网范文：“ National trends on agricultural crops production” 从描述性的数据中，探讨了15年期间作物生产和栽培面积,这篇农学范文探讨的目的是揭示作物栽培上的趋势。揭示作物类之间的联系。按时间序列略论揭示了显著降低某些农作物的生产,如亚麻、大麻、甜菜等。在1989年罗马尼亚农业的贡献在国民生产总值(GNP)占比大约是13.7%,增加到1995年的18.6%,下降到1999年的12.9%。
罗马尼亚生产的主要农作物是小麦、黑麦、大麦和棱大麦、玉米、大豆、向日葵等等。今天产量必须对齐到欧盟的政策，并应对气候变化。基于描述性信息，略论种植面积和作物总产量，探讨的目的是确定国家作物生产的趋势,以及不同作物之间的联系。下面的范文进行详述。
Abstract
Staring from descriptive data on crop production and cultivated area at national level during on fifteen years, the aim of this study is to reveal the trends on crops cultivation. The cluster analysis reveals linkages between crops classes as well as between different crops, which can be partly assigned to crops rotation. Time series analysis reveals dramatically reducing of production of some crops, such as flax, hemp, and sugar beet, and increasing of production, such at sunflower, and increasing of productivity, such at potatoes and field vegetables.
INTRODUCTION
The Romanian agriculture used to have a major contribution to Romanian economy but unfortunately the return of collectivized farmland to its cultivators, one of the first initiatives of the post-December 1989 revolution government, resulted in a short-term decrease in agricultural production. Some four million small parcels representing 80% of the arable surface were returned to original owners or their heirs (Dawidson, 2017). Many of the recipients were elderly or city dwellers, and the slow progress of granting formal land titles was an obstacle to leasing or selling land to active farmers. The contribution of agriculture to the Gross National Product (GNP) in Romania was around 13.7% in 1989, increasing to 18.6% in 1995 and decreasing to 12.9% in 1999 and 11.4% in 2017 respectively (MARD, 2017).
The major crops produced in Romania are: wheat and rye, barley and two-row barley, corn, soya, sunflowers (Turtoi et al., 2017), oats, rice, hay, potatoes, soybeans, sugar beets, feed roots, corn silage, and tobacco (Bachman, 1989). Today, the crops production must be aligned to the policy of European Union (Chantreuil et al., 2017; Hertel et al., 1997) and to the climate changes (Cuculeanu et al., 1999). Based on descriptive information about cultivated area and total production by year and by crop the aim of the study is to identify national trends in crops production, as well as linkages between productions of different crops.
MATERIAL AND METHOD
Material Nine main crops cultivated in Romania on a period of fifteen years (from 1990 to 2017) have been investigated. Data were taken from administrative sources: National Administrative of Land Improvement, for Agricultural Irrigated Area and Ministry of Agriculture, Forests 194 and Rural Development (Romanian Statistical Yearbook, 2017). The investigated main crops were: Cereals for grains: wheat and rye, barley and two-row barley, oats, maize, sorghum, rice; Leguminous crops for beans: peas beans, bean; Industrial crops: Fiber crops: flax for fiber, hemp for fiber; Oilseed crops: sunflower, rape, soya beans, flax for oil, castor plant; Other industrial crops: sugar beet, tobacco, medicinal and aromatic plants; Potatoes: autumn potatoes; Vegetables: tomatoes, dry onion, dry garlic, cabbage, green peppers, edible roots; Water melons and melons; Fodder crops: old and new perennials, lucerne, clover, annuals for hay and green fodder; Plants used for silage: maize for silage, fodder roots; Total Fruits: plums, apples, pears, peaches, cherries and sour cherries, apricots and engrafted apricots, nuts, strawberries, and other fruits.
A time series is a sequence of data points, measured typically at successive times, spaced at (often uniform) time intervals. Note that our data fits to this definition. Time series analysis comprises methods that attempt to understand such time series, often either to understand the underlying theory of the data points (what generated them?), or to make forecasts (predictions). Time series coming from earth and life sciences study include trend, cyclicity, and periodicity (Jäntschi, 1995). Clustering is the classification of objects (our objects are crops) into different groups, or more precisely, the partitioning of a data set into subsets (named clusters), so that the data in each subset (ideally) share some common trait - often proximity according to some defined distance measure. Data clustering is a common technique for statistical data analysis, which is used in many fields, including data mining and bioinformatics (Bolboacă and Jäntschi, 2017). We used both time series analysis and cluster analysis for our purpose of trend and linkages identification on national crop production. The subjects of analysis were cultivated area, and crop production for main crops.
CONCLUDING REMARKS
Cluster analysis as well as time series analysis reveled that cereals for grains are an apart class of crops in terms of cultivated area and production at national level, having not only the most important part at national level, but also being totally different from all others. Rotation of cultures has also an important influence on crop production and cultivated areas at national level, as were underlined for wheat, lucerne and maize. Some cultures have been almost abandoned, such as flax, hemp, and sugar beet. Other cultures such as potatoes and field vegetables increases in total production, even if it decreases in cultivated area. Sunflower is one of few cases of increasing of both cultivated area and productivity, over 95% being produced by private majority ownerships in 2017.()
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