Growth trends and sustainability yield index of potato in Madhya Pradesh

Introduction

Potato (Solanum tuberosum ssp. tuberosum) is an outcrossing crop with a chromosome number of 2n = 48. It is a highly branched, herbaceous annual plant, growing to a height of 0.5-1 meter, with underground modified stems (tubers) used as food. It has a leaf structure of odd-pinnate leaves with a terminal leaflet and bears flowers in cymose panicles. Even though potato is extensively grown in India now, it is not native to the subcontinent. Potato is a native to the Andean region of South America, especially the regions near present-day Bolivia and Peru, and was domesticated almost 8,000 years ago. It was brought to India by Portuguese traders in the late 16th century via the southern coast. Potato is one of the major vegetable crops because of its high yield, short growing period and suitability to various agro-climatic zones. It has a great advantage of being a vegetative propagated crop through seed tubers, which enables farmers to retain varietal purity and low production costs. Moreover, potato is a good source of food energy per unit area and time, and an integral part of the Indian diet. Given its high productivity and nutritive value, potato is not considered just a vegetable but a food crop, which plays a crucial role in food and nutritional security and income generation for farmers (Hussain, 2016) [5] . The ideal temperature for crop growth and development is 16-25 °C, with temperatures near 40 °C being detrimental. Optimal temperature for sprout emergence is around 22-24 °C; emergence is delayed with lower temperatures (less than 20 °C). Cooler night temperatures are needed for tuber initiation (12-18 °C is optimal) (Singh et al., 2022) [7] . It's typically grown 5-12 cm deep with an intra-row spacing of 15-40 cm and a row spacing of about 75 cm (Bussan et al., 2007; Laznik et al., 2010; Cunha et al., 2011). Potato is a relatively high nutrient requiring crop, accounting for almost 30% of the total cost of production (Pishgar Komleh et al., 2012; Zangeneh et al., 2010; Silva et al.) [11,13] . Potatoes are responsive to fertilizers (Levshin et al., 2020) [9] , and farmers frequently use large quantities of chemical fertilizers and pesticides, often more than recommended, which can have detrimental impacts on the environment (Zhong et al., 2018) [10] . Nutrient removal studies suggest that the production of one tonne of potato crop removes around 3.8 kg N, 0.6 kg P and 4.4 kg K (Alva et al., 2011) [1] . Potato is susceptible to many diseases, such as early and late blight, black spot, soft rot, brown rot, leaf roll virus, and potato virus Y (Kapsa, 2008) [6] . The principal pests are aphids, whiteflies, leafhoppers, white grubs, thrips, cutworms, mites and potato tuber moth (Venkateswarlu et al., 2018) [12] . Uttar Pradesh was the largest producer of potatoes in India during 2022 with a production of 20,126 thousand metric tonnes, followed by West Bengal (14,508 thousand metric tonnes), Bihar (9,075 thousand metric tonnes), Gujarat (4,025.7 thousand metric tonnes), and Madhya Pradesh (3,954.91 thousand metric tonnes).

Methodology

The collected information was clearly secondary. The information on the area, production, and potato yield for 1960-2022 were collected from Agriculture Statistics at a Glance.

Descriptive statistics

Descriptive statistics are used to present numerical data logically and intelligibly. In a research study, we may employ a range of metrics or only one to evaluate a significant number of people. Descriptive statistics help us make sense of massive amounts of data. Each descriptive statistic distils a significant quantity of information into a brief description. Descriptive statistics are classified into three types: measures of central tendency (CT), measures of dispersion, and measures of association ship. Because of their obvious advantages over a number of other measures, the arithmetic mean, standard deviation/error, skewness, kurtosis correlation, regression, and other metrics are often used to characterise the given data. Descriptive statistics provide simple summaries of the data and metrics. The series is anticipated for the coming years based on descriptive statistics in order to take suitable measures. Maximum, minimum, mean, median, skewness, kurtosis, and other descriptive statistics studies were utilised to explain the pattern of the series and establish a consensus under consideration.

Mean

Arithmetic mean or simple mean of a set of observation is their sum divided by the number of observation, e.g. the arithmetic mean x of n observation x1, x 2 , x 3 …….,x n is given by In case of grouped data

where x i 's are the mid values of the classes and f i 's are the respective frequencies. Among the three means viz. arithmetic mean (AM), geometric mean (GM) and harmonic mean (HM), AM is most widely used for its simplicity in calculation and explanation.

Standard deviation

It is more accurate and detailed estimate of dispersion because an outlier can greatly exaggerate the range. It is expressed by

Where, x i = value of the variable for the i th observation x = the mean or average N = the number of values

Standard Error

The standard error, abbreviated as S.E., is the standard deviation of a statistic's sampling distribution. The size of the standard error indicates the precision with which the parameter estimate was made. The formula for the standard error of the mean is,

Skewness

Skewness is defined as a lack of symmetry. We investigate skewness to get a sense of the form of the curve we can draw with the data we have. The coefficient of skewness is calculated based on moments.

Trend

A trend model could be described as a technique to depict how a process or a system acts as time goes by. Generally, Statistical models track a process and describe its statistical characteristics and outcomes. The objective is to use several trend models, which can be summed up as follows, to analyse the direction, pattern, and nature of the time series under consideration. (kumar et al., 2022) [7] .

Trend Model

Discerption Formula Linear Model

The equation of Linear model is given by Yt= b0+ (b1t) Quadratic Model

The equation of Quadratic Model is given by Yt= b0+ (b1t) + (b2t 2 ) Compound Model

The equation of compound model is given by Yt= b0 (b t ) or ln (Yt) = ln (b0) + t ln (b1) Cubic Model

The equation of cubic model is given by Yt= b0 + (b1t)+ (b2t 2 ) +(b3t 3 ) Exponential Model

The equation of exponential model is given by Yt= b0 e (b1t) or, ln(Yt) = ln (b0) + (b1t) Logarithmic Model

The equation of logarithmic model is given by Yt= b0+ b1ln (t) Growth Model

The equation of growth model is given by In (Yt) = b0+b1t Where Yt is the value of the series at time t and b0, b1, b2, and b3 are the parameters.

Sustainability Yield Index

Sustainability is generally accepted as a complex and multifaceted concept, which is interpreted differently among various disciplines, it encompasses the interaction of biophysical, social and economic factors, and is therefore difficult to assess and quite subjective. Sustainability broadly relates to the ability of a system to function and produce over time without negatively impacting resources and the environment. For agricultural systems, such as potato, sustainability is intricately tied to the concept of continuous production and food and nutritional security. A sustainable crop system is one that is stable, robust and productive in the long run, under different environmental and socio-economic conditions. Thus, the ability to sustain yields over time is used as a measure of sustainability of a production system. While a plethora of indicators and approaches have been suggested by researchers to assess sustainability, there is no simple measure of sustainability. Rather, multiple parameters are employed to gain insight into the sustainability of agricultural systems Devi et al. (2021) [4] . Sustainability Index (SI) the potato productivity data will be split into two periods for the sustainability index. Here, 𝑌𝑌 � is the mean yield of a treatment, S is the standard deviation of the yield and Y max is the highest yield of a treatment in a year. A high index value indicates high stability and consistency and thus sustainability.

Result 3.1 Performance of Potato in Madhya Pradesh

Trend analysis of potato in Madhya Pradesh

The overall performance path of the series movement was traced to parametric trend using a parametric trend model. To determine the trend in area production and yield of different states used various parametric model such as linear, exponential, logarithmic, quadratic, cubic and compound model. The best model is chosen from among the competing models based on its largest R 2 value, model significance, and coefficients. The results of these exercises are presented in the following section. and the overall period (1960 to 2022). The result of SI 1 was clearly indicated SI 1 values decreased from 0.594 in period 1to 0.523 period 2, reflecting enhanced yield stability and higher sustainability in later period (period2).

However, the lower value observed for the overall period (0.403) suggested that long term fluctuations adversely affected overall suggested despite recent improvement. In case of SI 2 a decline in values from 0.436 in period 1 to 0.382 period 2, was observed, indicating reduced variability and improved stability, as lower SI 2 values signify higher sustainability. However, the overall period recorded a higher value (0.669), implying greater variability when the entire duration was considered.

Similarly, SI 3 values increased from 0.0317 in period 1 to 0.059 period 2 and overall period 0.071. As lower SI 3 values represent better sustainability, the increasing trend suggests a gradual deterioration in yield stability over time Overall, the results demonstrated that potato yield sustainability in Madhya Pradesh improved significantly during the first period (1991-2022) compered the second period.

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