following the procedure described in this note. Work continues on establishing an automatic system for this model at the NTC.展开更多
The East Asia–Pacific(EAP) teleconnection pattern is the dominant mode of circulation variability during boreal summer over the western North Pacific and East Asia, extending from the tropics to high latitudes. Howev...The East Asia–Pacific(EAP) teleconnection pattern is the dominant mode of circulation variability during boreal summer over the western North Pacific and East Asia, extending from the tropics to high latitudes. However, much of this pattern is absent in multi-model ensemble mean forecasts, characterized by very weak circulation anomalies in the mid and high latitudes. This study focuses on the absence of the EAP pattern in the extratropics, using state-of-the-art coupled seasonal forecast systems. The results indicate that the extratropical circulation is much less predictable, and lies in the large spread among different ensemble members, implying a large contribution from atmospheric internal variability. However,the tropical–mid-latitude teleconnections are also relatively weaker in models than observations, which also contributes to the failure of prediction of the extratropical circulation. Further results indicate that the extratropical EAP pattern varies closely with the anomalous surface temperatures in eastern Russia, which also show low predictability. This unpredictable circulation–surface temperature connection associated with the EAP pattern can also modulate the East Asian rainband.展开更多
This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic devel...This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province＇s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows：（1） Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low.（2） Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others.（3） Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.展开更多
Support vector machine(SVM)is a new technology in data mining.It is a new tool to solve machine learning problems with the help of optimization.Support vector machines belong to a new machine learning that extends fro...Support vector machine(SVM)is a new technology in data mining.It is a new tool to solve machine learning problems with the help of optimization.Support vector machines belong to a new machine learning that extends from statistical learning theory.Its structure is relatively simple,with good generalization ability and global optimality.Support vector machine has provided a unified framework for solving finite sample learning problems,and there are many solutions proposed.It can deal with those more complex problems and introduce the characteristics of the support vector machine model.Aiming at the application of the model in economic forecasting,a method to improve the prediction accuracy of the model is proposed.The theoretical analysis and practical application verification are performed,which shows that this method can obtain more accurate prediction results.展开更多
Fog has recently become a frequent high-impact weather phenomenon along the coastal regions of North China. Accurate fog forecasting remains challenging due to limited understanding of the predictability and mechanism...Fog has recently become a frequent high-impact weather phenomenon along the coastal regions of North China. Accurate fog forecasting remains challenging due to limited understanding of the predictability and mechanism of fog formation associated with synoptic-scale circulation. One frequent synoptic pattern of fog formation in this area is associated with cold front passage(cold-front synoptic pattern, CFSP). This paper explored the predictability of a typical CFSP fog event from the perspective of analyzing key characteristics of synoptic-scale circulation determining fog forecasting performance and the possible mechanism. The event was ensemble forecasted with the Weather Research and Forecasting model. Two groups of ensemble members with good and bad forecasting performance were selected and composited. Results showed that the predictability of this case was largely determined by the simulated strengths of the cold-front circulation(i.e., trough and ridge and the associated surface high). The bad-performing members tended to have a weaker ridge behind a stronger trough, and associated higher pressure over land and a weaker surface high over the sea, leading to an adverse impact on strength and direction of steering flows that inhibit warm moist advection and enhance cold dry advection transported to the focus region. Associated with this cold dry advection, adverse synoptic conditions of stratification and moisture for fog formation were produced, consequently causing failure of fog forecasting in the focus region. This study highlights the importance of accurate synoptic-scale information for improved CFSP fog forecasting, and enhances understanding of fog predictability from perspective of synoptic-scale circulation.展开更多
Despite the significant annual consumption of honey in Saudi Arabia, information gaps remain with regard to the marketing and market structure of honey along the value chain. This study analyzed the major factors that...Despite the significant annual consumption of honey in Saudi Arabia, information gaps remain with regard to the marketing and market structure of honey along the value chain. This study analyzed the major factors that influenced the consumption, expenditure patterns, and demand of honey in Saudi Arabia. This study forecasted the near-future expected market demands for honey in Saudi Arabia by collecting and analyzing the primary data using questionnaires. A total of 331 respondents from representative regions and large cities were randomly selected and interviewed. The data were analyzed using qualitative and quantitative methods as well as appropriate econometric models. Respondents characterized honey quality using organoleptic words, and these characterizations varied based on the relative significance of perception parameters. Taste, aroma, physical state, and color had aggregated average scores of 4.58, 4.44, 3.54, and 3.28, respectively. In addition to the above parameters, honey source, brand name, and confidence in the producers influenced its perceived quality. The major outlets for honey in Saudi Arabia included producers, specialized honey stores, and auction markets in major cities during the harvesting seasons. Medication, food, and sweetening were the major motivations for buying honey in the Saudi market, with aggregate scores of 4.52, 3.71, and 1.52, respectively. Significant honey price variations were observed within and among different honeys and packaging volumes;this finding might be due to factors such as botanical and geographical origins, package volume size economics (i.e., bulk purchases), honey variety blending, brand names, and producer policies. The average price of locally produced honey was approximately $73 per kg, which is 10 times more than the average price of honey in the US and the EU. The estimated consumption/income elasticity was 0.27. These results suggest that honey is a basic commodity in Saudi Arabia. Based on econometric model forecasts, the Saudi market demand for honey is expected to reach approximately 29,784 tons in 2025.展开更多
文摘A volcano can be defined as a complex system, not least for the hidden clues related to its internal nature. Innovative models grounded in the Artificial Sciences, have been proposed for a novel pattern recognition analysis at Mt. Etna volcano. The reference monitoring dataset dealt with real data of 28 parameters collected between January 2001 and April 2005, during which the volcano underwent the July-August 2001, October 2002-January 2003 and September 2004-April 2005 flank eruptions. There were 301 eruptive days out of an overall number of 1581 investigated days. The analysis involved successive steps. First, the TWIST algorithm was used to select the most predictive attributes associated with the flank eruption target. During his work, the algorithm TWIST selected 11 characteristics of the input vector: among them SO<sub>2</sub> and CO<sub>2</sub> emissions, and also many other attributes whose linear correlation with the target was very low. A 5 × 2 Cross Validation protocol estimated the sensitivity and specificity of pattern recognition algorithms. Finally, different classification algorithms have been compared to understand if this pattern recognition task may have suitable results and which algorithm performs best. Best results (higher than 97% accuracy) have been obtained after performing advanced Artificial Neural Networks, with a sensitivity and specificity estimates over 97% and 98%, respectively. The present analysis highlights that a suitable monitoring dataset inferred hidden information about volcanic phenomena, whose highly non-linear processes are enhanced.
基金This project is supported by National Natural Science Foundation of China(No.20172041) and Provincial Science Foundation of Anhui, China (No.03042308).
文摘As a result of the fierceness of business competition, companies, to remaincompetitive, have to charm their customers by anticipating their needs and being able to rapidlydevelop exciting new products for them. To overcome this challenge, technology forecasting isconsidered as a powerful tool in today's business environment, while there are as many successstories as there are failures, a good application of this method will give a good result. Amethodology of integration of patterns or lines of technology evolution in TRIZ parlance ispresented, which is also known as TRIZ technology forecasting, as input to the QFD process to designa new product. For this purpose, TRIZ technology forecasting, one of the TRIZ major tools, isdiscussed and some benefits compared to the traditional forecasting techniques are highlighted. Thena methodology to integrate TRIZ technology forecasting and QFD process is highlighted.
基金jointly supported by the National Basic Research Program of China (Grant No.2009CB421407) the R&D Special Fund for Public Welfare Industry (meteorology) (GYHY200806010)
文摘The authors investigate possible changes of monsoon rainfall and associated seasonal (June-JulyAugust) anomaly patterns over eastern China in the late 21st century under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 emission scenario as simulated by a high-resolution regional climate model (RegCM3) nested in a general circulation model (FvGCM/CCM3).Two sets of multi-decadal simulations are performed at 20-km grid spacing for present day and future climate conditions.Results show that the RegCM3 reproduces the mean rainfall distribution;however the evolution of the monsoon rain belt from South China to North China is not well simulated.Concerning the rain pattern classifications,RegCM3 overestimates the occurrence of Pattern 1 (excessive rainfall in northern China) and underestimates that of Pattern 2 (increased rainfall over the Huai River basin).Under future climate conditions,RegCM3 projects less occurrence of Pattern 1,more of Pattern 2,and little change of Pattern 3 (rainfall increase along the Yangtze River).These results indicate that there might be increased rainfall over the Huai-Yellow River area and reduced rainfall over North China in the future,while rainfall over the lower reaches of the Yangtze River basin is not modified significantly.Uncertainties exist in the present study are also discussed.
基金National NaturalScience Foundation of China(30100122).
文摘In order to comprehend temporal pattern of the larvae population of the yellow rice borer, Tryporyza incertulas, and provide valuable information for its forecast model, the data series of the population for each generation and the over-wintered larvae from 1960 to 1990 in Dingcheng District, Changde City, Hunan Province, were analyzed with geostatistics. The data series of total number, the 1st generation, the 3rd generation and the over-wintered larvae year to year displayed rather better autocorrelation and prediction. The data series of generation to generation, the 2nd generation and the 4th generation year to year, however, demonstrated poor autocorrelation, especially for the 4th generation, whose autocorrelation degree was zero. The population dynamics of the yellow rice borer was obviously intermittent. A remarkable cycle of four generations, one year, was observed in the population of generation to generation. Omitting the certain generation or interposing the over-wintered larvae only resulted in a less or slight change of autocorrelation of the whole data series generation to generation. Crop system, food, climate and natural enemies, therefore, played more important roles in regulating the population dynamics than base number of the larvae. The basic techniques of geostatistics applied in analyzing temporal population dynamics were outlined.
基金funded by the Korea Meteorological Administration Research and Development Program under Grant CATER 2012-2040supported by the BK21 project of the Korean government
文摘Recently, the National Typhoon Center （NTC） at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone （TC） track density from June to October. This model is the first approach to target seasonal TC track clusters covering the entire western North Pacific （WNP） basin, and may represent a milestone for seasonal TC forecasting, using a simple statistical method that can be applied at weather operation centers. In this note, we describe the procedure of the track-pattern-based model with brief technical background to provide practical information on the use and operation of the model. The model comprises three major steps. First, long-term data of WNP TC tracks reveal seven climatological track clusters. Second, the TC counts for each cluster are predicted using a hybrid statistical-dynamical method, using the seasonal prediction of large-scale environments. Third, the final forecast map of track density is constructed by merging the spatial probabilities of the seven clusters and applying necessary bias corrections. Although the model is developed to issue the seasonal forecast in mid-May, it can be applied to alternative dates and target seasons following the procedure described in this note. Work continues on establishing an automatic system for this model at the NTC.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41320104007, 41775083 and U1502233)supported by the UK–China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund
文摘The East Asia–Pacific(EAP) teleconnection pattern is the dominant mode of circulation variability during boreal summer over the western North Pacific and East Asia, extending from the tropics to high latitudes. However, much of this pattern is absent in multi-model ensemble mean forecasts, characterized by very weak circulation anomalies in the mid and high latitudes. This study focuses on the absence of the EAP pattern in the extratropics, using state-of-the-art coupled seasonal forecast systems. The results indicate that the extratropical circulation is much less predictable, and lies in the large spread among different ensemble members, implying a large contribution from atmospheric internal variability. However,the tropical–mid-latitude teleconnections are also relatively weaker in models than observations, which also contributes to the failure of prediction of the extratropical circulation. Further results indicate that the extratropical EAP pattern varies closely with the anomalous surface temperatures in eastern Russia, which also show low predictability. This unpredictable circulation–surface temperature connection associated with the EAP pattern can also modulate the East Asian rainband.
基金National Natural Science Foundation of China,No.41171433Philosophy and Social Science Foundation of China,No.16BJY039
文摘This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province＇s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows：（1） Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low.（2） Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others.（3） Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.
基金supported by the Scientific Research program of Xinxiang University(Grant No.XXUTD20170108).
文摘Support vector machine(SVM)is a new technology in data mining.It is a new tool to solve machine learning problems with the help of optimization.Support vector machines belong to a new machine learning that extends from statistical learning theory.Its structure is relatively simple,with good generalization ability and global optimality.Support vector machine has provided a unified framework for solving finite sample learning problems,and there are many solutions proposed.It can deal with those more complex problems and introduce the characteristics of the support vector machine model.Aiming at the application of the model in economic forecasting,a method to improve the prediction accuracy of the model is proposed.The theoretical analysis and practical application verification are performed,which shows that this method can obtain more accurate prediction results.
基金supported by the National Key R&D Program of China (Nos. 2017YFC1404100 and 2017YFC1404104)the National Natural Science Foundation of China (Nos. 41705081 and 41575067)the Global Change Research Program of China (No. 2015CB953904)
文摘Fog has recently become a frequent high-impact weather phenomenon along the coastal regions of North China. Accurate fog forecasting remains challenging due to limited understanding of the predictability and mechanism of fog formation associated with synoptic-scale circulation. One frequent synoptic pattern of fog formation in this area is associated with cold front passage(cold-front synoptic pattern, CFSP). This paper explored the predictability of a typical CFSP fog event from the perspective of analyzing key characteristics of synoptic-scale circulation determining fog forecasting performance and the possible mechanism. The event was ensemble forecasted with the Weather Research and Forecasting model. Two groups of ensemble members with good and bad forecasting performance were selected and composited. Results showed that the predictability of this case was largely determined by the simulated strengths of the cold-front circulation(i.e., trough and ridge and the associated surface high). The bad-performing members tended to have a weaker ridge behind a stronger trough, and associated higher pressure over land and a weaker surface high over the sea, leading to an adverse impact on strength and direction of steering flows that inhibit warm moist advection and enhance cold dry advection transported to the focus region. Associated with this cold dry advection, adverse synoptic conditions of stratification and moisture for fog formation were produced, consequently causing failure of fog forecasting in the focus region. This study highlights the importance of accurate synoptic-scale information for improved CFSP fog forecasting, and enhances understanding of fog predictability from perspective of synoptic-scale circulation.
文摘Despite the significant annual consumption of honey in Saudi Arabia, information gaps remain with regard to the marketing and market structure of honey along the value chain. This study analyzed the major factors that influenced the consumption, expenditure patterns, and demand of honey in Saudi Arabia. This study forecasted the near-future expected market demands for honey in Saudi Arabia by collecting and analyzing the primary data using questionnaires. A total of 331 respondents from representative regions and large cities were randomly selected and interviewed. The data were analyzed using qualitative and quantitative methods as well as appropriate econometric models. Respondents characterized honey quality using organoleptic words, and these characterizations varied based on the relative significance of perception parameters. Taste, aroma, physical state, and color had aggregated average scores of 4.58, 4.44, 3.54, and 3.28, respectively. In addition to the above parameters, honey source, brand name, and confidence in the producers influenced its perceived quality. The major outlets for honey in Saudi Arabia included producers, specialized honey stores, and auction markets in major cities during the harvesting seasons. Medication, food, and sweetening were the major motivations for buying honey in the Saudi market, with aggregate scores of 4.52, 3.71, and 1.52, respectively. Significant honey price variations were observed within and among different honeys and packaging volumes;this finding might be due to factors such as botanical and geographical origins, package volume size economics (i.e., bulk purchases), honey variety blending, brand names, and producer policies. The average price of locally produced honey was approximately $73 per kg, which is 10 times more than the average price of honey in the US and the EU. The estimated consumption/income elasticity was 0.27. These results suggest that honey is a basic commodity in Saudi Arabia. Based on econometric model forecasts, the Saudi market demand for honey is expected to reach approximately 29,784 tons in 2025.
