Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a p...Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a predictive model for cassava yield (Manihot esculenta Crantz) amidst climate variability in rainfed zone of Enugu State, Nigeria. This study utilized data of climate variables and tonnage of cassava yield spanning from 1971 to 2012;as well as information from a questionnaire and focus group discussion from farmers across two seasons in 2023 respectively. Regression analysis was employed to develop the predictive model equation for seasonal climate variability and cassava yield. The rainfall and temperature anomalies, decadal change in trend of cassava yield and opinion of farmers on changes in rainfall season were also computed in the study. The result shows the following relationship between cassava and all the climatic variables: R2 = 0.939;P = 0.00514;Cassava and key climatic variables: R2 = 0.560;P = 0.007. The result implies that seasonal rainfall, temperature, relative humidity, sunshine hours and radiation parameters are key climatic variables in cassava production. This is supported by computed rainfall and temperature anomalies which range from −478.5 to 517.8 mm as well as −1.2˚C to 2.3˚C over the years. The questionnaire and focus group identified that farmers experienced at one time or another, late onset of rain, early onset of rain or rainfall cessation over the years. The farmers are not particularly sure of rainfall and temperature characteristics at any point in time. The implication of the result of this study is that rainfall and temperature parameters determine the farming season and quantity of productivity. Hence, there is urgent need to address the situation through effective and quality weather forecasting network which will help stem food insecurity in the study area and Nigeria at large. The study made recommendations such as a comprehensive early warning system on climate variability incidence which can be communicated to local farmers by agro-meteorological extension officers, research on crops that can grow with little or no rain, planning irrigation scheme, and improving tree planting culture in the study area.展开更多
建立一种采用液相色谱法同时测定亚麻荠植株中8种酚酸和黄酮化合物含量的方法,并探讨亚麻荠植株醇提物的体外抗氧化活性。试验确定采用体积分数75%乙醇回流提取样品,选用Angilent Eclipse XDB plus C_(18)柱为色谱柱。结果表明:8种化合...建立一种采用液相色谱法同时测定亚麻荠植株中8种酚酸和黄酮化合物含量的方法,并探讨亚麻荠植株醇提物的体外抗氧化活性。试验确定采用体积分数75%乙醇回流提取样品,选用Angilent Eclipse XDB plus C_(18)柱为色谱柱。结果表明:8种化合物的标准曲线回归方程线性关系良好,相关系数均大于0.999;8种化合物的加标回收率为95.26%~102.61%,建立的方法可以对不同产地的亚麻荠植株样品进行区分。抗氧化试验表明,亚麻荠植株醇提取物对羟基自由基与DPPH自由基具有较好的清除能力。展开更多
文摘Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a predictive model for cassava yield (Manihot esculenta Crantz) amidst climate variability in rainfed zone of Enugu State, Nigeria. This study utilized data of climate variables and tonnage of cassava yield spanning from 1971 to 2012;as well as information from a questionnaire and focus group discussion from farmers across two seasons in 2023 respectively. Regression analysis was employed to develop the predictive model equation for seasonal climate variability and cassava yield. The rainfall and temperature anomalies, decadal change in trend of cassava yield and opinion of farmers on changes in rainfall season were also computed in the study. The result shows the following relationship between cassava and all the climatic variables: R2 = 0.939;P = 0.00514;Cassava and key climatic variables: R2 = 0.560;P = 0.007. The result implies that seasonal rainfall, temperature, relative humidity, sunshine hours and radiation parameters are key climatic variables in cassava production. This is supported by computed rainfall and temperature anomalies which range from −478.5 to 517.8 mm as well as −1.2˚C to 2.3˚C over the years. The questionnaire and focus group identified that farmers experienced at one time or another, late onset of rain, early onset of rain or rainfall cessation over the years. The farmers are not particularly sure of rainfall and temperature characteristics at any point in time. The implication of the result of this study is that rainfall and temperature parameters determine the farming season and quantity of productivity. Hence, there is urgent need to address the situation through effective and quality weather forecasting network which will help stem food insecurity in the study area and Nigeria at large. The study made recommendations such as a comprehensive early warning system on climate variability incidence which can be communicated to local farmers by agro-meteorological extension officers, research on crops that can grow with little or no rain, planning irrigation scheme, and improving tree planting culture in the study area.
文摘建立一种采用液相色谱法同时测定亚麻荠植株中8种酚酸和黄酮化合物含量的方法,并探讨亚麻荠植株醇提物的体外抗氧化活性。试验确定采用体积分数75%乙醇回流提取样品,选用Angilent Eclipse XDB plus C_(18)柱为色谱柱。结果表明:8种化合物的标准曲线回归方程线性关系良好,相关系数均大于0.999;8种化合物的加标回收率为95.26%~102.61%,建立的方法可以对不同产地的亚麻荠植株样品进行区分。抗氧化试验表明,亚麻荠植株醇提取物对羟基自由基与DPPH自由基具有较好的清除能力。
