Descriptive statistics, Regression analysis, Paired t-test, Covid-19.

Statistical investigation is a systematic process of collecting and analysing the data to study the trends and patterns. It helps industries, policy makers, and other authorities etc.., to make more accurate decisions. It helps to find the best performance and develop products by doing modelling of the ongoing situation and providing the future scenario.  The application of statistical approaches and methods is necessary for efficient practice in resolving the various problems that arise in many branches of agricultural industries.

The importance of horticulture in improving the productivity of land, generating employment, improving economic condition of the farmers and entrepreneurs, enhancing exports and above all providing nutritional security to the people. India is the second largest producer of fruits and vegetables in the world next only to China (NHB, 2011). The country's annual requirement is 74.40 MTs fruits and 175.2 MTs vegetables. With the present level of population, the annual requirement of fruits and vegetables will be of the order of more than production level.

According to the second advance estimate of horticulture production released by the Ministry of Agriculture, India is expected to have the highest ever horticulture production of 329.86 million tonnes in 2020-21, up by 2.93 per cent over previous year. The increase in production has been registered in vegetables, spices, medicinal and aromatic crops. The Floriculture sector has been the hardest hit by the pandemic as production declined by 7.17 per cent.

In India, the share of agriculture in GDP increased to 19.9 per cent, hitting 20 per cent after 17 years of which horticulture contributes 30.4 per cent to agriculture GDP (Anon., 2020). The increasing consciousness of nutrition of high valued commercial crops which comparatively witness low pathogenic distress as against the field crops, thus having wide ambit in booming processing industry. The total horticulture area and production in 2019-20 is 26.46 m ha and 320.77 MT respectively, an increase of about 9.72 MT (increase of 3.12%) over 2018-19 (Anon., 2021). Increase in production of fruits, vegetables, aromatic and medicinal plants and plantation crops, while decrease in production of spices and flowers over previous year, is envisaged.

Karnataka state has occupied 3rd place in respect of total area with 18.66 lakh hectares contributing to 8.60 per cent area to total area and 6th place in respect of total production with 177.98 lakh tons contributing 7.4 per cent production to total production at all India level. Karnataka state has occupied 3rd place regarding Fruit crops with area of  3.78 lakh hectares and production of 62.74 lakh tons and 8th place regarding Vegetable crops with 4.66 lakh hectares of area  and  90.56 lakh tons of production. The total geographical area of the Kolar district is 3,74,916 hectares, out of which, 2,13,543 is net cultivated area with an horticulture area of 1,11,453 hectares (29.73 % net cultivated area).

Due to the impact of COVID-19 on agriculture and horticulture crops  livestock/poultry Krishna district of Andhra Pradesh were 5 respondents (8.33%) decline   in   production   of   agriculture, decline   in   horticulture   and   35.00   declines   in production of livestock. In agriculture crops 25.00 per  cent  decline  in  farm  gate  prices  followed  by 86.66  per  cent  decline  in  horticulture  crops.  In marketing majority  76.66 per  cent of the farmers faced  lack  of  marketing  facilities  in  agriculture crops, followed by 95.00 per cent in marketing of horticulture  produce  and  53.33  per  cent  of  the farmers  faced  problems  marketing  of  livestock produce (Venkata et al., 2023). The impact of Covid-19 and the lockdown, the changes in the functioning of agricultural markets and assess the impact on prices and arrivals of commodities at wholesale markets. These impacts viewed as consequences of behavioural responses from consumers, wholesalers and retailers through to farmers. Farm incomes are by their very nature seasonal prices and quantities traded of commodities whose harvest times begin from late March are a key determinant of the liquidity of farmers and how their livelihoods are being affected by the pandemic, and also assess that state government had undertaken a greater degree of market reforms were better able to protect farmers from disruption.

However, most studies focus on national or state-level impacts, lacking district-specific analyses. This study addresses that gap by analyzing six-year trends (2016-2021) in market arrivals and prices of five key horticultural crops-tomato, chilli, cabbage, beans, and cucumber-in the Kolar APMC, Karnataka, before and during the COVID-19 pandemic.

Kolar district is located at 13.13°N 78.13°E with an average elevation of 849 metres (2,785 ft). It is located at a distance of about 70 kilometres from Bangalore, 50 kilometres from Bangalore International Airport, 147 kilometres from Hogenakkal waterfalls & 32 kilometres from Kolar Gold Fields. The district falls in the Eastern dry agro climatic Zone. It experiences a semi-arid climate, characterized by typical monsoon tropical weather with hot summers and mild winters. The year is normally divided into four seasons.

The secondary data were collected for the period Jan, 2016 to Dec, 2021 that includes marketing prices of horticultural crops on daily basis and also arrivals of six years of  horticultural crops i.e., from Jan, 2016 to Dec, 2021 on daily basis (Anon., 2022).

Descriptive statistics. This involved mean, standard deviation and variance which tells about the description of the procurement in particular year. Mean gives the idea of average amount of the milk procurement, standard deviation and the variance along with CV gives the homogeneity of the milk procurement in the DMS over the days of study period.

Regression: It is a functional relationship between the two variables in that one is dependent and another one is independent variable.

Simple linear regression model:

Y= α+ β X + ℇ

Where, Y- Dependent variable (prices)

X- Independent variable (arrivals)

α - Intercept.

β - Slope of Regression line.

ℇ - Random Error.

Paired t-test: The paired t-test gives a hypothesis examination of the difference between population means for a set of random samples whose variations are almost normally distributed. 

 Let us assume two paired sets, such as Xi and Yi for i = 1, 2, …, n such that their paired difference are independent which are identically and normally distributed.

Paired t-test statistic :

t =

To study the effect of covid-19 pandemic on market prices of crops

Descriptive statistics. The descriptive analysis including mean and coefficient of variance of each crops from year 2016 to 2021 is presented in Table 1, which includes mean value of both arrivals and prices of crops under study. The maximum arrivals was observed in 2021 year and from 2017 to 2021 arrivals shows increasing trend, same trend showed in all crops. While coming to prices, showed decreases in both 2020 and 2021 year compare to previous year from 2016-19. 

Table 1: Descriptive statistics of crops during study period.

    Note:  Arrivals expressed in quintals (Q) and Prices expressed in Rs/Q

Linear regression equation of trend of prices of crops. The linear regression equation of trend of prices of crops before Covid-19 period presented in Table 2. indicated that cabbage, beans and cucumber crops showed increasing trend while rest of all decreasing trend, that too only cucumber crop was significantly changing remaining all 4 crops was changing non-significantly.

The linear regression equation of trend of prices of crops during Covid-19 period presented in Table 3. that indicates all crops prices showed increasing trend during Covid-19 pandemic period but none of the crops was changing significantly.

The linear regression equation of arrivals and prices of crops during overall study period presented in Table 4. indicated that prices of all crops under study are decreasing with increases in arrivals unit that too changing significantly. 

Comparison of prices of crops during lockdown with past four years. The prices of crops from year 2020 and 2021 during lockdown period tested to check the mean difference from the year 2016 to 2019 with same study period, the result of paired t-test was presented in Table 5 and 6.

Supply chain disruptions during the COVID‑19 lockdown were widespread across India and globally. Tripathi et al. (2021) observed that vegetable direct-marketing systems in India temporarily collapsed due to mobility restrictions and labor shortages, severely impacting smallholder farmers. Similarly, Pakhuan and Choenkwan (2021) reported substantial disruptions in ginger production in Northeast Thailand, emphasizing the vulnerability of labor-dependent horticulture systems. On the agronomic front, Bishnoi et al. (2021) demonstrated that optimized row spacing significantly influenced the yield performance of cluster bean, suggesting scope for adaptive cultivation practices under pandemic conditions. Kumar et al. (2021) provided a multi-level assessment of how COVID-19 affected agricultural systems in Uttar Pradesh, noting constraints across supply, labor, and market access. Furthermore, Phad (2022) highlighted that the performance of Agricultural Produce Market Committees (APMCs) in the Marathwada region declined sharply, pointing to systemic weaknesses in wholesale market infrastructure during the pandemic.

The descriptive analysis including mean and coefficient of variance of each crops from year 2016 to 2021 is presented in Table 1. It was observed that during study period tomato crop showed maximum variation in both price and arrivals as compare to all other crops, followed by cabbage, cucumber, beans and chilli crop which showed minimum variation in both price and arrivals. During Covid-19 pandemic tomato price and cabbage price variation happened maximum but in beans and cucumber, price variation observed moderately and maintain more homogeneity in chilli price. This can be supported from the evidences given from the study carried out by Afrin et al. (2020) on dynamics of area change in vegetable production in karnataka.  Among the vegetables potato, and leafy vegetables recorded negative growth rate. Inequality between districts has also been observed for growth in area under vegetables. Tomato, gourds, cole crops and other vegetables group showed positive trend of area over the study period. However, onion and leafy vegetables would have more or less constant area over the projected period. 

Before Covid-19 pandemic there was a positive slope observed in cabbage, beans and cucumber prices that too in small range, In case of tomato and chilli prices shown decreasing slope. During Covid-19 pandemic the positive slope of linear regression trend line indicate the positive growth of vegetable price during the lockdown in year 2020-21. Similar study related to the impact of the Covid-19 pandemic on the prices of the three essential food items and perishable commodities in India conducted by Bairagi et al. (2022). The results revealed that price of basic food items increased significantly during the pandemic compared to the pre-pandemic period. In contrast, during the same period, the price of onions declined significantly. The findings may suggest panic-buying, hoarding, and storability of food items. The results further reveal that remittance income and cash transfers from the government negatively affected commodity prices.

The paired sample t-test was conducted to compare mean of prices of before Covid-19 (2016-2019) and during Covid-19 (2020-2021), the results of paired t-test was presented in the Table 5 and 6. During first Covid-19 pandemic year 2020, this study observed that the prices of tomato and cabbage showed significant difference between before (2016-19) and during Covid-19 (2020). The prices of chilli and beans also significantly differed during pandemic and before, except 2016. In case of cucumber price, It was observed that there was a significant difference in during pandemic and before (2016 & 2019) but non-significant with 2017 & 2018. During second Covid-19 pandemic year 2021, this study observed that the prices of tomato and chilli showed significant difference between before (2016-19) and during Covid-19 (2020), the prices of cabbage and beans also significantly differ during pandemic and before except 2016 (non-significant). In case of cucumber price, observed that there is a significant difference only in previous year 2019 but non-significant from 2016-2018.

Table 2: Linear regression fit equation of crops before Covid-19 period.

Table 3: Linear regression fit equation of crops during Covid-19 pandemic period.

Note: Y is dependent variable, price in Rs/Q;   X is independent variable, time in days;  R2 - Coefficient of determination; ns - Non-significant

Table 4: Overall Linear regression fit equation of crops during study period.

Note:- Y – Dependent variable, Prices; X – Independent variable, Arrivals 

* - Significant at 5 per cent;   ** - Significant at 1 per cent 

Adj.R2–Adjusted coefficient of determination ;  R2 - coefficient of determination

Table 5: Comparison of before COVID-19 pandemic with during COVID-19 (2020) pandemic.

Table 6: Comparison of before COVID-19 pandemic with during COVID-19 (2021) pandemic.

Note:    * - Significant at 5 per cent ;  ** - Significant at 1 per cent;   ns – Non significant

∙ The study helps to make the policy makers for understanding the nature if market supply chains.

∙ The investors, traders, retailers will get the idea of most sustainable agricultural/horticultural produce with context of pandemic, disaster like situation.

∙ Same kind of methodology can be done for the impact of pandemic, flood, drought and other natural disaster on other sectors like silk industry, commercial crops, processing industries etc.

∙ Addition to it, future trends of impact can also be calculated with various future projections tools like SARIMA, MLP-ANN, NNAR etc.