Affected by the meteorological disasters and market fluctuations,the growing area,yield and quality of cotton in Shandong Province have been reduced to varying degrees in recent years.The majority of farmers are regar...Affected by the meteorological disasters and market fluctuations,the growing area,yield and quality of cotton in Shandong Province have been reduced to varying degrees in recent years.The majority of farmers are regarded as the main body of agricultural production,whose enthusiasm for growing cotton and confidence in the cotton market play a significant role in stabilizing the growing area and improving the quality of cotton.We randomly select the cotton farmers for in-depth interview,to understand the situation of cotton cultivation and their state of mind for growing,aimed at deriving the factors influencing farmers'willingness to grow cotton.In the future,it is necessary to make the best use of the advantages and bypass the disadvantages,and in a timely manner curb the decline of cotton cultivation in the process of guiding and encouraging the cotton cultivation,in order to solve the problems of low farmers'willingness to grow cotton and sluggish cotton industry from the root.展开更多
Rice yield is still low in Nigeria despite the ecological advantages. Several challenges has been traced it production. The study intend to investigate if other rice producing nations are faced with similar challenges...Rice yield is still low in Nigeria despite the ecological advantages. Several challenges has been traced it production. The study intend to investigate if other rice producing nations are faced with similar challenges and at what magnitude and more importantly, what can be learn to improve the rice yield in Nigeria. Based on 2013/2014 survey, a total sample of 400 famers were randomly interviewed;164 from Niger State of Nigeria and 236 from Hainan province of China. The study collate the perception of farmers to rice production constraints categorized into biotic, abiotic and socioeconomics. Biplot analysis was employed to examine multivariate pattern of their perceptions towards production constraints. The multivariate technique simultaneously displaying different yield levels and factor constraints in data matrix providing the inter-unit distances, variance and correlations of variables. According to the study, Niger state farmers identified socioeconomic constraint as the major factors to production and attributed it to lack of or insufficient investment while the Hainan farmers majorly identified abiotic constraints. The study also indicated that great potential remain to further improve rice yield in both regions especially in Nigeria given the appropriate investment on essential inputs. This study is of great use to extension officers more so, given the investment in Africa, policy makers take advantage of the bilateral and multilateral relationship to invest ease transfer of agricultural information and technologies between or among partners.展开更多
Aflatoxin associated with a number of cereals and legumes is estimated to increase the chances of developing primary liver cancer in 152.7 and 61.1 cancer/year/100,000 population of infants and children, respectively ...Aflatoxin associated with a number of cereals and legumes is estimated to increase the chances of developing primary liver cancer in 152.7 and 61.1 cancer/year/100,000 population of infants and children, respectively in Nigeria. This study was carried out to assess the implications of some agronomic practices on the infestation of aflatoxigenic fungi and total aflatoxin in maize produce in Benue State. Two maize sample types (Pre-harvest and Post-harvest) collected from 3 locations in Benue State were cultured on Sabouraud dextrose agar for fungi isolation and identification. Moisture content and total aflatoxin concentration were determined (ELISA method) in both pre-harvest oven dried and farmer’s post-harvest sun dried samples. Information on agronomic practices was obtained with the aid of questionnaire. T-test and analysis of variance (ANOVA) were used to analyze the data with confident levels set at 95%. Overall, 5 mould genera were identified: Aspergillus (44.0%), Fusarium (24.44%), Botryodiplodia (17.78%), Rhizopus (15.56%) and Penicillium (4.44%). Moisture content of oven dried samples was significantly less than that of farmers sun dried samples (t = 10.45, P < 0.001). Similarly, a significant difference in total aflatoxin concentration was recorded between farmers sun dried and oven dried samples (t = 2.37, P = 0.03). Half of the farmer’s sun dried samples had aflatoxin concentration above the recommended EU (4 ug/Kg) limit, but none of the pre-harvest oven dried samples exceeded EU limits. Maize samples from fertilized farms were more likely than non-fertilized farms to have higher aflatoxin concentration (P = 0.002). Similarly, Maize seeds purchase from the open market were more likely than seeds from previous harvest to be contaminated with aflatoxin (P = 0.003). The study advocates rapid drying of timely harvested maize so as to reduce or stop the action of heavy field fungi contaminants as well as aflatoxin accumulation.展开更多
The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems.The states of mind or judgment ...The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems.The states of mind or judgment outcomes are highly complex phenomena that happen inside the human body.Decoding these states is significant for improving the quality of technology and providing an impetus to scientific research aimed at understanding the functioning of the human mind.One of the key advantages of quantum wave-functions over conventional classical models is the existence of configurable hidden variables,which provide more data density due to its exponential state-space growth.These hidden variables correspond to the amplitudes of each probable state of the system and allow for the modeling of various intricate aspects of measurable and observable physical quantities.This makes the quantum wave-functions powerful and felicitous to model cognitive states of the human mind,as it inherits the ability to efficiently couple the current context with past experiences temporally and spatially to approach an appropriate future cognitive state.This paper implements and compares some techniques like Variational Quantum Classifiers(VQC),quantum annealing classifiers,and hybrid quantum-classical neural networks,to harness the power of quantum computing for processing cognitive states of the mind by making use of EEG data.It also introduces a novel pipeline by logically combining some of the aforementioned techniques,to predict future cognitive responses.The preliminary results of these approaches are presented and are very encouraging with upto 61.53%validation accuracy.展开更多
基金Supported by Fund of Cotton Industrial Economic Experts of Modern Agricultural Technology System in Shandong Province[Shandong Agricultural Science and Technology(2012)No.26]Fund of Soft Science Research Base for Issues Concerning Agriculture and Countryside and Farmers in Shandong Province(2007RKA003)
文摘Affected by the meteorological disasters and market fluctuations,the growing area,yield and quality of cotton in Shandong Province have been reduced to varying degrees in recent years.The majority of farmers are regarded as the main body of agricultural production,whose enthusiasm for growing cotton and confidence in the cotton market play a significant role in stabilizing the growing area and improving the quality of cotton.We randomly select the cotton farmers for in-depth interview,to understand the situation of cotton cultivation and their state of mind for growing,aimed at deriving the factors influencing farmers'willingness to grow cotton.In the future,it is necessary to make the best use of the advantages and bypass the disadvantages,and in a timely manner curb the decline of cotton cultivation in the process of guiding and encouraging the cotton cultivation,in order to solve the problems of low farmers'willingness to grow cotton and sluggish cotton industry from the root.
文摘Rice yield is still low in Nigeria despite the ecological advantages. Several challenges has been traced it production. The study intend to investigate if other rice producing nations are faced with similar challenges and at what magnitude and more importantly, what can be learn to improve the rice yield in Nigeria. Based on 2013/2014 survey, a total sample of 400 famers were randomly interviewed;164 from Niger State of Nigeria and 236 from Hainan province of China. The study collate the perception of farmers to rice production constraints categorized into biotic, abiotic and socioeconomics. Biplot analysis was employed to examine multivariate pattern of their perceptions towards production constraints. The multivariate technique simultaneously displaying different yield levels and factor constraints in data matrix providing the inter-unit distances, variance and correlations of variables. According to the study, Niger state farmers identified socioeconomic constraint as the major factors to production and attributed it to lack of or insufficient investment while the Hainan farmers majorly identified abiotic constraints. The study also indicated that great potential remain to further improve rice yield in both regions especially in Nigeria given the appropriate investment on essential inputs. This study is of great use to extension officers more so, given the investment in Africa, policy makers take advantage of the bilateral and multilateral relationship to invest ease transfer of agricultural information and technologies between or among partners.
文摘Aflatoxin associated with a number of cereals and legumes is estimated to increase the chances of developing primary liver cancer in 152.7 and 61.1 cancer/year/100,000 population of infants and children, respectively in Nigeria. This study was carried out to assess the implications of some agronomic practices on the infestation of aflatoxigenic fungi and total aflatoxin in maize produce in Benue State. Two maize sample types (Pre-harvest and Post-harvest) collected from 3 locations in Benue State were cultured on Sabouraud dextrose agar for fungi isolation and identification. Moisture content and total aflatoxin concentration were determined (ELISA method) in both pre-harvest oven dried and farmer’s post-harvest sun dried samples. Information on agronomic practices was obtained with the aid of questionnaire. T-test and analysis of variance (ANOVA) were used to analyze the data with confident levels set at 95%. Overall, 5 mould genera were identified: Aspergillus (44.0%), Fusarium (24.44%), Botryodiplodia (17.78%), Rhizopus (15.56%) and Penicillium (4.44%). Moisture content of oven dried samples was significantly less than that of farmers sun dried samples (t = 10.45, P < 0.001). Similarly, a significant difference in total aflatoxin concentration was recorded between farmers sun dried and oven dried samples (t = 2.37, P = 0.03). Half of the farmer’s sun dried samples had aflatoxin concentration above the recommended EU (4 ug/Kg) limit, but none of the pre-harvest oven dried samples exceeded EU limits. Maize samples from fertilized farms were more likely than non-fertilized farms to have higher aflatoxin concentration (P = 0.002). Similarly, Maize seeds purchase from the open market were more likely than seeds from previous harvest to be contaminated with aflatoxin (P = 0.003). The study advocates rapid drying of timely harvested maize so as to reduce or stop the action of heavy field fungi contaminants as well as aflatoxin accumulation.
文摘The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems.The states of mind or judgment outcomes are highly complex phenomena that happen inside the human body.Decoding these states is significant for improving the quality of technology and providing an impetus to scientific research aimed at understanding the functioning of the human mind.One of the key advantages of quantum wave-functions over conventional classical models is the existence of configurable hidden variables,which provide more data density due to its exponential state-space growth.These hidden variables correspond to the amplitudes of each probable state of the system and allow for the modeling of various intricate aspects of measurable and observable physical quantities.This makes the quantum wave-functions powerful and felicitous to model cognitive states of the human mind,as it inherits the ability to efficiently couple the current context with past experiences temporally and spatially to approach an appropriate future cognitive state.This paper implements and compares some techniques like Variational Quantum Classifiers(VQC),quantum annealing classifiers,and hybrid quantum-classical neural networks,to harness the power of quantum computing for processing cognitive states of the mind by making use of EEG data.It also introduces a novel pipeline by logically combining some of the aforementioned techniques,to predict future cognitive responses.The preliminary results of these approaches are presented and are very encouraging with upto 61.53%validation accuracy.
