Time Series Analysis and Forecasting Techniques on the Horticulture Crops in India

Horticulture is a branch of agriculture that deals with the art, sciences, technology and business of plant cultivation. Horticulture has improved economic status of farmer’s seasonal availability of fruits and vegetables throughout the year increased. This study was conducted to forecast the horticulture crops in India for the years from 2019 to 2021. And the study aim to find out the correctness of forecasting methods on the data collected from the source of horticulture crops in India.


Introduction
Time series modeling and forecasting has basic importance to varied sensible domains. Hence a lot of active research works goes on during this subject throughout many years. Several necessary models are planned in literature for up the accuracy and potency of your time series modeling and forecasting. Horticulture in India is branch of agriculture that deals with the art, sciences, technology and business of plant cultivation. Though horticulture may be a separation of an agriculture that deals with plant, plant farming, it's really totally different from agriculture. The necessity for diversification to horticulture sector was acknowledged by the govt. of India in middle eighties by focusing its attention on investment during this sector. Presently husbandry has established its credibleness in up financial gain through exaggerated productivity, generating employment and in enhancing exports.
Resultantly, horticulture has moved from rural compass to business venture. Among a category of forecasting techniques, a specific forecasting technique for a given knowledge set is selected by using one of the criteria for model choice. In most forecasting things, accuracy is treated because the preponderant criteria for choosing forecasting techniques. Generally, accuracy refers to "goodness of fit", that successively visit however well the chosen forecasting model is ready to breed the info that are already renowned. In applied mathematics or time series modeling it's attainable to use a set of the renowned knowledge to forecast the remainder of the renowned knowledge, enabling one to review the accuracy of the forecasts a lot of directly. Suppose yt be the particular knowledge for fundamental quantity t; Ft be the forecast (or

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Mini tab could be a product that helps you to research the information. This is often designed primarily for the Six Sigma Professional. It provides an easy, effective way to input the applied mathematics knowledge, manipulate that knowledge, determine trends and patterns, so extrapolate answers to these problems. This is often most generally used package for the business of all sizeslittle, medium and enormous. Minitab provides a fast, effective answer for the level of analysis required in most of the Six Sigma projects. 3. If you wish, use any panel choices, and then click OK. 4. Empirical Work 4.1 India production: horticulture crops: Spices Spice could be a dried seed, fruit, rot, bark, or vegetative substance primarily used for seasoning, coloring or protective sensible. Generally a spice is employed to cover alternative flavors. Spices are distinguished from herbs that are components of leafed inexperienced plants additionally used for seasoning or as garnish. Several spices have antimicrobial properties, they're additional unremarkably utilized in hotter climates, wherever additional infectious diseases, are prevailing. A spice could have an additional use, typically healthful, ceremony, cosmetics or fragrance production, or as a vegetable. Asian nation is that the world"s largest producer of turmeric (Curcuma longa), a perennial herb of the family ginger. The plant"s underground stems or rhizomes are used as spice, dye, drugs and spiritual maker since antiquity. To find out the correctness of forecasting methods on the information collected from the supply of horticulture crops in India throughout the year 2001 to 2018, more the study is to predict the forecast and forecast errors for 3 consecutive years from 2019 to 2021.

1: Forecast and Forecast error for the horticulture crops (Spices) using Linear Trend Model
Year

Chart 3: Double Exponential Method (spices)
After careful examination, it's apparent that the mean absolute error percentage is least i.e., MAPE = 12% in the case of the method linear trend model, thus to review and analyse the spices crop production in India and to predict for future values the linear trend model could also be adopted.

Name of the horticulture crop: Vegetables
The vegetable production in India has hyperbolic many manifolds with gradual increase in productivity and space of vegetable cultivation over the years that maintains its second ranking in world vegetable production once china. The standing and growth of vegetable production in India and its current state of affairs viz.
India is that the second largest producer of vegetables next to china within the world. In India its is fully grown in a locality of 9.575 million hectares with the productivity of 17.7% m/h that contributes 14% of the entire world population of vegetables.  The ministry has additionally explicit that fruit production in India is quicker than vegetable, despite the later constituting a bigger section of the horticulture sector. In fact, India is that the world"s leading producer for a few fruits likes banana, mango and papaya, whereas it's the second largest producer of sugarcane and also the third largest producer of coconut. Among Indian states, Andhra Pradesh is the largest fruit manufacturing state with 13.939 tones followed by Maharashtra, Gujarat and Tamil Naidu. It is quite conclusive from the higher than facts and figures that mean absolute percentage error is two percent which is minimum within the case of linear trend model, thus it's again concluded over that this methodology provides the foremost acceptable needed values and victimization this the anticipated forecast and forecast error are more closely falling to true values.
From the higher than facts and figures the MAPE values is minimum that corresponds to the linear trend model, thus this methodology provides us more the accumulation values and also the predications supported this methodology are with reference to true values.

CONCLUSIONS
Among the ways used for locating the forecast and forecast errors, the one and solely methodology recommended is linear trend model (Trend Analysis). This methodology is incredibly appropriate to predict the statistic values that are closely falling to true values.
it's apparently ascertained from the whole work wherever the horticulture spices, vegetables and fruits crop in India are thought-about increasing over a amount from 2001 -2018. More it's additionally detected that there exist even associate increasing spices, vegetable and fruits crop production for the anticipated years of 2019 to 2021.