Previous Year Questions

Question :

Directions [Set of 10 Questions]: Read the passage carefully and answer the questions that follow.

Over centuries, the growth of agriculture contributed to the rise of civilizations. About 11,500 years ago, people gradually learned how to grow cereal and root crops, and settled down to a life based on farming. Agriculture enabled people to produce surplus food. They could use this extra food when crops failed or trade it for other goods. Food surpluses allowed people to work at other tasks unrelated to farming. Agriculture kept formerly nomadic people near their fields and led to the development of permanent villages. These became accessible through trade. New economies were so successful in some areas that cities grew and civilizations developed. Food production must keep pace with population growth and distribution methods. This is an enormous agricultural and political challenge. The challenge is not food shortages but unequal distribution of the world's food supply. The ratio of population to farmable land has favoured some countries more than others. Some experts believe countries' government policies have hindered equal food distribution. Droughts, floods, and other disasters continue to cause local food shortages. Exporting food or agricultural technology from countries with surpluses to those with shortages will not solve the problem of world hunger. Beginning in the 1970s, scientists found that they could rearrange genes and add new ones to promote disease resistance, productivity, and other desired characteristics in crops and livestock.

Agriculture has traditionally been impacted by a lack of credible and timely data such as area under production, yield, crop and soil health, and commodity prices. This has caused demand-supply imbalance, volatility in the market prices of commodities and suboptimal or excessive use of natural resources. The only way we can address the pressing issues by solving these challenges at scale is by capturing and synthesising data for enabling decision making for farmers, agri input/output/processing companies and other value chain players such as banks and insurance companies. Fortunately, we have access to a wide range of digital technologies developed in the last four - five years by multiple AgriTech start-ups. These technologies help track multiple data points along the value chain from pre harvest, including input application, area under production, farm boundaries, farmer profile, soil health, hyperlocal weather and crop health, to post harvest, including quality, grades, traceability and losses, all the way to retail and export markets. The data is captured through a combination of multiple devices, including sensors, IoT devices, smartphones, spectrometers, drones and satellite images. Machine learning (ML) and AI technologies are needed to build data-centric models which can predict any weather event, pest attack, harvest and crop yield with more accuracy. Many AI models also provide immediate, low-cost, affordable, portable and accurate solutions for the measurement of soil moisture, nutrition, crop health, quality assessment, etc. One of the biggest challenges in scaling AI models is access to good-quality data.

Which of the following is the result of lack of reliable data like crop and soil health, and price of commodities?