010 Big Data sets the tone for Agriculture Transformation! Check How?
Can you tell what is the most important thing for the survival of millions of people in this world?
你能告诉我，对于这个世界上数百万人的生存来说，什么是最重要的？
“The world doesn’t need any more engineers. We don’t run out of airplanes, television sets or mobile phones…we ran out of food.”
“世界不再需要工程师了.我们的飞机、电视机和手机都用完了，我们的食物也用完了.”
In the world full of nearly 7.5 billion people to feed themselves, more focus is given to the technology and growth of the economy.
在这个充满了近75亿人为了养活自己，人们更加关注技术和经济增长.
Big Data is helping and transforming multiple numbers of industries and changing the sectors with remarkable development.
大数据正在帮助和改变多个行业，并以显著的发展改变行业.
About 100 years ago, industrialization began but the digitalization in industries is witnessed in this age. Digitalization has improved the face of agriculture and farming.
大约 100 年前，工业化开始了，但是在这个时代，工业的数字化被见证了.数字化改善了农业和农业的面貌.
Also, the introduction of drone technology and robotics has modified the agriculture sector.
此外，无人机技术和机器人技术的引入改变了农业部门.
***Before moving on I recommend you to revise your Big Data Concepts. ***
***在继续之前，我建议你修改你的大数据概念. ***
Big data in agriculture
Why Agriculture needs Big Data?
农业为什么需要大数据？
Researchers have estimated that by 2050, the world’s population will reach 10 billion. This clearly means that food consumption will be double to fulfill the need for such a big number of population. Almost 40% of earth’s surface is already in use for agriculture and surprisingly a huge amount of production goes in the waste throughout the process. Therefore, Big Data is brought into the picture.
研究人员估计，到 2050年，世界人口将达到 100亿.这显然意味着，为了满足如此庞大的人口需求，食品消费将增加一倍.几乎 40% 的地球表面已经被用于农业，令人惊讶的是，在整个过程中，大量的生产都被浪费了.因此，大数据被带入了这个画面.
Big Data provides a helping hand for every problem and complexities in agriculture. It plays a key role in establishing an advanced and smart agricultural system. Farmers around the world may often get confused in decision making regarding the type of crop to be harvested. With the help of Big Data analytics, predictions are drawn from the previous year’s climatic conditions, the nutrients of the soil, rainfall, etc. These wise decisions with Big Data help to yield maximum production and help to grow the economic sector for the production of food.
大数据为农业的每一个问题和复杂性提供了帮助.它对建立先进、智慧的农业体系起着关键作用.世界各地的农民可能经常对将要收获的作物类型的决策感到困惑.在大数据分析的帮助下，从前一年的气候条件、土壤养分、降雨量等方面进行预测.这些利用大数据做出的明智决策有助于最大限度地提高产量，并有助于发展粮食生产的经济部门.
Do you want to make effective and efficient use of Big Data in your business and take it to the great heights?
Get expertise training for Big Data
你想在你的业务中有效和高效地利用大数据，并将其推向高峰吗？
获得大数据专业知识培训
Big Data in Agriculture
农业大数据
According to DataFlair, these are the ways in which Big Data is helping the Agriculture sector.
根据 DataFlair 的说法，这些是大数据帮助农业部门的方式.
1. Monitoring Natural Trends
1. 监测自然灾害趋势
Before Big Data existed, it was impossible to predict the significant risk factors like pest and crop diseases, and natural disasters like storms or extreme weather which can decimate entire harvests. Yes, experienced farmers can spot the signs of these factors but it’s often too very late. By feeding past and present data into a system and extracting insights through Data Science and valid algorithms can effectively boost future yields. This saves farmers from a lot of loss.
在大数据出现之前，无法预测害虫和作物疾病等重大风险因素，也无法预测风暴或极端天气等自然灾害，这些因素可能会毁掉整个收成.是的，有经验的农民可以发现这些因素的迹象，但通常为时已晚.通过将过去和现在的数据输入到一个系统中，并通过数据科学和有效的算法提取见解，可以有效地提高未来的产量.这为农民节省了很多损失.
2. Accurate Crop Prediction
2. 准确产量预测
Sowing the seed and waiting for a plant to grow and see how the crop will yield is a long process. In recent years, Big Data as an accurate prediction provides help by predicting crop yields accurately without even planting a seed. An accurate algorithm is used to analyze the weather conditions and datasets of the crop from the last few years and predicts the best crop this year.
播种，等待植物生长，看看作物的产量是一个漫长的过程.近年来，大数据作为一种精确的预测，即使不播种，也能准确地预测作物产量，从而提供帮助.使用精确的算法分析过去几年的天气状况和作物数据集，并预测今年的最佳作物.
3. Agricultural Automation
3. 农业自动化
Due to advancements in technology and big data, automated tools like farm bots, sprinklers, solar water pumps, and drips came into existence. Drones are to be fitted with advanced sensors to update their data, monitor crops, notifying the area needed for improvement. Robots are used in many parts of the world for planting kernels of corn and picking up the weeds which spoil the main crop.
由于技术和大数据的进步，农场机器人、洒水器、太阳能水泵和滴水等自动化工具应运而生.无人机将配备先进的传感器来更新数据、监测作物、通知需要改进的区域.世界上许多地方都使用机器人来种植玉米粒和采摘破坏主要作物的杂草.
4. Data-Driven Industry
4. 数据驱动的行业
The other good side of Big Data is that it is connected with external platforms for a considerable amount of data and insights. Farmers can use predictive analytic techniques to plan for and act as per the weather patterns, consumer demands, and trends. This data will help them to understand how the surrounding world affects the agriculture industry. What should they plant? What is the best time? Are the prices of supplies rising? and how does this affect profits? All these generate a need to create a data-driven industry that operates in new and innovative ways to make room for data-driven solutions.
的另一面大数据它与外部平台连接，获取大量数据和见解.农民可以使用预测分析技术，根据天气模式、消费者需求和趋势进行规划和行动.这些数据将有助于他们了解周围世界对农业的影响.他们应该种什么？最佳时间是什么时候？供应价格上涨了吗？这对利润有什么影响？所有这些都需要创建一个数据驱动的行业，以新的创新方式运营，为数据驱动的解决方案腾出空间.
5. Risk Assessment
5..风险评估
In general business, management and planning teams often carry out a detailed risk assessment. But until now it is not practiced in the agriculture sector. With Big Data nearly every system, decision or event can be considered in the risk analysis plan. Every problem can be accounted for not just an appropriate solution but with the expected results. It makes sure that taking these actions won’t destroy the crop. Most importantly, they can use real-time data to ensure damage remains minimal.
在一般的业务中，管理和计划团队往往会进行详细的风险评估.但是到目前为止，农业部门还没有这样做.几乎每个系统都有大数据，在风险分析计划中可以考虑决策或事件.每一个问题都可以被解释为不仅仅是一个合适的解决方案，还有预期的结果.它确保采取这些行动不会破坏作物.最重要的是，他们可以使用实时数据来确保损失最小.
***Have you checked how the income tax department is using Big Data ***
***你检查过了吗所得税部门利用大数据 ***
Conclusion
结论
The scope of Big Data is now pushing in the agriculture sector. Big Data analytics and machine learning play a huge role in predicting various complexities involved in the production process. Big Data will eventually grow in the future and bring more advancement and automation in farming.
大数据的范围正在农业领域推动.大数据分析和机器学习在预测生产过程中涉及的各种复杂性方面发挥着巨大的作用.大数据最终将在未来发展，带来更多的农业进步和自动化.
“The adoption of Big Data in agriculture is the best way for smart farming” – DataFlair.
“在农业中采用大数据是智慧农业的最佳方式”-数据仓库.
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