scholarly journals Effect of Climate Variables in Rice Yield in Nueva Ecija, Philippines

2020 ◽  
Vol 9 (1) ◽  
pp. 29-44
Author(s):  
Andro M. Enovejas ◽  
◽  
Sharmaine Maldia ◽  
Nurul Amri Komarudin ◽  
Dante Gideon K. Vergara ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Climate Variability ◽  
Minimum Temperature ◽  
Rice Yield ◽  
Cropping System ◽  
The Philippines ◽  
Climate Variables ◽  
Yield Data ◽  
Mean Temperature ◽  
Rainfed Farming

Climate variability is one of the factors that directly and greatly affect cropping system and plant yield. It is therefore very important to obtain a good understanding about climate variability or changes in the climate and the effect of these changes to clearly understand the vulnerability of food crops as well as its agronomic impacts for us to create and implement adaptive strategies to mitigate its negative effects. This study assessed the effect of climate in rice crop yield in both irrigated and rainfed ecotype farming system in Nueva Ecija Province in the Philippines using semi-annual yield data and the different climate variables such as seasonal rainfall, mean temperature, minimum temperature, and relative humidity by using empirical/statistical method through time series analysis, and correlation analysis. Results indicated that rice yield for irrigated and rainfed ecosystem type of farming in Nueva Ecija show an overall increasing trend from year 1991-2018, although there are observed decline and fluctuations in some years. The different climate variables (i.e., rainfall, temperature, and humidity) show fluctuating trends and irregularities spanning from the year 1991-2018. But it showed overall decreasing trends for relative humidity and increasing trends for rainfall, minimum temperature, and mean temperature. There are significant correlations between rice yield the all the climate variables in both irrigated and rainfed farming ecosystem types.

scholarly journals Evaluating the Yield Response of Maize (Zea mays L.) and Rice (Oryza sativa L.) to Future Climate Variability in The Gambia

2019 ◽  
Vol 7 (2) ◽  
pp. 11
Author(s):  
Ebrima Sonko ◽  
Sampson K. Agodzo ◽  
Philip Antwi-Agyei
Keyword(s):  
Climate Variability ◽  
Rice Yield ◽  
Oryza Sativa L ◽  
Maize Yield ◽  
Future Climate ◽  
Yield Response ◽  
Climate Data ◽  
Negative Effects ◽  
Yield Data ◽  
Maize Cultivars

Climate change and variability impact on staple food crops present a daunting challenge in the 21st century. The study assesses future climate variability on maize and rice yield over a 30-year period by comparing the outcomes under two GCM models, namely, CSIRO_RCP4.5 and NOAA_RCP4.5 of Australia’s Commonwealth Scientific and National Oceanic and Atmospheric Administration respectively. Historical climate data and yield data were used to establish correlations and then subsequently used to project future yields between 2021 and 2050. Using the average yield data for the period 1987-2016 as baseline yield data, future yield predictions for 2021-2030, 2031-2040 and 2041-2050 were then compared with the baseline data. The results showed that the future maize and rice yield would be vulnerable to climate variability with CSIRO_RCP4.5 showing increase in maize yield whilst CSIRO_RCP4.5 gives a better projection for rice yield. Furthermore, the results estimated the percentage mean yield gain for maize under CSIRO_RCP4.5 and NOAA_ RCP4.5 by about 17 %, 31 % and 48 % for the period 2021-2030, 2031-2040 and 2041-2050 respectively. Mean rice yield lossess of -23 %, -19 % and -23 % were expected for the same period respectively. The study recommended the use of improved rice and maize cultivars to offset the negative effects of climate variability in future.

scholarly journals Identifying Climatic Variables with Rice Yield Relationship and Land Cover Change Detection at Sylhet Region

2019 ◽  
pp. 1-12 ◽  
Author(s):  
Gazi Tamiz Uddin ◽  
Md. Altaf Hossain ◽  
Fahmida Ishaque
Keyword(s):  
Relative Humidity ◽  
Land Cover ◽  
Land Cover Change ◽  
Rice Yield ◽  
Flash Flood ◽  
Climatic Variables ◽  
Landsat 8 ◽  
Yield Data ◽  
Vegetation Condition ◽  
Boro Rice

The study is conducted to determine the correlation between climatic parameters and rice yield. The present study is also undertaken to analyze the land cover change in Sylhet district between 2013 and 2018 using LANDSAT-8 images. Local climate and rice yield data are collected from BMD (Bangladesh Meteorological Department) and BRRI (Bangladesh Rice Research Institute) and BBS (Bangladesh Bureau of Statistics). ArcGIS 10.5 and SPSS software are used to show the vegetation condition and correlation coefficient between rice yield and climatic variables respectively. It is revealed from the result that rainfall is negatively correlated with Aman and Boro (local and HYV) rice whereas temperature and relative humidity showed a positive correlation with local Aman and Boro rice. On the other hand, relative humidity showed a strong linear relationship with HYV Boro rice. Finally, both temperature and relative humidity have substantial effects on yields in the Boro rice. Furthermore, vegetation condition is observed through NDVI and found the moderate-high vegetation in 2013. After that NDVI value is fluctuating which evidently signifies the rapid vegetation cover change due to a flash flood, flood and other climate changing aspects. Additionally, Forested and high land vegetation’s are endangered rapidly. Some adaptation strategies should be followed to minimize the effects of natural calamities for improving better vegetation condition.

scholarly journals Assessment of Climate Variability Trends in Nasarawa State, Nigeria

2020 ◽  
pp. 41-50
Author(s):  
Oladeinde Stephen Olufemi ◽  
Magaji I. Joshua ◽  
Ekpo Abraham Salamatu
Keyword(s):  
Climate Variability ◽  
Minimum Temperature ◽  
Global Climate ◽  
Linear Trend ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Climate Variables ◽  
Daily Data ◽  
Annual Total ◽  
Slope Line

Changing global climate has emerged as one of the greatest environmental problems of mankind in the 21st century. However, there is still a dearth of information regarding the trends and patterns of climate variables at local and specific levels. It is against this background that this paper assessed climate variability trends in Nasarawa State, Nigeria over 21 years’ period (1997 – 2017). Daily data on climate variables for the State was obtained from the Nigerian Meteorological Agency and analysed using the linear trend function in Microsoft Excel. Pattern and course of the variables’ trend were determined using the trend/slope line and the trend equation. Out of the six investigated climatic parameters; maximum temperature, minimum temperature, total annual rainfall and dew points experienced the greatest fluctuation in Nasarawa State during the 21 years’ period (1997 – 2017). Also, while maximum and minimum temperature generally assumed an increasing trend, annual total rainfall and dew points alongside relative humidity and wind speed were generally decreasing. Policymakers in the various earth’s supporting systems such as agriculture, land and water, should employ the key findings of this study for advising some suitable adaptation and mitigation policies to cope with climate variability and change.

scholarly journals Effect of temperature variation on Aman and Boro rice production of Barisal division in Bangladesh

2019 ◽  
Vol 30 (1) ◽  
pp. 95-103
Author(s):  
J Karmokar ◽  
MM Billah ◽  
MA Haque
Keyword(s):  
Temperature Variation ◽  
Minimum Temperature ◽  
Rice Yield ◽  
Rice Production ◽  
Series Data ◽  
Maximum Temperature ◽  
Seasonal Temperature ◽  
Mean Temperature ◽  
The Impact ◽  
Boro Rice

A study was undertaken to study the impact of seasonal temperature variation on Aman and Boro rice production in Barisal division of Bangladesh. The study revealed that the relationship between changing patterns of seasonal mean temperature and yield of rice, which illustrates the average mean temperature for the correlation of time series data from 1958-2008. The regression model is used to analyze the different temperature trends, and to identify the possible factors and causes of these differences. The value of t-statistic for slope and p-value for different regression equations are estimated. Results show that the average maximum temperature is risk increasing for Boro, while it is risk decreasing for Aman for the period of 2006-2008. Besides, minimum temperature is risk increasing for Boro during 1994-2008 but it is risk decreasing for Aman except the year 1998. We observed that the summer temperature has been rising up during the period 1958-1974 and fallen down for 1992-2008. The average annual temperature changes from 0.5˚C to 1˚C over the period from 2005 to 2008 which impact on Aman and Boro rice yield. Therefore, the predictive approach provides an outline for future risk of the minimum temperature that has the impact on rice yield than maximum temperature, which can be used for rice production for its better management strategies. Progressive Agriculture 30 (1): 95-103, 2019

scholarly journals Climate Variability and Sugarcane Yield in Louisiana

2005 ◽  
Vol 44 (11) ◽  
pp. 1655-1666 ◽  
Author(s):  
David Greenland
Keyword(s):  
Climate Variability ◽  
Soil Water ◽  
Climatic Variables ◽  
Climate Variables ◽  
Yield Data ◽  
Climatic Environment ◽  
Monthly Total Precipitation ◽  
Sugarcane Yield ◽  
Yield Values ◽  
Crop Variety

Abstract This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield–climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV)], mean maximum August temperature, mean minimum February temperature, soil water surplus between April and September, and occurrence of autumn (fall) hurricanes, were built into a model to simulate adjusted yield values. The CCV model simulates the yield value with an rmse of 5.1 t ha−1. The mean of the adjusted yield data over the study period was 60.4 t ha−1, with values for the highest and lowest years being 73.1 and 50.6 t ha−1, respectively, and a standard deviation of 5.9 t ha−1. Presumably because of the almost constant high water table and soil water availability, higher precipitation totals, which are inversely related to radiation and temperature, tend to have a negative effect on the yields. Past trends in the values of critical climatic variables and general projections of future climate suggest that, with respect to the climatic environment and as long as land drainage is continued and maintained, future levels of sugarcane yield will rise in Louisiana.

scholarly journals ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR OKRA YIELD PREDICTION

2017 ◽  
Vol 15 (2) ◽  
pp. 95-102
Author(s):  
O A OJESANMI ◽  
A D ADEKOYA ◽  
A A AWOSEYI
Keyword(s):  
Relative Humidity ◽  
Fuzzy Inference System ◽  
Minimum Temperature ◽  
Fuzzy Inference ◽  
Meteorological Data ◽  
Maximum Temperature ◽  
Yield Prediction ◽  
Yield Data ◽  
Inference System ◽  
Neuro Fuzzy

This paper, adaptive neuro-fuzzy inference system for okra yield prediction, describes the use of neuro-fuzzy inference system in the prediction of okra yield using environmental parameters such as minimum temperature, relative humidity, evaporation, sunshine hours, rainfall and maximum temperature as input into the neuro-fuzzy inference system, and yield as output. The agro meteorological data used were obtained from the department of agro meteorological and water management, Federal University of Agriculture, Abeokuta and the yield data were obtained from the Department of Horticulture, Federal University of Agriculture, Abeokuta. MATLAB was used for the analysis of the data. From the results, the maximum predicted yield showed that at minimum temperature of 24.4 oc, relative humidity of 78.3% and evaporation of 5.5mm, the yield predicted is 1.67 tonnes/hectare. 

Development of a decision support system for small reservoir irrigation systems in rainfed and drought prone areas

2010 ◽  
Vol 61 (11) ◽  
pp. 2779-2785 ◽  
Author(s):  
Orlando F. Balderama
Keyword(s):  
Decision Support ◽  
Water Reservoir ◽  
Cropping System ◽  
The Philippines ◽  
Climate Conditions ◽  
Crop Selection ◽  
Agricultural Planning ◽  
Rainfed Farming ◽  
Resource Data

An integrated computer program called Cropping System and Water Management Model (CSWM) with a three-step feature (expert system—simulation—optimization) was developed to address a range of decision support for rainfed farming, i.e. crop selection, scheduling and optimisation. The system was used for agricultural planning with emphasis on sustainable agriculture in the rainfed areas through the use of small farm reservoirs for increased production and resource conservation and management. The application of the model was carried out using crop, soil, and climate and water resource data from the Philippines. Primarily, four sets of data representing the different rainfall classification of the country were collected, analysed, and used as input in the model. Simulations were also done on date of planting, probabilities of wet and dry period and with various capacities of the water reservoir used for supplemental irrigation. Through the analysis, useful information was obtained to determine suitable crops in the region, cropping schedule and pattern appropriate to the specific climate conditions. In addition, optimisation of the use of the land and water resources can be achieved in areas partly irrigated by small reservoirs.

Assessment of Weather and Climate-Related Risks to Human Health in Different Areas of the Krasnoyarsk Region

2021 ◽  
pp. 61-66
Author(s):  
DA Narutdinov ◽  
RS Rakhmanov ◽  
ES Bogomolova ◽  
SA Razgulin
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Human Health ◽  
Minimum Temperature ◽  
Temperate Climate ◽  
Maximum Wind ◽  
Average Wind ◽  
Weather And Climate ◽  
Effective Temperatures ◽  
Temperate Climates

Introduction: Extreme climate conditions have a negative impact on human health. Purpose: The study aimed to assess weather and climate-related risks to human health in different areas of the Krasnoyarsk Region by effective temperatures estimated during two long-term observation periods. Materials and methods: We analyzed ambient temperatures (average monthly and minimum), wind speed (average and maximum), and relative humidity in the subarctic and temperate continental zones estimated during the periods of determining climatic norms in 1961–1990 and 1991–2020. The health risk was assessed on the basis of effective temperatures. Results: In the subarctic zone, the wind strength (average and maximum values) decreased, the duration of such periods increased just like the ambient temperature while the relative humidity did not change. In temperate climates, all indicators have changed. In the subarctic zone, in the second observation period, frostbite was possible within 20–30 minutes during two months (versus 3 in the first). In the temperate climate, there was no such risk to humans. At the minimum temperature and maximum wind speed in the subarctic zone, the risk of frostbite is possible during 5 months (versus 6): after 10–15 minutes during two months and after 20–30 minutes – during three months of the year. In temperate climates, frostbite is possible within 20–30 minutes during two months (versus 3 in the first period). Conclusions: In the interval of establishing climatic norms (1991–2020), a significant increase in effective temperatures was determined: in the subarctic zone with the average wind strength and temperature in February–April and June, with maximum wind and minimum temperature – in March–July; in temperate climates, in April and June, respectively. The duration of periods of health risks posed by cold temperature exposures in the subarctic climate with average wind and temperature values equaled two months (I–II), with maximum wind speed and minimum temperatures – five months (XI–III); in the temperate climate, it was null and 2 (3) months (I, II, and XII), respectively.

Impact of weather parameters on alternaria blight of Indian mustard [(Brassica juncea (L.) Czern. & Coss.)]

2021 ◽  
Vol 50 (1) ◽  
pp. 15-19
Author(s):  
Rakesh Punia ◽  
Pavitra Kumari ◽  
Anil Kumar ◽  
AS Rathi ◽  
Ram Avtar
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Disease Severity ◽  
Vapour Pressure ◽  
Minimum Temperature ◽  
Indian Mustard ◽  
Maximum Increase ◽  
Alternaria Blight ◽  
Progress Curve ◽  
Sunshine Hours

Progression of Alternaria blight disease was measured on two susceptible Indian mustard varieties viz., RH 30 and RH 0749 sown at three different dates. The maximum increase in disease severity was recorded between first weeks of February and last week of February. During this period, the maximum and minimum temperature, relative humidity at morning and evening, average vapour pressure of morning and evening, maximum and bright sunshine hours and wind speed were higher, which resulted in congenial conditions for severe infection by the pathogen. The disease severity was positively correlated with maximum and minimum temperature, average vapour pressure, wind speed, sunshine hours and evaporation, while relative humidity and rainfall negatively correlated with Alternaria blight on both the varieties. A maximum value of area under disease progress curve was observed on cultivar RH 30 (651.1 cm2) as compared to RH 0749 (578.9 cm2), when crop was sown on 9th November.

scholarly journals Characteristics of Size Change of Tropical Cyclones Traversing the Philippines

2018 ◽  
Vol 146 (9) ◽  
pp. 2891-2911 ◽  
Author(s):  
Shu-Jeng Lin ◽  
Kun-Hsuan Chou
Keyword(s):  
Angular Momentum ◽  
Relative Humidity ◽  
Tropical Cyclones ◽  
Momentum Flux ◽  
Vertical Wind Shear ◽  
The Philippines ◽  
Sea Surface ◽  
Japan Meteorological Agency ◽  
The South ◽  
Size Change

Abstract This study investigates the size changes of tropical cyclones (TCs) traversing the Philippines based on a 37-yr statistical analysis. TC size is defined by the radius of 30-kt (≈15.4 m s−1) wind speed (R30) from the best track data of the Japan Meteorological Agency. A total of 71 TCs passed the Philippines during 1979–2015. The numbers of size increase (SI; 36) and size decrease (SD; 34) cases are very similar; however, the last 15 years have seen more SI cases (17) than SD cases (11). SI and SD cases mostly occur along northerly and southerly paths, respectively, after TCs pass the Philippines. Before landfall, SI cases have small initial sizes and weak intensities, but SD cases have larger initial sizes and stronger intensities. After landfall, most SI cases are intensifying storms, and most SD cases are nonintensifying storms. Composite analyses of vertical wind shear, absolute angular momentum flux, relative humidity, and sea surface temperature between SI and SD cases are compared. All of these values are larger in SI cases than in SD cases. Furthermore, the interdecadal difference in the ratio of the numbers of SI to SD cases reveals an unusually high number of SI cases during 2001–15. The synoptic patterns between 1979–2000 and 2001–15 are analyzed. The high SI ratio in the latter period is related to strong southwesterly wind in the south of the South China Sea that raised relative humidity, warmed the sea surface, and increased import of angular momentum flux.

Sign in / Sign up

Export Citation Format

Share Document