Recently, there have been reports of price crashes and distress sales in case of farm produce, such as tomatoes, mangoes, and garlic. In some cases, farmers have dumped their produce on roads. Produce such as fruits and vegetables are perishable and therefore have a short shelf life. Further, due to inadequate storage facilities and poor food processing infrastructure farmers have limited options but to sell the produce at prevailing market prices. This can lead to distress sales or roadside discards (in some cases to avoid additional cost of transportation).
Food processing allows raw food to be stored, marketed, or preserved for consumption later. For instance, raw agricultural produce such as fruits may be processed into juices, jams, and pickles. Activities such as waxing (for preservation), packaging, labelling, or ripening of produce also form part of the food processing industry.
Between 2001-02 and 2016-17, production of food grains grew annually at 1.7% on average. Production of horticulture crops surpassed food grains with an average growth rate of 4.8%. While production has been increasing over the years, surplus produce tends to go waste at various stages such as procurement, storage, and processing due to lack of infrastructure such as cold storages and food processing units.
Source: Horticulture Statistics at a Glance 2017, Union Budget 2018-19; PRS.
Losses high among perishables such as fruits and vegetables
Crop losses ranged between 7-16% among fruits and around 5% among cereals in 2015. The highest losses were witnessed in case of guava, followed by mango, which are perishable fruits. Perishables such as fruits and vegetables are more prone to losses as compared to cereals. Such crop losses can occur during operations such as harvesting, thrashing, grading, drying, packaging, transportation, and storage depending upon the commodity.
It was estimated that the annual value of harvest and post-harvest losses of major agricultural products at the national level was Rs 92,651 crore in 2015. The Standing Committee on Agriculture (2017) stated that such wastage can be reduced with adequate food processing facilities.
Sources: Annual Report 2016-17, Ministry of Food Processing Industries; PRS.
Inadequate food processing infrastructure
As previously discussed, perishables such as fruits and vegetables are more prone to damages as compared to cereals. Due to inadequate processing facilities in close proximity, farmers may be unable to hold their produce for a long time. Hence, they may be forced to sell their produce soon after harvest, irrespective of the prevailing market situations. Expert committees have recommended that agri-logistics such as cold chain infrastructure and market linkages should be strengthened.
Cold chain infrastructure: Cold chain infrastructure includes processing units, cold storages, and refrigerated vans. As of 2014, out of a required cold storage capacity of 35 million metric tonnes (MT), almost 90% (31.8 million MT) of the capacity was available (see Table 1). However, cold storage needs to be coupled with logistical support to facilitate smooth transfer of harvested value from farms to distant locations. This includes: (i) pack-houses for packaging and preparing fresh produce for long distance transport, (ii) refrigerated transport such as reefer vehicles, and (iii) ripening chambers to ripen raw produce before marketing. For instance, bananas which are harvested raw may be ripened in these chambers before being marketed.
While there are sufficient cold storages, there are wide gaps in the availability of other associated infrastructure. This implies that even though almost 90% (32 million tonnes) of cold storage capacity is available, only 15% of the required refrigerated transport exists. Further, the shortfall in the availability of infrastructure necessary for safe handling of farm produce, like pack-houses and ripening chambers, is over 90%.
Table 1: Gaps in cold chain infrastructure (2014)
| Facility | Required | Available | Gap | % gap |
| Cold storage (in million MT) |
35.1 |
31.8 | 3.2 |
9.3% |
| Pack-houses |
70,080 |
249 | 69,831 |
99.6% |
| Reefer vehicles |
61,826 |
9,000 | 52,826 |
85.4% |
| Ripening chambers |
9,131 |
812 | 8,319 |
91.1% |
To minimise post-harvest losses, the Standing Committee (2017) recommended that a country-wide integrated cold chain infrastructure network at block and district levels should be created. It further recommended that a Cold Chain Coordination and Monitoring Committee should be constituted at the district-level. The Standing Committee also recommended that farmers need to be trained in value addition activities such as sorting, grading, and pre-cooling harvested produce through facilities such as freezers and ripening chambers.
Between 2008 and 2017, 238 cold chain projects were sanctioned under the Scheme for Integrated Cold Chain and Value Addition Infrastructure. Grants worth Rs 1,775 crore were approved for these projects. Of this amount, Rs 964 crore (54%) has been released as of January 2018. Consequently, out of the total projects sanctioned, 114 (48%) are completed. The remaining 124 projects are currently under implementation.
Transport Facilities: Currently, majority of food grains and certain quantities of tea, potato, and onion are transported through railways. The Committee on Doubling Farmers Income had recommended that railways needs to upgrade its logistics to facilitate the transport of fresh produce directly to export hubs. This includes creation of adjoining facilities for loading and unloading, and distribution to road transport.
Mega Food Parks: The Mega Food Parks scheme was launched in 2008. It seeks to facilitate setting up of food processing units. These units are to be located at a central processing centre with infrastructure required for processing, packaging, quality control labs, and trade facilitation centres.
As of March 2018, out of the 42 projects approved, 10 were operational. The Standing Committee on Agriculture noted certain reasons for delay in implementation of projects under the scheme. These include: (i) difficulty in getting loans from banks for the project, (ii) delay in obtaining clearances from the state governments and agencies for roads, power, and water at the project site, (iii) lack of special incentives for setting up food processing units in Mega Food Parks, and (iv) unwillingness of the co-promoters in contributing their share of equity.
Further, the Standing Committee stated that as the scheme requires a minimum area of 50 acres, it does not to promote smaller or individual food processing and preservation units. It recommended that smaller agro-processing clusters near production areas must be promoted. The Committee on Doubling Farmers Income recommended establishment of processing and value addition units at strategic places. This includes rural or production areas for pulses, millets, fruits, vegetables, dairy, fisheries, and poultry in public private-partnership mode.
Recently, the Supreme Court collegium reiterated its recommendations for the appointment of 11 judges to certain High Courts. It had first recommended these names earlier this year and in August last year, but these appointments were not made. The Indian judiciary faces high vacancies across all levels (the Supreme Court, High Courts, and subordinate courts). Vacancy of judges in courts is one of the reasons for delays and a rising number of pending cases, as there are not enough judges to hear and decide cases. As of today, more than four crore cases are pending across all courts in India. In this blog post, we discuss vacancies across courts over the years, delays in appointment of judges, and methods to determine the adequate judge strength required to handle the caseload courts face.
High vacancy of judges across courts
Vacancies in courts keep on arising periodically due to retirement, resignation, demise, or elevation of judges. Over the years, the sanctioned strength of judges in both High Courts and subordinate courts has been increased gradually. However, vacancies persist due to insufficient appointments (see Figures 1 and 2). Between 2010 and 2020, vacancies increased from 18% to 21% across all levels of courts (from 6% to 12% in the Supreme Court, from 33% to 38% in High Courts, and from 18% to 20% in subordinate courts).
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Figure 1: Vacancy of judges in High Courts |
Figure 2: Vacancy of judges in subordinate courts |
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Sources: Court News 2010-2018; Vacancy Statement, and Rajya Sabha replies, Part I, Budget Session (2021), Department of Justice; PRS. |
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As on November 1, 2021, the Supreme Court had a vacancy of one judge (out of a sanctioned strength of 34). Vacancy in High Courts stood at 37% (406 posts vacant out of a sanctioned strength of 1,098). Since May, 2021, the Supreme Court collegium has recommended more than 130 names for appointment as High Court judges. In three High Courts (Telangana, Patna, and Calcutta), at least half of the posts are vacant (see Figure 3). The Standing Committee on Personnel, Public Grievances, Law and Justice (2020) noted that every year, 35-40% of posts of High Court judges remain unfilled.
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Figure 3: Vacancy of judges across High Courts (in %) (as on November 1, 2021)
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Source: Vacancy Statement, Department of Justice; PRS. |
Appointments of High Court judges are guided by a memorandum of procedure. As per this memorandum, the appointment process is to be initiated by the concerned High Court at least six months before a vacancy occurs. However, the Standing Committee (2021) noted that this timeline is rarely adhered to by High Courts. Further, in the final stage of the process, after receiving recommendations from the Supreme Court collegium, the executive appoints judges to the High Court. No timeline is prescribed for this stage of the appointment process. In 2018 and 2019, the average time taken to appoint High Court judges after receiving the collegium’s recommendations was five to seven months.
As of today, over 3.6 crore cases are pending before subordinate courts in India. As on February 20, 2020, 21% posts for judges were vacant (5,146 posts out of the sanctioned strength of 24,018) in subordinate courts. Subordinate courts in Bihar, Haryana, and Jharkhand (among the states with high population) had a high proportion of vacancies of judges (see Figure 4). Note that the Supreme Court is monitoring the procedure for appointment of judges to subordinate courts.
For an analysis of the data on pendency and vacancies in the Indian judiciary, see here.
Figure 4: Vacancy of judges across subordinate courts (in %) (as on February 20, 2020)
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Source: Report No. 101, Standing Committee on Personnel, Public Grievances, Law and Justice (2020); PRS. |
How many judges do we need?
The Law Commission of India (1987) had noted the importance of manpower planning for the judiciary. Lack of adequate number of judges means a greater workload per judge. Thus, it becomes essential to arrive at an optimal judge strength to deal with pending and new cases in courts. Over the years, different methods of calculating the required judge strength for subordinate courts (where the backlog of cases in the Indian judiciary is concentrated) have been recommended (see Table 1).
Table 1: Methods recommended for calculating the required number of judges for subordinate courts
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Method of calculation |
Recommendation and its status |
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Judge-to-population ratio: optimum number of judges per million population |
The Law Commission of India (1987) had recommended increasing this ratio to 50 judges per million people. This was reiterated by the Supreme Court (2001) and the Standing Committee on Home Affairs (2002). For 2020, the judge-to-population ratio was 21 judges per million population. Note that this figure is calculated based on the sanctioned strength of judges in the Supreme Court, High Courts and subordinate courts. |
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Rate of disposal: number of additional judges required (to clear the existing backlog of cases and ensure that new backlog is not created) based on the average number of cases disposed per judge |
The Law Commission of India (2014) proposed this method. It rejected the judge-to-population ratio method, observing that filing of cases per capita varies substantially across geographic units depending on socio-economic conditions. |
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Weighted case load method: calculating judge strength based on the disposal by judges, taking into account the nature and complexity of cases in local conditions |
The National Court Management Systems Committee (NCMS) (2016) critiqued the rate of disposal method. It proposed, as an interim measure, the weighted case load method, which addresses the existing backlog of cases as well as the new flow of cases every year in subordinate courts. In 2017, the Supreme Court accepted this model. |
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Time-based weighted case load method: calculating the required judge strength taking into account the actual time spent by judges in different types of cases at varying stages based on an empirical study |
Used widely in the United States, this was the long-term method recommended by the NCMS (2016) to assess the required judge strength for subordinate courts. It involves determining the total number of ‘judicial hours’ required for disposing of the case load of each court. The Delhi High Court used this approach in a pilot project (January 2017- December 2018) to calculate the ideal judge strength for disposing of pending cases in certain courts in Delhi. |
Sources: Reports No. 120 (1987) and 245 (2014), Law Commission of India; Report No. 85, Standing Committee on Home Affairs (2002); Note for Calculating Required Judge Strength for Subordinate Courts, National Court Management Systems Committee (NCMS) (2016); Imtiyaz Ahmad vs. State of Uttar Pradesh, Supreme Court (2017); PRS.
