Price behaviour and market dynamics of onion in regulated markets of Haryana: A time series analysis

Introduction

Vegetables play a crucial role in human nutrition, providing essential vitamins, minerals, dietary fiber and antioxidants that are necessary for sustaining health and preventing chronic illnesses. Among the various vegetable crops, onion (Allium cepa L.) holds a significant place due to its widespread consumption, consistent year-round demand and its importance in household, culinary and processing applications. Onion is classified as a cool-to moderateseason bulb crop, appreciated for its pungency, flavour and extended storage capabilities. It is grown in a variety of agro-climatic conditions and thrives best in well-drained loamy soils with moderate temperatures. To achieve optimal bulb yield and quality, the crop necessitates timely irrigation, balanced fertilization and effective management of pests and diseases. India holds the position of the second-largest vegetable producer globally. Haryana has developed into a significant horticultural state, with onion farming being crucial for agricultural diversification and enhancing farmers' income. During the agricultural year 2022-23, the area under cultivation reached 24,158 hectares, resulting in a total output of 5,29,811 metric tons.

Onions are widely cultivated in the Nuh and Yamunanagar districts of Haryana, with significant market arrivals managed through locations such as Punhana, Taura, Jagadhari and Sadhuara. Although onions possess better storability compared to many other vegetables, they still encounter challenges stemming from insufficient storage and processing infrastructure. This inadequacy results in considerable seasonal variations in market arrivals. During peak harvest times, an excess of supply frequently leads to drastic price drops, whereas diminished availability in offseasons triggers price surges, thereby generating instability in both farmers' earnings and consumer prices. While the accessibility of market data via platforms like AGMARKNET has improved transparency concerning onion arrivals and pricing, issues such as post-harvest losses, inconsistent market arrivals and inadequate market integration continue to exist. Thus, it is crucial to analyze trends, growth and seasonal variations in onion arrivals and prices across the primary regulated markets in Haryana to comprehend market dynamics. In this regard, the current study aims to investigate oniones to evaluate the patterns of arrivals and prices and to determine their effects on enhancing market efficiency, price stability and income www.extensionjournal.com security for onion producers in Haryana. Keeping this in mind the objectives of the study are thus-1. To analyse the growth and trend in arrivals and price of onion in selected regulated markets in Haryana 2. To estimate the seasonal price behaviour of onion in the state 3. To develop the price forecast for onion

Materials and Methodology

The research utilized a blend of descriptive, statistical and econometric techniques to examine the trends, seasonality and pricing behaviour of onion in the state. The Nuh and Yamunanagar districts were selected due to their substantial area and production within the state, with the corresponding markets chosen for their higher arrivals: Punhana

Measurement of Seasonal Variations

Seasonal variations in market arrivals and prices were examined through the ratio-to-moving-average method (also known as the percentage of moving average method), which is regarded as more effective than alternative methods for calculating seasonal indices. This approach enabled the detection of both peak and lean periods. The seasonal index was calculated as:

Forecasting Using ARIMA Model To predict future prices and arrivals, the Auto Regressive Integrated Moving Average (ARIMA) model, commonly referred to as the Box-Jenkins method (Box and Jenkins, 1976), was utilized. Given that agricultural time-series data frequently display trends and non-stationarity, stationarity was assessed using autocorrelation functions (ACF). Nonstationary series were adjusted through differencing until stationarity was reached. An ARIMA (p, d, q) model incorporates autoregressive (p), differencing (d) and moving average (q) components and is expressed as:

• and are the actual value and random error at time period t, respectively

•

(i = 1, 2,….,p), θj (j = 1, 2,….,q) are model parameters.

• "p" and "q" are integers and often referred to as orders of the model.

Random errors terms are assumed to be independently and identically distributed with a mean of zero and a constant variance. The ARIMA model incorporates nonseasonal factors in a multiplicative model and is denoted as: ARIMA (p, d, q). Where, p = order of non-seasonal Auto Regressive (AR) d = order of non-seasonal difference q = order of non-seasonal

The selection of appropriate ARIMA models was based on the examination of ACF and PACF plots and automated model selection using the auto.arima() function in the forecast package of R, which applies the Hyndman-Khandakar algorithm.

Model Estimation and Diagnostic Checking

Model parameters were estimated using the least squares method. The adequacy of fitted models was evaluated through diagnostic tests, ensuring that residuals were www.extensionjournal.com random and free from autocorrelation. The following criteria were used for model validation:

Results and Discussion

Onion is a significant bulb crop that thrives in cool to moderate seasons in Haryana, cultivated during the kharif, late-kharif and rabi periods. The nursery is established in May-June, August-September and October-November, with transplanting occurring in July, October and December-January, respectively. The crop reaches maturity in 110-140 days and is harvested from October to May, thereby ensuring a continuous supply in the market throughout the year. Onions grow optimally in well-drained sandy loam soils, provided there is adequate irrigation and nutrient management 1. To analyse the growth and trend in arrivals and price of onion in selected regulated markets in Haryana Tables 1 and2 illustrate the Compound Annual Growth Rate (CAGR) of monthly onion arrivals and prices across four selected markets: Punhana, Tauru, Jagadhari and Sadhuara. In the Punhana market, arrivals displayed both positive and negative growth trends throughout the months. For instance, in (3.06% arrivals, 3.32% price) and February (-0.03% arrivals, 7.32% price), respectively. Likewise, in May (-1.43% arrivals, -1.09% price) and September (1.60% arrivals, -3.13% price), both arrivals and prices moved in the same direction. In the Tauru market, significant variability was noted in the growth trends of arrivals and prices. For instance, January (-6.07% arrivals, 7.03% price) and February (-1.29% arrivals, 8.17% price) demonstrated a clear negative correlation, while July (2.71% arrivals, 1.18% price) and August (11.66% arrivals, -0.98% price), respectively exhibited partial co-movement between arrivals and prices. In the Jagadhari market, arrivals consistently recorded high growth throughout the year; however, price movements did not follow a uniform inverse trend. For example, both arrivals and prices increased in January (13.95% arrivals, 8.35% price) and February (11.41% arrivals, 8.57% price), respectively. Even during peak arrival months such as May (23.57% arrivals, 1.57% price) and June (24.18% arrivals, -1.59% price), the growth in prices declined only slightly and not in proportion to the increase in arrivals. In contrast, the Sadhuara market demonstrated a more significant inverse correlation between the growth in arrivals and prices as in January (-3.96% arrivals, 5.14% price) and February (-0.55% arrivals, 7.82% price), as well as in August (4.79% arrivals, -2.43% price) and September (3.62% arrivals, -1.89% price) respectively. Nevertheless, certain anomalies were noted, such as in November (-9.31% arrivals, 5.35% price) and December (-6.08% arrivals, 4.98% price), where prices rose despite a decrease in arrivals. A seasonal analysis further underscores the variations across districts and markets. In the Nuh district, Punhana recorded modest post-harvest growth in arrivals (0.99%) alongside significant price increases (3.38%), followed by positive mid-season arrivals (4.86%) and slight price improvement (0.55%). During the lean period, arrivals remained slightly negative (-0.64%) while prices remained stable (0.61%). In contrast, Tauru reported relatively higher post-harvest arrivals (3.15%) with moderate price growth (1.46%), strong mid-season price increases (4.44%) even as arrivals declined slightly (-0.38%) and consistently negative lean-period arrivals (-2.86%) accompanied by substantial price gains (6.00%), reflecting seasonal supply constraints. In the Yamunanagar district, Jagadhari displayed robust and consistent growth in arrivals during the post-harvest (22.04%), mid-season (16.93%) and lean periods (13.43%). These trends were bolstered by positive price movements in the mid-season (1.79%) and lean months (6.60%), despite a slight decline during the post-harvest period (-1.24%). Conversely, Sadhuara experienced negative or marginal growth in arrivals across all three phases (-1.29%, -2.07% and -1.45%), while prices remained positive in most periods, recording 0.02 per cent in the post-harvest, 2.87 per cent in the mid-season and 3.92 per cent during the lean season. The overall Compound Annual Growth Rate (CAGR) reveals that total arrivals peaked in Jagadhari at 17.71 per cent, with moderate increases noted in Punhana at 1.69 per cent and Tauru at 1.00 per cent. Conversely, Sadhuara experienced a minor decrease of -2.29 per cent. In terms of pricing, there was a consistent upward trend across all markets, particularly in Tauru, which saw the most substantial growth at 4.17 per cent. These findings underscore notable spatial and seasonal fluctuations in the dynamics of the onion market throughout Haryana. The coefficients for arrivals were positive across all markets-Punhana, Jagadhari and Tauru (0.0024, 0.0464 and 0.005, respectively) with the exception of Sadhuara, which exhibited a negative coefficient (-0.0024). Price coefficients were also positive in all markets, specifically Punhana 4 and5, the seasonal indices for onion arrivals and prices across the four selected markets demonstrate distinct quarterly fluctuations. In the first quarter (January-March), arrivals showed a gradual increase in most markets, climbing from 0.81 to 1.02 in Punhana and from 0.80 to 1.19 in Tauru, while prices fell from 1.10 to 0.86 and from 1.15 to 0.84, respectively. A similar pattern was noted in Jagadhari, where arrivals rose from 0.90 to 1.05 and prices decreased from 1.29 to 0.86. In Sadhuara, a more pronounced increase in arrivals to 1.21 in March resulted in the lowest annual price index of 0.79. In the second quarter (April-June), arrivals remained relatively stable in Punhana and Tauru, fluctuating between 1.01 and 1.12, while prices hit their lowest points, with Punhana and Tauru recording indices of 0.63 and 0.59, respectively, in May. Jagadhari achieved its highest arrivals (1.40) in May, coinciding with its lowest price (0.59), whereas Sadhuara saw a peak in arrivals (1.76) with prices dropping to 0.56 respectively. The third quarter (July-September) exhibited a reversal in trends. In Punhana, arrivals increased slightly to 1.16 in September, while prices surged from 0.88 in July to 1.18 in September. Tauru recorded its peak arrivals (1.47) in August, with prices fluctuating between 1.00 and 1.17. Jagadhari experienced moderate arrivals with a consistent rise in prices, reaching 1.11 in September. Conversely, Sadhuara faced declining arrivals (0.70), which resulted in an increase in prices to 1.17. In the fourth quarter (October-December), arrivals contracted significantly, especially in Tauru (0.62 in December) and Sadhuara (remaining below 0.90 throughout the quarter). This reduction in supply led to peak prices in November, with Punhana, Tauru and Jagadhari recording indices of 1.39, 1.41 and 1.47, respectively. The observed seasonality illustrates the crop patterns across various markets. In Punhana, where onion is the primary crop, post-harvest arrivals averaged 0.94, with prices recorded at 0.82. During the mid-season, there was a slight increase in arrivals (0.95) alongside a rise in prices (1.25). In the lean period, arrivals further increased (1.11), while prices moderated to 0.94, indicating relatively stable market conditions. Conversely, in Tauru, which is characterized by rabi production, post-harvest arrivals were higher at 1.20, but prices were lower at 0.77. Mid-season arrivals saw a decline (0.80), accompanied by an increase in prices (1.32), reflecting the pressure of demand. Throughout the lean period, arrivals remained stable at 1.00, with moderate prices at 0.91, suggesting a balanced yet constrained supply situation.

To develop the price forecast for onion

The results of the Augmented Dickey-Fuller (ADF) test demonstrate that the price series at level were stationary at the 1 percent significance level across all chosen markets. In the Punhana market, the ADF statistic for level prices was -4.7197 (p = 0.01), which led to the rejection of the null hypothesis concerning the presence of a unit root. Likewise, the markets of Tauru (-4.711), Jagadhari (-5.4633) and Sadhuara (-4.8092) also displayed stationarity at levels, with p-values of 0.01. When examining first differences, the ADF statistics became increasingly negative (- The optimal ARIMA models varied across the markets. In Punhana, ARIMA (2,0,0) with a non-zero mean was identified as the most appropriate, indicating a second-order autoregressive process. Tauru was best characterized by ARIMA (1,0,1), while Jagadhari adhered to an ARIMA (1,0,0) specification. In Sadhuara, seasonal variations were significant and ARIMA (2,0,0)(2,0,0)[12] with a non-zero mean provided the best fit, underscoring the relevance of seasonal components in price behaviour. Forecasts for the timeframe spanning January 2024 to December 2025 in

Conclusion

The current study aims to conduct a comprehensive analysis of onion arrivals, prices, seasonal behaviour and forecasting performance in selected markets, including Punhana, Tauru, Jagadhari and Sadhuara, located in Haryana. From the analysis of Compound Annual Growth Rate and monthly trends, it has been identified that the classical inverse relationship between onion arrivals and prices has been observed to be prominent only in the Sadhuara market, followed to a moderate extent in Tauru. These markets are largely governed by traditional market forces of supply and demand, as lower arrivals result in higher prices and vice versa. However, markets like Punhana show irregular and moderate behaviour, indicating the impact of external sources of supply, including Faridabad and Delhi APMC. Jagadhari markets are largely divergent from conventional market behaviour, as prices tend to rise with increasing arrivals, indicating the dominance of demand factors, quality and strong regional market linkages, including Maharashtra and Rajasthan. Further, the results of the seasonal analysis also confirmed the cyclical behaviour in the onion marketing system. The arrival and prices tended to peak in the post-harvest and summer seasons (March-August), resulting in declining prices and the shortage in the autumn season (September-November) led to an increase in prices. The temporary synchronization in the arrival and prices in August in Punhana and Tauru could be because of the demand and storage constraints in these markets. The absence of major shortages in the markets in the lean period also highlighted the role of inter-state trade and improvements in connectivity. Further, the trend analysis, i.e., the regression models, also revealed that Jagadhari recorded the highest and most consistent growth in onion arrivals, reflecting the good infrastructure and stable supply base. Punhana and Tauru recorded marginal growth in onion arrivals, while Sadhuara recorded a decline in the trend, reflecting the irregularity in the arrival of onions in the markets. The results also indicated that the markets in Yamunanagar, i.e., Jagadhari and Sadhuara, performed better than the markets in Nuh, reflecting the better infrastructure and integration in the onion markets. The results from the stationarity tests established that the prices of onions in all the markets were stationary at level, implying that there were no long-term trends and that the prices did not adhere to the random walk hypothesis. The results further established the applicability of the ARIMA models in forecasting the prices. Among the models, Sadhuara recorded the highest accuracy in forecasting the prices compared to the others, considering that the model took into account the seasonal components, followed by Punhana. The model for Tauru recorded moderate forecasting efficiency, while Jagadhari recorded the lowest accuracy. Further, the results from the forecasting models from 2024 to 2025 indicated that there were different trends in the markets. Jagadhari recorded a consistent decline in the prices, implying that the demand for onions in the region was moderated, while Punhana and Tauru recorded stable prices, implying that the markets were stable. On the other hand, Sadhuara recorded fluctuations in the prices, implying that the onions arrived in the region in an unsteady manner. The accuracy of the forecasting models further supported the results, with Punhana having the highest accuracy (76.81%) followed by Tauru and Sadhuara ranging to 73 per cent, while Jagadhari was the most difficult to predict with lowest accuracy (68.99%). In conclusion, the study reveals that the onion price dynamics in the state of Haryana are influenced by a complex interplay of local production, inter-state trade, demand conditions, infrastructure and seasonal factors. While the Sadhuara and Tauru markets are more inclined to follow the classical supply-price relationships, the onion markets of Punhana and especially Jagadhari are more influenced by external and demand factors. The high volatility and fluctuating performance of the onion markets underscore the susceptibility of the onion markets to supply shocks. Therefore, it is imperative that the existing storage infrastructure is strengthened, the cold chain is developed further, the market intelligence systems are improved and the inter-market coordination is strengthened to stabilize the onion prices. Moreover, efforts to promote staggered sowing, post-harvest management strategies and the integration of the onion markets with national markets can also help to reduce the extreme volatility of the onion prices.

References

1. Amarnath JS, Velmurugan S, Prabakaran K. Marketing and price forecasting of aggregatum onion in Tamil Nadu, India. International Journal of Farm Sciences. 2017;7(1):116-122.
2. Amir MW, Amin M, Nazir HZ. Statistical modelling and forecasting for onion production of Pakistan. Journal of Agriculture Research. 2021;59(2):171-176.
3. Beniwal A, Poolsingh D, Shastry SS. Trends and price behaviour analysis of onion in India. Indian Journal of Agricultural Economics. 2022;77(4):632-642.
4. Darekar AS, Pokharkar VG, Yadav DB. Onion price forecasting in Yeola market of Western Maharashtra using ARIMA technique. International Journal of Advanced Biological Research. 2016;6(4):551-552.
5. Darekar AS, Pokharkar VG, Gavali AV, Yadav DB. Forecasting the price of onion in Lasalgaon and Pimpalgaon market of Western Maharashtra. International Journal of Tropical Agriculture. 2015;33(4):3563-3568.
6. Parmar HB, Bhopala UD, Dhandhalya MG. Analyzing the seasonal variations and price trends in major onion markets of India. Asian Journal of Agricultural Extension, Economics and Sociology. 2024;42(1):2433.
7. Selvi CT, Naidu GM, Murthy BR, Rajeshwari S. Trend and seasonal variation in arrivals and price of onion in major markets of Tamil Nadu. Andhra Pradesh Journal of Agricultural Sciences. 2020;6(2):92-100.
8. Shelke RD, Chavan RV, Bhogaonkar MM. Studying the trends in arrivals and price of onion in Ahmednagar market of Maharashtra. International Journal of Commerce and Business Management. 2016;9(1):4952.
9. Shukla DN, Rai J. An economic study of behaviour of market arrivals and price of onion, garlic and turmeric in selected markets of Uttar Pradesh. International Research Journal of Agricultural Economics and Statistics. 2014;5(2):235-240.