Effects Of Climate Variables On Crop Productivity Essay

Forty percent of the earth’s land cover is classified as either arid or semi-arid environment (Clark Davis & Kay 1983), in which, billions of people mainly from developing countries, live and work. Many of the arid zone environment is classified as to dry to grow crops (Creswell & Martin 1998). Still, crops like sorghum, millets (CONSORTIUM 2011) and cashes (Creswell & Martin 1998) are grown with reasonable success, as the plants or farmers have been able to adapt to the dry environment (Creswell & Martin 1998).

Today’s world is facing many challenges given the growing concerns and current repercussions of environmental climate change and demands of a growing global population. Not only is climate change effecting the worlds ecosystems, human health and fresh water resources, it is drastically effecting the worlds agriculture. Unpredictable weather such, as rising temperatures, colder temperatures, excessive flooding, and droughts are just a few of the increasing weather instabilities, which are challenging and threatening today’s agriculture growth and production. As such, crop yields continue to decline and present a risk to future food security. As a world, we are facing an adaptation deficit leaving us very vulnerable and thus, we must seek to

The purpose of this study is to help model one of the world’s most economically important crops, coffee. In this article Brunsell and his colleagues are trying to relate the variations in yield of coffee with microclimatic variations, as well as agricultural practices. In doing so this will help them better understand the impacts that global climate change will have on not only coffee crops but it could also even help them with other crop disturbances that will happen during climate change. This article is an important piece

Agriculture is highly dependent upon weather and climate in order to produce the food necessary to sustain human life. North America is the world’s largest and most productive supplier of food and fiber (3). Canada is the second largest country in the world however it only contains five percent of land that is suitable for farming (7). This small farming area is divided in two different zones. The first zone is the great Prairies located in Alberta, Saskatchewan and Manitoba and the mixed Wood Plains of the St. Lawrence River and the second zone is the Great Lakes regions (7). Approximately 80% of Canada’s major farming is done the Prairies (7). There have been several recent studies that indicate most regions of Canada to warm up during the next 60 years (3). The Intergovernmental Panel on Climate Change (IPCC) in 2007 projected that global average temperature to increase by 1.5 to 4.5 degrees Celsius (3). Ironically, this would be the largest increase in global mean temperature in the last 10, 000 years (3). According to the comprehensive Canada Country Study (CCS) all the Global Climate Model (GCM) indicates Canada will be impacted with the most warming (7). The impacts of this climate change will be greatly reflected on the

of soil types and climate conditions. It can produce 2 to 3 times more crop than

In the article “ Warming world is a threat to the world’s food supplies,” CCPA Monitor writer John Vidal (2013) explains that climate change affects food supplies and triggers a domino effect in the world, such as economy, policy, environment, and agriculture. The writer also indicates most vulnerable people are easily affected by climate change, as the poor people and children and the number of those people still rising. There will be up to 2 billion more people to be fed by 2050. According to the author, climate change will cause crop shortages and price increases, that government are actively adjusting countermeasure to the issues (Vidal, 2013).

(2014) built on this research by using the biophysical crop production simulation model APSIM (Agricultural Production Simulator, (Keating et al. 2003) with one of the hottest and driest future climate change scenarios (the CSIROMk3.5 A1FI scenario) to provide information on the impact of climate change on cotton yield and irrigation water requirements for the southern Queensland region. These simulations highlight the complexity of the cotton production system especially the ameliorating effect of CO2 fertilisation on growth that would otherwise be highly compromised with decreased rainfall. The simulations indicate yields increasing by 5.9% to 2030, but then decreasing by 3.6% to 2050.

The data that has been presented will now be broken down and simplified as well analysed as to what it all means for the agriculture business sector. However, there may be additional information included to help support our findings. Presently the agriculture system is already struggling with the increased demand for food and renewable energy. Now with the climate change issues of temperature increases, raised sea levels, the issues of water scarcity, pollution, and soil degradation are also now playing a large factor in today’s struggles. Small differences in weather or more specifically temperature can affect a farmer’s crop more than we realise. Crops with a higher level of average temperature will require more water in order to stay

Arid and semiarid regions are seriously lacking in fresh water. Water shortages in these regions have become the basic norm rather than the exception. Most importantly, the situation of water shortage is growing worse due to abrupt climatic changes and continuous population growth. All of these factors will decrease the amount of water allocated to the agricultural sector, which consumes about 75% of the available water supply. Therefore, as the water supply for agronomic purposes becomes insufficient, development of new germplasms with higher yield potential becomes more imperative and it will be one of the major adaptation strategies to sustain crop productions under arid and semiarid conditions. In order to improve the germplasms for these conditions, it is essential to evaluate a large number of genotypes using multiple selection criteria. Several morpho-physiological traits, particularly those related to crop processes, yield characteristics, and drought-tolerance mechanisms such as relative water content, canopy water content, SPAD value and normalized relative canopy temperature are usually effective as useful complementary selection criteria for screening germplasms under different environmental conditions (Chen et al., 2012; Elsayed et al., 2015). Direct measurements of those traits by traditional methods are destructive and time-consuming and some of them are difficult to do when a large number of genotypes need to be evaluated across different

The development of modern crop varieties for developing countries began in a concerted fashion in the late 1950s. Food prices rose after World War 2 due to rapidly increasing population and the reduced availability of land in many countries. The Food and Agriculture Organization of the United Nations coordinated wheat and rice breeding schemes. They key break-through was the development of short, fertilizer-responsive rice and wheat varieties. These varieties were resistant to disease and insects and were used as model plant types for breeders to adapt to local conditions. The first users of the wheat and rice varieties were in India, Malaysia and Pakistan in 1965 (Evenson, 2003). They produced spectacular increases in yield

We divided the time domain into three periods, baseline period (1990-2011) and mid future (2046-2065) and far future (2081-2099) periods for climate change scenario analysis in the present study. Moreover, the model requires good quality observed data (1990-2011) to calibrate with NASA (National Aeronautics and Space Administration) data which obtained from the Global Yield Gap Atlas (GYGA, http://www.yieldgap.org). Depending on projection data availability in five regions for an observed period (1990-2011) and two future periods (2046-2065) and 2081-2100) were taken into consideration for future yield simulation of rice. The predicted changes in climate and their impacts need to be assessed relative to the observed period. The observed climate (1990-2011) is significantly different from the climate of the past years, for example, 1961-1990. Similarly, some climate change studies have been used the daily observed weather data as a reference (baseline period) climate (Kumar et al. 2014). Table 1 illustrates the relative change of mean maximum and minimum temperature, total

The model constructed relies on own survey data and some statistical data from national and regional surveys. This data was used in parameterization and calibration activities. In the survey, heaping, a typical error in agricultural data, was presented (Beegle et al. 2012). Heaping is a special case of data coarsening where respondents round quantitative information (e.g. “around one hectare” may in reality be either 1.2 or 0.8 hectare). This could have an influence on the estimates of production functions, as happened with Schreinemachers (2006). Another problem was the farmers use local reference units and we lack conversion tables for those units. For instance, outputs of some crops such as plantain, cassava or fruits were reported in bunch or bags without specifying their weights in kg. In order to overcome this later problem, a conversion table was built during interviews, through asking members of the community with more education and also key experts. Information about fertilizer and pesticides was recorded by plot and not by crop, a problem mentioned in section 6.2.2.1.1.

By the 1990s, almost 75% of the area under rice cultivation in Aisa was growing these new varieties. The same was true for almost half of the wheat planted in Africa and more than half of that in Latin America and Asia, and more than 50% of the world's corn as well. Overall, a very large percentage of farmers in the developing world were using Green Revolution seeds, with the greatest use found in Asia, followed by Latin America.

Mexico’s agricultural sector is renown in the international community for a myriad of goods that it produces. From the cultivation of crops, sustainable soils, land usage and irrigation systems, its rich land has helped Mexico’s economy prosper in the 21st century. This feat is largely due to the country’s production and exportation of maize, one of their largest crops. However, in recent times Mexico’s agriculture sector has been affected by the vices of climate change and greenhouse emission gases amongst other natural phenomenons. For the purpose of this paper the change of climatic patterns in areas of temperature, precipitation and intensity will be discussed, as well as its correlation to climate change and current weather trends, which have created unsustainable environments for maize to grow.

Precision agriculture, access to finances and technology, quality seeds, and integrated crop/pest management knowledge are topics that ought to be focal points in the body of this paper. Soil science may be considerably less exciting than global production statistics, but these basics are at the core of the yield gap issue. Moreover, it is likely that governments and environmental stakeholders are aware of the agricultural/environmental statistics, but are unlikely to know how to support individual farmers in a way that promotes resilient and productive growth. Tangible methods are necessary for change, especially when providing guidance at the governmental level. On a positive note, the data that the authors provide about the potential calorie gains by closing the yield gap is highly valuable, and could provide incentives and targets for policymakers. While closing the yield gap will eventually be necessary to feed a growing population, it does nothing to increase food access for populations that are already food insecure.