IELTS Reading: Sự Phát Triển Của Nông Nghiệp Thông Minh – Đề Thi Mẫu Có Đáp Án Chi Tiết

Mở Bài

Nông nghiệp thông minh (Smart Agriculture) đang trở thành một trong những chủ đề nóng hổi nhất trong các kỳ thi IELTS Reading hiện nay. Với sự phát triển vượt bậc của công nghệ và nhu cầu cấp thiết về an ninh lương thực toàn cầu, chủ đề “The Rise Of Smart Agriculture In Food Production” xuất hiện ngày càng thường xuyên trong các đề thi thực tế, đặc biệt từ năm 2020 trở lại đây.

Bài viết này cung cấp cho bạn một bộ đề thi IELTS Reading hoàn chỉnh với 3 passages theo đúng chuẩn Cambridge IELTS, bao gồm 40 câu hỏi đa dạng về dạng bài và mức độ khó. Bạn sẽ được luyện tập với các dạng câu hỏi phổ biến như Multiple Choice, True/False/Not Given, Yes/No/Not Given, Matching Headings, Summary Completion và nhiều dạng khác.

Mỗi passage được thiết kế tăng dần độ khó từ Easy (Band 5.0-6.5), Medium (Band 6.0-7.5) đến Hard (Band 7.0-9.0), giúp bạn làm quen với cấu trúc thi thật và phát triển kỹ năng đọc hiểu một cách bài bản. Đặc biệt, phần đáp án chi tiết kèm giải thích sẽ giúp bạn hiểu rõ logic làm bài và cách paraphrase – kỹ năng cốt lõi để đạt band điểm cao.

Đề thi này phù hợp cho học viên từ band 5.0 trở lên, đang trong quá trình ôn luyện IELTS Reading và muốn làm quen với chủ đề công nghệ trong nông nghiệp.

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1. Hướng Dẫn Làm Bài IELTS Reading

Tổng Quan Về IELTS Reading Test

IELTS Reading Test bao gồm 3 passages với tổng cộng 40 câu hỏi, thời gian làm bài là 60 phút. Không có thời gian chuyển đáp án riêng, vì vậy bạn cần quản lý thời gian hiệu quả.

Phân bổ thời gian khuyến nghị:

• Passage 1: 15-17 phút (độ khó thấp, câu hỏi dễ xác định)
• Passage 2: 18-20 phút (độ khó trung bình, yêu cầu hiểu sâu hơn)
• Passage 3: 23-25 phút (độ khó cao, cần phân tích và suy luận)

Lưu ý dành 2-3 phút cuối để kiểm tra và chuyển đáp án vào phiếu trả lời.

Các Dạng Câu Hỏi Trong Đề Này

Đề thi mẫu này bao gồm 7 dạng câu hỏi phổ biến nhất:

1. Multiple Choice – Chọn đáp án đúng từ A, B, C, D
2. True/False/Not Given – Xác định thông tin đúng, sai hay không được đề cập
3. Yes/No/Not Given – Xác định ý kiến của tác giả
4. Matching Headings – Nối tiêu đề với đoạn văn phù hợp
5. Summary Completion – Hoàn thành tóm tắt bài đọc
6. Matching Features – Nối thông tin với đối tượng tương ứng
7. Short-answer Questions – Trả lời câu hỏi ngắn

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2. IELTS Reading Practice Test

PASSAGE 1 – The Digital Revolution in Modern Farming

Độ khó: Easy (Band 5.0-6.5)

Thời gian đề xuất: 15-17 phút

Agriculture has been the backbone of human civilization for thousands of years, but the way we grow food is changing dramatically. Smart agriculture, also known as precision farming, is transforming traditional farming methods through the use of modern technology. This revolution is not just about using computers on farms; it represents a fundamental shift in how farmers approach food production.

At its core, smart agriculture uses data collection and analysis to help farmers make better decisions. Farmers can now install sensors in their fields that monitor soil moisture, temperature, and nutrient levels in real-time. These sensors send information to computers or smartphones, allowing farmers to see exactly what is happening across their entire farm without having to walk through every field. This technology is particularly useful for large farms where manual monitoring would be time-consuming and impractical.

One of the most visible examples of smart agriculture is the use of drones. These unmanned aerial vehicles fly over fields and take detailed photographs using special cameras. The images can show which areas of a crop are healthy and which areas might be suffering from disease, pest infestation, or water stress. By identifying problems early, farmers can take action quickly, often treating only the affected areas rather than spraying entire fields with chemicals. This targeted approach saves money and reduces the environmental impact of farming.

GPS technology has also become essential in modern farming. Tractors and other farm equipment can now drive themselves with remarkable precision, following pre-programmed routes with accuracy measured in centimeters. This automation means that farmers can plant seeds at exactly the right depth and spacing, which leads to better crop yields. Some systems can even adjust the amount of fertilizer or water being applied based on the specific needs of different parts of a field, a technique called variable rate application.

Máy bay không người lái giám sát cánh đồng trong hệ thống nông nghiệp thông minh hiện đại

Water management is another area where technology is making a significant difference. Smart irrigation systems use weather forecasts, soil moisture data, and plant needs to determine the optimal amount of water to apply. In regions where water is scarce, this technology can reduce water use by 30-50% compared to traditional irrigation methods. The systems can be controlled remotely, meaning farmers can turn irrigation on or off from their phones, even when they are away from the farm.

The benefits of smart agriculture extend beyond individual farms. When farmers share their data with researchers and technology companies, it helps to develop better crop varieties and more effective farming techniques. This collaborative approach is creating a global knowledge base that can help farmers everywhere improve their productivity. For example, data from thousands of farms can be used to predict which crop varieties will perform best in different conditions, or to identify the early warning signs of new plant diseases.

However, the adoption of smart agriculture technology is not without challenges. The initial investment in sensors, drones, and software can be expensive, which puts these tools out of reach for many small-scale farmers, especially in developing countries. There is also a learning curve – farmers need training to use new technologies effectively, and this education takes time and resources. Some older farmers are reluctant to change methods that have worked for generations.

Data privacy is another concern. As farms become more connected, questions arise about who owns the agricultural data being collected and how it should be used. Farmers worry that sharing their data might give competitors or large corporations an unfair advantage. There are also concerns about what happens if the technology fails – a malfunctioning sensor or a software error could lead to crop losses if farmers rely too heavily on automated systems.

Despite these challenges, the trend toward smart agriculture continues to grow. Governments in many countries are offering subsidies and training programs to help farmers adopt new technologies. Technology companies are developing more affordable solutions designed for small farms, and cooperative arrangements allow groups of farmers to share expensive equipment. As climate change makes weather patterns less predictable, the ability to respond quickly to changing conditions becomes increasingly valuable.

Looking ahead, experts believe that smart agriculture will become the standard practice rather than the exception. The integration of artificial intelligence and machine learning promises to make farming even more efficient and sustainable. These technologies could help feed the growing global population while reducing agriculture’s impact on the environment, making smart farming not just an option, but a necessity for the future of food production.

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Questions 1-13

Questions 1-5: Multiple Choice

Choose the correct letter, A, B, C or D.

1. According to the passage, smart agriculture is
   A. only about using computers on farms
   B. a complete change in farming approaches
   C. limited to large commercial farms
   D. replacing farmers with machines

2. Sensors in fields help farmers by
   A. replacing the need to walk through fields
   B. automatically treating crop diseases
   C. providing real-time information about field conditions
   D. reducing the size of farms needed

3. Drones are particularly useful for
   A. planting seeds automatically
   B. identifying specific problem areas in crops
   C. replacing traditional tractors
   D. controlling irrigation systems

4. GPS technology in farming equipment allows for
   A. faster driving speeds
   B. reduced fuel consumption
   C. automatic harvesting
   D. precise seed planting

5. Smart irrigation systems can reduce water usage by
   A. 10-20%
   B. 20-30%
   C. 30-50%
   D. 50-70%

Questions 6-9: True/False/Not Given

Do the following statements agree with the information given in the passage?

Write:

• TRUE if the statement agrees with the information
• FALSE if the statement contradicts the information
• NOT GIVEN if there is no information on this

6. Manual monitoring of large farms is efficient and practical.
7. Variable rate application adjusts inputs based on different field requirements.
8. All farmers are enthusiastic about adopting smart agriculture technology.
9. Climate change is making weather patterns more difficult to predict.

Questions 10-13: Sentence Completion

Complete the sentences below.

Choose NO MORE THAN TWO WORDS from the passage for each answer.

10. One major challenge for small farmers is the high __ __ required for new technology.

11. Concerns exist about __ __ regarding who controls agricultural data.

12. Many governments offer __ and training to encourage technology adoption.

13. Experts predict smart agriculture will become __ __ in the future.

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PASSAGE 2 – Economic and Environmental Impacts of Agricultural Technology

Độ khó: Medium (Band 6.0-7.5)

Thời gian đề xuất: 18-20 phút

The integration of digital technologies into agricultural systems has precipitated a paradigm shift in how we conceptualize food production. Beyond the immediate operational benefits, smart agriculture is reshaping the economic landscape of farming and generating substantial implications for environmental sustainability. The multifaceted nature of these changes requires careful examination to understand both the opportunities and limitations that this technological revolution presents.

From an economic perspective, the adoption of precision agriculture technologies presents a compelling value proposition, though one that is not without its complexities. Research conducted across multiple agricultural regions has demonstrated that farms utilizing smart technologies can achieve yield increases of 15-25% while simultaneously reducing input costs by 10-15%. These improvements stem from the optimization of resource use – applying fertilizers, pesticides, and water more efficiently means less waste and lower expenditure. The economic viability of such investments, however, is heavily dependent on farm size and crop type. Large-scale operations producing high-value crops such as grapes, almonds, or vegetables can often recoup their technology investments within 3-5 years, whereas smaller farms growing commodity crops may require a decade or more to reach break-even point.

The labor market dynamics within agriculture are also undergoing significant transformation. While automation reduces the need for certain types of manual labor, particularly repetitive tasks like weeding or harvesting, it simultaneously creates demand for new skill sets. Modern farms increasingly require workers who can interpret data, maintain sophisticated equipment, and make informed decisions based on analytical insights. This shift is creating a generational divide within farming communities – younger farmers who have grown up with technology adapt more readily, while older generations often struggle with the transition. The implications extend beyond individual farms to entire rural communities, where the changing nature of agricultural employment affects local economies and social structures.

Phân tích dữ liệu nông nghiệp thông minh giúp tối ưu hóa năng suất và giảm chi phí

Environmental considerations represent perhaps the most consequential aspect of smart agriculture’s impact. Traditional farming practices have long been criticized for their degradation of natural resources – excessive water use, soil depletion, and chemical runoff that contaminates waterways. Smart agriculture offers potential solutions to these problems through more targeted and judicious use of resources. For instance, precision application technologies ensure that agrochemicals are used only where needed and in appropriate quantities, reducing the total volume of chemicals released into the environment by up to 40%. Similarly, sophisticated irrigation systems that respond to real-time soil moisture data and weather forecasts can dramatically reduce water consumption, a critical advantage in regions facing water scarcity.

The relationship between smart agriculture and biodiversity presents a more nuanced picture. On one hand, reduced chemical use and more efficient land utilization can create conditions more favorable to wildlife. Studies from European farms have shown that precision farming techniques can support higher populations of beneficial insects and birds compared to conventional methods. On the other hand, the trend toward larger, more technologically advanced farms can lead to consolidation of agricultural land, potentially reducing habitat diversity. The removal of hedgerows, small woodlots, and other non-productive areas to accommodate large machinery and uniform fields may offset some of the environmental gains achieved through reduced chemical use.

Carbon footprint represents another area where smart agriculture demonstrates both promise and complexity. The energy required to manufacture, transport, and operate agricultural technology adds to the carbon emissions associated with farming. However, these costs must be weighed against the efficiencies gained. More precise application of nitrogen fertilizers, for example, reduces nitrous oxide emissions – a greenhouse gas far more potent than carbon dioxide. Similarly, optimized field operations using GPS guidance systems reduce fuel consumption by minimizing overlapping passes and unnecessary vehicle movements. The net effect on carbon emissions varies significantly depending on the specific technologies employed and the farming systems in which they are used.

The scalability of smart agriculture technologies to smallholder farmers in developing nations presents both challenges and opportunities. While these farmers could potentially derive substantial benefits from precision agriculture, multiple barriers impede adoption. Beyond the obvious financial constraints, issues of infrastructure – particularly reliable internet connectivity and electricity – limit the practicality of many smart farming solutions in rural areas of developing countries. Some organizations are working to develop simplified, lower-cost versions of precision agriculture tools tailored to small-scale farming contexts. Mobile phone-based applications that provide weather forecasts, pest alerts, and market information represent one approach to bringing some benefits of agricultural technology to resource-limited farmers.

The trajectory of smart agriculture will likely be shaped by several emerging trends. Artificial intelligence and machine learning are beginning to enable predictive analytics that can anticipate problems before they become visible, potentially allowing farmers to take preventive rather than reactive measures. Blockchain technology is being explored as a means of tracking food products from farm to consumer, potentially adding value for farmers who can demonstrate sustainable practices. The convergence of these technologies with biological innovations such as gene editing and synthetic biology may further transform agricultural possibilities, though such developments also raise new ethical and regulatory questions that society must address.

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Questions 14-26

Questions 14-18: Yes/No/Not Given

Do the following statements agree with the views of the writer in the passage?

Write:

• YES if the statement agrees with the views of the writer
• NO if the statement contradicts the views of the writer
• NOT GIVEN if it is impossible to say what the writer thinks about this

14. The economic benefits of smart agriculture are straightforward and universal.
15. Younger farmers generally find it easier to adapt to new agricultural technologies than older farmers.
16. Smart agriculture completely solves the environmental problems caused by traditional farming.
17. The use of precision farming techniques can support higher populations of beneficial wildlife.
18. Mobile phone applications can help bring technology benefits to small-scale farmers.

Questions 19-23: Matching Headings

The passage has seven paragraphs, A-G.

Choose the correct heading for paragraphs B-F from the list of headings below.

List of Headings:

• i. The carbon emissions debate in modern farming
• ii. Technology barriers in developing agricultural regions
• iii. Financial returns and farm size considerations
• iv. Future technological developments in agriculture
• v. Changes in agricultural workforce requirements
• vi. Environmental benefits and concerns of precision farming
• vii. The impact on local biodiversity

19. Paragraph B
20. Paragraph C
21. Paragraph D
22. Paragraph E
23. Paragraph F

Questions 24-26: Summary Completion

Complete the summary below.

Choose NO MORE THAN TWO WORDS from the passage for each answer.

Smart agriculture can increase yields by 15-25% while reducing costs. However, the time required to reach (24) __ __ varies greatly depending on farm size. Large operations with high-value crops may recover investments within 3-5 years, while smaller farms growing (25) __ __ may need much longer. The technology also creates a (26) __ __ within farming communities due to different levels of technological familiarity.

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PASSAGE 3 – Theoretical Frameworks and Future Trajectories of Agricultural Innovation

Độ khó: Hard (Band 7.0-9.0)

Thời gian đề xuất: 23-25 phút

The metamorphosis of agricultural practices through technological intervention necessitates examination through multiple theoretical lenses to fully comprehend its ramifications for global food systems. Contemporary discourse surrounding smart agriculture often oscillates between techno-optimistic narratives that envision technology as a panacea for agricultural challenges, and more critical perspectives that interrogate the socioeconomic and ecological externalities of technologically-mediated farming systems. A nuanced understanding requires synthesizing insights from innovation diffusion theory, political economy frameworks, and socio-technical systems analysis to elucidate the complex interplay between technological capabilities, market forces, institutional structures, and environmental imperatives.

Innovation diffusion theory, as articulated by Everett Rogers, provides a foundational framework for understanding the temporal and spatial patterns of agricultural technology adoption. The theory posits that innovation adoption follows an S-shaped curve, with early adopters embracing new technologies, followed by the early and late majority, and finally laggards who resist change. In the context of smart agriculture, this pattern is evident but complicated by factors extraneous to the original model. The capital-intensive nature of precision agriculture technologies creates a bifurcation in the adoption curve, with well-resourced commercial operations comprising the bulk of early adopters, while smallholders remain systematically excluded. This divergence has profound implications for agricultural inequality, potentially exacerbating the disparity between large agribusinesses and subsistence farmers, thereby reinforcing existing power asymmetries within the global food system.

The political economy of agricultural innovation reveals how smart agriculture is embedded within and shaped by broader capitalist structures. Critical scholars argue that the proliferation of proprietary technologies in agriculture represents a form of technological treadmill, where farmers must continually invest in new equipment and subscriptions to remain competitive, thereby transferring wealth from farmers to technology corporations. The commodification of agricultural data raises particularly vexing questions about ownership and value extraction. When farmers’ field data is collected, aggregated, and analyzed by technology companies, who rightfully owns the resulting insights? The asymmetric power relationship between individual farmers and large technology platforms echoes concerns raised in other sectors about platform capitalism and data sovereignty. Some analysts contend that this data concentration could enable technology companies to exert unprecedented control over agricultural markets, influencing everything from seed selection to commodity pricing.

Hệ thống nông nghiệp thông minh tích hợp trí tuệ nhân tạo và phân tích dữ liệu lớn

Socio-technical systems theory offers an integrative perspective that recognizes agricultural transformation as involving not merely technological substitution but the reconfiguration of entire systems encompassing technology, infrastructure, regulations, markets, cultural practices, and knowledge systems. From this vantage point, the success or failure of smart agriculture cannot be attributed solely to the efficacy of individual technologies but must consider how these technologies align with or disrupt existing agricultural ecosystems. The interdependencies between technology components – sensors require data networks, which require reliable electricity, which requires infrastructure investment – mean that partial implementation often yields suboptimal results. This systems perspective helps explain why technologies that function effectively in developed nations’ agricultural contexts often falter when transplanted to different socio-economic and infrastructural environments.

Environmental sustainability discourse surrounding smart agriculture must grapple with the paradox of the Jevons effect, whereby efficiency improvements may lead to increased overall resource consumption rather than conservation. While precision agriculture technologies enable more efficient use of inputs per unit area, they may simultaneously facilitate the expansion of agricultural land into marginal or previously uncultivated areas, potentially offsetting efficiency gains through extensification. Moreover, the focus on optimizing productivity within existing agricultural paradigms may deflect attention from more fundamental questions about agricultural systems design. Some agroecologists argue that truly sustainable food production requires reconceptualizing agriculture around ecological principles such as biodiversity, soil health, and nutrient cycling, rather than merely making industrial agriculture more efficient through technological augmentation.

The geopolitical dimensions of agricultural technology development and dissemination merit careful consideration. As smart agriculture becomes increasingly integral to food security, questions arise about technological sovereignty and dependence. Nations relying on imported agricultural technologies may find themselves vulnerable to supply chain disruptions or geopolitical leverage. This concern has prompted several countries to develop domestic agricultural technology sectors, even when this requires substantial public investment. The potential for agricultural technologies to serve as instruments of soft power or economic statecraft adds another dimension to the calculus of agricultural innovation.

Epistemological questions about the nature of agricultural knowledge undergird many debates about smart agriculture. Traditional farming knowledge, accumulated over generations through empirical observation and transmitted through apprenticeship and community networks, is being supplemented or replaced by algorithmically-derived insights generated from large datasets. This transition raises questions about whose knowledge counts, what is lost when traditional ecological knowledge is devalued, and how different knowledge systems might be productively integrated rather than set in opposition. Some researchers advocate for participatory approaches to agricultural technology development that incorporate farmer knowledge and priorities from the outset, rather than treating farmers as passive recipients of externally-developed innovations.

Looking toward future trajectories, several emerging technologies promise to further transform agricultural possibilities while raising new ethical and practical questions. Synthetic biology approaches that enable precise genetic modifications could produce crops tailored to specific environmental conditions or nutritional profiles, though public acceptance remains uncertain. Autonomous robots capable of performing delicate tasks like fruit picking or weeding at scale may address labor shortages while displacing agricultural workers. Vertical farming and controlled environment agriculture, enabled by sophisticated monitoring and control systems, could decouple food production from traditional agricultural geography, though the energy requirements of such systems raise sustainability questions. The convergence of these technological possibilities with looming challenges such as climate change, population growth, and resource scarcity suggests that the role of technology in agriculture will remain a contested and consequential domain for decades to come.

Governance frameworks appropriate to the age of smart agriculture remain underdeveloped. Existing regulatory structures, designed for pre-digital agricultural contexts, often prove inadequate for addressing issues of data privacy, algorithmic transparency, and equitable access to agricultural technologies. International coordination will be necessary to establish norms and standards that ensure technological development serves inclusive and sustainable agricultural objectives rather than entrenching inequality or environmental degradation. The stakes of these policy decisions extend beyond agriculture itself to encompass fundamental questions about food sovereignty, rural livelihoods, and humanity’s relationship with the natural systems that sustain us.

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Questions 27-40

Questions 27-31: Multiple Choice

Choose the correct letter, A, B, C or D.

27. According to the passage, techno-optimistic narratives view technology as
    A. one of several solutions to agricultural problems
    B. a complete solution to all farming challenges
    C. inadequate for addressing modern agriculture
    D. suitable only for developed nations

28. The capital-intensive nature of smart agriculture creates
    A. equal opportunities for all farmers
    B. a division between large and small farms
    C. lower costs for smallholder farmers
    D. simplified adoption patterns

29. The author suggests that the commodification of agricultural data
    A. clearly benefits farmers economically
    B. has no impact on power relationships
    C. raises complex questions about ownership
    D. is easily resolved through existing laws

30. According to socio-technical systems theory, agricultural transformation involves
    A. only technological changes
    B. replacing old machines with new ones
    C. reconfiguring entire interconnected systems
    D. focusing solely on efficiency improvements

31. The Jevons effect paradox suggests that
    A. efficiency always leads to conservation
    B. improved efficiency may increase total consumption
    C. technology has no impact on resource use
    D. agricultural expansion is impossible

Questions 32-36: Matching Features

Match each concept (32-36) with the correct description (A-H).

Concepts:
32. Innovation diffusion theory
33. Platform capitalism
34. Socio-technical systems
35. Epistemological questions
36. Technological sovereignty

Descriptions:
A. Concerns about relying on imported technologies
B. The integration of farmer knowledge with algorithmic insights
C. How innovations spread through populations over time
D. The complete replacement of traditional farming
E. Power relationships in data-driven agricultural markets
F. Interconnected elements beyond just technology
G. Government subsidies for farming equipment
H. Automatic acceptance of all innovations

Questions 37-40: Short-answer Questions

Answer the questions below.

Choose NO MORE THAN THREE WORDS from the passage for each answer.

37. What type of knowledge has been traditionally transmitted through apprenticeship and community networks?

38. What two emerging challenges does the passage mention alongside climate change as factors affecting agriculture’s future?

39. What does the passage say remains underdeveloped for the age of smart agriculture?

40. What fundamental aspect of humanity does agricultural policy affect according to the passage?

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3. Answer Keys – Đáp Án

PASSAGE 1: Questions 1-13

1. B
2. C
3. B
4. D
5. C
6. FALSE
7. TRUE
8. FALSE
9. TRUE
10. initial investment
11. data privacy
12. subsidies
13. standard practice

PASSAGE 2: Questions 14-26

14. NO
15. YES
16. NO
17. YES
18. YES
19. iii
20. v
21. vi
22. i
23. ii
24. break-even point
25. commodity crops
26. generational divide

PASSAGE 3: Questions 27-40

27. B
28. B
29. C
30. C
31. B
32. C
33. E
34. F
35. B
36. A
37. traditional farming knowledge / traditional ecological knowledge
38. population growth, resource scarcity
39. governance frameworks
40. relationship with natural systems

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4. Giải Thích Đáp Án Chi Tiết

Passage 1 – Giải Thích

Câu 1: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: smart agriculture is
• Vị trí trong bài: Đoạn 1, dòng 2-4
• Giải thích: Bài đọc nói rõ “This revolution is not just about using computers on farms; it represents a fundamental shift in how farmers approach food production.” Từ “fundamental shift” được paraphrase thành “complete change in farming approaches” trong đáp án B. Đáp án A sai vì bài viết nói “not just about using computers”. Đáp án C và D không được đề cập.

Câu 2: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: sensors, help farmers
• Vị trí trong bài: Đoạn 2, dòng 2-5
• Giải thích: “These sensors send information to computers or smartphones, allowing farmers to see exactly what is happening” – rõ ràng là cung cấp thông tin real-time về điều kiện đồng ruộng. “Monitor soil moisture, temperature, and nutrient levels in real-time” được paraphrase thành “providing real-time information about field conditions”.

Câu 5: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: smart irrigation, reduce water usage
• Vị trí trong bài: Đoạn 5, dòng 3-4
• Giải thích: Bài viết nói rõ “this technology can reduce water use by 30-50% compared to traditional irrigation methods” – trùng khớp hoàn toàn với đáp án C.

Câu 6: FALSE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: manual monitoring, large farms, efficient, practical
• Vị trí trong bài: Đoạn 2, dòng 6-7
• Giải thích: Bài viết nói “manual monitoring would be time-consuming and impractical” – điều này trái ngược hoàn toàn với nhận định trong câu hỏi, do đó đáp án là FALSE.

Câu 7: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: variable rate application, adjust inputs, field requirements
• Vị trí trong bài: Đoạn 4, dòng 5-7
• Giải thích: “Some systems can even adjust the amount of fertilizer or water being applied based on the specific needs of different parts of a field” – câu này khẳng định chính xác nội dung của câu hỏi.

Câu 10: initial investment

• Dạng câu hỏi: Sentence Completion
• Từ khóa: challenge, small farmers, high cost
• Vị trí trong bài: Đoạn 7, dòng 2
• Giải thích: “The initial investment in sensors, drones, and software can be expensive” – cụm từ này xuất hiện chính xác trong bài và phù hợp về ngữ pháp với câu hỏi.

Câu 13: standard practice

• Dạng câu hỏi: Sentence Completion
• Từ khóa: experts, predict, smart agriculture, become, future
• Vị trí trong bài: Đoạn 10, dòng 1-2
• Giải thích: “experts believe that smart agriculture will become the standard practice rather than the exception” – cụm “standard practice” là đáp án chính xác.

Passage 2 – Giải Thích

Câu 14: NO

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: economic benefits, straightforward, universal
• Vị trí trong bài: Đoạn B, dòng 1-3
• Giải thích: Tác giả nói “presents a compelling value proposition, though one that is not without its complexities” và “The economic viability…is heavily dependent on farm size and crop type” – điều này cho thấy lợi ích kinh tế KHÔNG đơn giản và phổ quát, do đó đáp án là NO.

Câu 15: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: younger farmers, easier, adapt, older farmers
• Vị trí trong bài: Đoạn C, dòng 6-7
• Giải thích: “younger farmers who have grown up with technology adapt more readily, while older generations often struggle with the transition” – tác giả rõ ràng đồng ý với quan điểm này.

Câu 17: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: precision farming, support, beneficial wildlife
• Vị trí trong bài: Đoạn E, dòng 3-4
• Giải thích: “Studies from European farms have shown that precision farming techniques can support higher populations of beneficial insects and birds” – tác giả đưa ra bằng chứng nghiên cứu để hỗ trợ quan điểm này.

Câu 19: iii (Financial returns and farm size considerations)

• Dạng câu hỏi: Matching Headings
• Vị trí: Paragraph B
• Giải thích: Đoạn B tập trung vào việc thảo luận về lợi nhuận kinh tế (yield increases 15-25%, reducing costs 10-15%), thời gian hoàn vốn (3-5 years cho trang trại lớn, 10+ years cho trang trại nhỏ), và cách mà quy mô trang trại ảnh hưởng đến khả năng sinh lời.

Câu 20: v (Changes in agricultural workforce requirements)

• Dạng câu hỏi: Matching Headings
• Vị trí: Paragraph C
• Giải thích: Đoạn C thảo luận về sự thay đổi trong nhu cầu lao động – giảm nhu cầu lao động chân tay nhưng tăng nhu cầu về kỹ năng kỹ thuật, và sự phân chia thế hệ trong cộng đồng nông dân.

Câu 24: break-even point

• Dạng câu hỏi: Summary Completion
• Từ khóa: time required to reach
• Vị trí trong bài: Đoạn B, dòng 6-7
• Giải thích: “smaller farms…may require a decade or more to reach break-even point” – cụm từ này chính xác mô tả điểm hòa vốn.

Câu 26: generational divide

• Dạng câu hỏi: Summary Completion
• Từ khóa: creates, farming communities, technological familiarity
• Vị trí trong bài: Đoạn C, dòng 5-6
• Giải thích: “This shift is creating a generational divide within farming communities” – đây là cụm từ chính xác mô tả sự phân chia do khác biệt về trình độ công nghệ.

Passage 3 – Giải Thích

Câu 27: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: techno-optimistic narratives, view technology
• Vị trí trong bài: Đoạn 1, dòng 2-3
• Giải thích: “techno-optimistic narratives that envision technology as a panacea for agricultural challenges” – từ “panacea” (thuốc chữa bách bệnh) được paraphrase thành “complete solution to all challenges” trong đáp án B.

Câu 28: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: capital-intensive, creates
• Vị trí trong bài: Đoạn 2, dòng 4-6
• Giải thích: “The capital-intensive nature…creates a bifurcation in the adoption curve, with well-resourced commercial operations…while smallholders remain systematically excluded” – “bifurcation” (sự phân nhánh) và sự loại trừ người nông dân nhỏ cho thấy sự phân chia giữa trang trại lớn và nhỏ.

Câu 30: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: socio-technical systems theory, transformation involves
• Vị trí trong bài: Đoạn 4, dòng 1-3
• Giải thích: “agricultural transformation as involving not merely technological substitution but the reconfiguration of entire systems encompassing technology, infrastructure, regulations, markets, cultural practices, and knowledge systems” – rõ ràng là việc tái cấu trúc toàn bộ hệ thống.

Câu 31: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: Jevons effect paradox
• Vị trí trong bài: Đoạn 5, dòng 1-3
• Giải thích: “the paradox of the Jevons effect, whereby efficiency improvements may lead to increased overall resource consumption rather than conservation” – hiệu quả tăng có thể dẫn đến tiêu thụ tổng thể tăng.

Câu 32: C

• Dạng câu hỏi: Matching Features
• Giải thích: Innovation diffusion theory “provides a foundational framework for understanding the temporal and spatial patterns” of technology adoption – mô tả cách đổi mới lan truyền qua thời gian.

Câu 35: B

• Dạng câu hỏi: Matching Features
• Giải thích: Đoạn 7 thảo luận về “epistemological questions” liên quan đến việc “Traditional farming knowledge…is being supplemented or replaced by algorithmically-derived insights” và “how different knowledge systems might be productively integrated” – đây là sự tích hợp kiến thức nông dân với thông tin thuật toán.

Câu 37: traditional farming knowledge / traditional ecological knowledge

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: transmitted, apprenticeship, community networks
• Vị trí trong bài: Đoạn 7, dòng 2-3
• Giải thích: “Traditional farming knowledge, accumulated over generations through empirical observation and transmitted through apprenticeship and community networks” – cụm từ này xuất hiện chính xác trong bài.

Câu 38: population growth, resource scarcity

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: emerging challenges, alongside climate change
• Vị trí trong bài: Đoạn 8, dòng cuối
• Giải thích: “looming challenges such as climate change, population growth, and resource scarcity” – hai thách thức được nêu cùng với biến đổi khí hậu.

Câu 39: governance frameworks

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: remains underdeveloped, age of smart agriculture
• Vị trí trong bài: Đoạn 9, dòng 1
• Giải thích: “Governance frameworks appropriate to the age of smart agriculture remain underdeveloped” – cụm từ xuất hiện chính xác.

Câu 40: relationship with natural systems

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: fundamental aspect, humanity, agricultural policy
• Vị trí trong bài: Đoạn 9, dòng cuối
• Giải thích: “fundamental questions about…humanity’s relationship with the natural systems that sustain us” – đây là khía cạnh cơ bản của nhân loại mà chính sách nông nghiệp ảnh hưởng đến.

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5. Từ Vựng Quan Trọng Theo Passage

Passage 1 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
backbone	n	/ˈbækbəʊn/	xương sống, trụ cột	Agriculture has been the backbone of human civilization	the backbone of society/economy
precision farming	n phrase	/prɪˈsɪʒn ˈfɑːmɪŋ/	nông nghiệp chính xác	Smart agriculture, also known as precision farming	precision agriculture/technology
fundamental shift	n phrase	/ˌfʌndəˈmentl ʃɪft/	sự thay đổi cơ bản	represents a fundamental shift in how farmers approach	fundamental change/transformation
monitor	v	/ˈmɒnɪtə(r)/	giám sát, theo dõi	sensors that monitor soil moisture	monitor progress/conditions
nutrient levels	n phrase	/ˈnjuːtriənt ˈlevlz/	mức độ dinh dưỡng	monitor soil moisture, temperature, and nutrient levels	nutrient content/deficiency
unmanned aerial vehicles	n phrase	/ʌnˈmænd ˈeəriəl ˈviːɪklz/	phương tiện bay không người lái	drones – these unmanned aerial vehicles	aerial surveillance/photography
pest infestation	n phrase	/pest ˌɪnfeˈsteɪʃn/	sự nhiễm sâu bệnh	areas suffering from disease, pest infestation	severe infestation, pest control
targeted approach	n phrase	/ˈtɑːɡɪtɪd əˈprəʊtʃ/	cách tiếp cận có mục tiêu	This targeted approach saves money	targeted intervention/strategy
variable rate application	n phrase	/ˈveəriəbl reɪt ˌæplɪˈkeɪʃn/	ứng dụng tỷ lệ thay đổi	a technique called variable rate application	variable rate technology
crop yields	n phrase	/krɒp jiːldz/	năng suất cây trồng	leads to better crop yields	increase/improve crop yields
initial investment	n phrase	/ɪˈnɪʃl ɪnˈvestmənt/	vốn đầu tư ban đầu	The initial investment can be expensive	initial capital/cost
learning curve	n phrase	/ˈlɜːnɪŋ kɜːv/	quá trình học hỏi	There is also a learning curve	steep learning curve

Passage 2 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
precipitate	v	/prɪˈsɪpɪteɪt/	thúc đẩy, gây ra	has precipitated a paradigm shift	precipitate a crisis/change
paradigm shift	n phrase	/ˈpærədaɪm ʃɪft/	sự thay đổi mô hình tư duy	precipitated a paradigm shift	major paradigm shift
compelling	adj	/kəmˈpelɪŋ/	thuyết phục, hấp dẫn	presents a compelling value proposition	compelling evidence/argument
recoup	v	/rɪˈkuːp/	hoàn vốn, thu hồi	can often recoup their technology investments	recoup losses/costs
break-even point	n phrase	/breɪk ˈiːvn pɔɪnt/	điểm hòa vốn	may require a decade to reach break-even point	reach break-even point
generational divide	n phrase	/ˌdʒenəˈreɪʃənl dɪˈvaɪd/	khoảng cách thế hệ	creating a generational divide	bridge the generational divide
degradation	n	/ˌdeɡrəˈdeɪʃn/	sự suy thoái	criticized for their degradation of natural resources	environmental degradation
agrochemicals	n	/ˌæɡrəʊˈkemɪklz/	hóa chất nông nghiệp	ensure that agrochemicals are used only where needed	agrochemical industry/use
biodiversity	n	/ˌbaɪəʊdaɪˈvɜːsəti/	đa dạng sinh học	relationship between smart agriculture and biodiversity	biodiversity conservation/loss
consolidation	n	/kənˌsɒlɪˈdeɪʃn/	sự hợp nhất	trend toward…consolidation of agricultural land	consolidation of power/resources
carbon footprint	n phrase	/ˈkɑːbən ˈfʊtprɪnt/	dấu chân carbon	Carbon footprint represents another area	reduce carbon footprint
greenhouse gas	n phrase	/ˈɡriːnhaʊs ɡæs/	khí nhà kính	a greenhouse gas far more potent	greenhouse gas emissions
scalability	n	/ˌskeɪləˈbɪləti/	khả năng mở rộng quy mô	The scalability of smart agriculture technologies	scalability issues/challenges
impede	v	/ɪmˈpiːd/	cản trở	multiple barriers impede adoption	impede progress/development
trajectory	n	/trəˈdʒektəri/	quỹ đạo, xu hướng	The trajectory of smart agriculture	upward trajectory, career trajectory

Passage 3 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
metamorphosis	n	/ˌmetəˈmɔːfəsɪs/	sự biến đổi hoàn toàn	The metamorphosis of agricultural practices	undergo metamorphosis
ramifications	n	/ˌræmɪfɪˈkeɪʃnz/	hậu quả, tác động	to fully comprehend its ramifications	serious ramifications
oscillate	v	/ˈɒsɪleɪt/	dao động	discourse often oscillates between narratives	oscillate between extremes
panacea	n	/ˌpænəˈsɪə/	thuốc chữa bách bệnh	envision technology as a panacea	panacea for all problems
elucidate	v	/ɪˈluːsɪdeɪt/	làm sáng tỏ	to elucidate the complex interplay	elucidate a point/concept
bifurcation	n	/ˌbaɪfəˈkeɪʃn/	sự phân nhánh	creates a bifurcation in the adoption curve	bifurcation point
exacerbate	v	/ɪɡˈzæsəbeɪt/	làm trầm trọng thêm	potentially exacerbating the disparity	exacerbate tensions/problems
asymmetry	n	/eɪˈsɪmətri/	sự bất cân xứng	reinforcing existing power asymmetries	information asymmetry
proliferation	n	/prəˌlɪfəˈreɪʃn/	sự gia tăng nhanh	The proliferation of proprietary technologies	nuclear proliferation
commodification	n	/kəˌmɒdɪfɪˈkeɪʃn/	sự hàng hóa hóa	The commodification of agricultural data	commodification of culture
vexing	adj	/ˈveksɪŋ/	gây bực bội, phức tạp	raises particularly vexing questions	vexing problem/issue
sovereignty	n	/ˈsɒvrənti/	chủ quyền	concerns about platform capitalism and data sovereignty	national sovereignty
integrative	adj	/ˈɪntɪɡrətɪv/	tích hợp	offers an integrative perspective	integrative approach/framework
reconfiguration	n	/ˌriːkənˌfɪɡjəˈreɪʃn/	sự cấu hình lại	involving…the reconfiguration of entire systems	reconfiguration of space
paradox	n	/ˈpærədɒks/	nghịch lý	must grapple with the paradox	paradox of choice
extensification	n	/ɪkˌstensɪfɪˈkeɪʃən/	sự mở rộng diện tích	offsetting efficiency gains through extensification	agricultural extensification
geopolitical	adj	/ˌdʒiːəʊpəˈlɪtɪkl/	địa chính trị	The geopolitical dimensions merit consideration	geopolitical tensions/interests
epistemological	adj	/ɪˌpɪstəməˈlɒdʒɪkl/	nhận thức luận	Epistemological questions undergird debates	epistemological framework

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Kết Bài

Chủ đề “The rise of smart agriculture in food production” không chỉ phổ biến trong các kỳ thi IELTS Reading mà còn phản ánh một xu hướng toàn cầu quan trọng đang định hình lại cách chúng ta sản xuất lương thực. Qua bộ đề thi mẫu hoàn chỉnh này, bạn đã được tiếp cận với ba passages đa dạng về độ khó – từ cơ bản đến nâng cao – giúp bạn làm quen với cấu trúc và yêu cầu của bài thi thực tế.

Ba passages đã cung cấp góc nhìn toàn diện về nông nghiệp thông minh: từ các công nghệ cơ bản và ứng dụng thực tế (Passage 1), đến tác động kinh tế và môi trường (Passage 2), và cuối cùng là các khía cạnh lý thuyết phức tạp cùng triển vọng tương lai (Passage 3). Sự tăng dần về độ phức tạp này phản ánh chính xác cấu trúc của bài thi IELTS Reading thực tế.

Đáp án chi tiết kèm giải thích đã chỉ ra rõ ràng vị trí thông tin trong bài, cách paraphrase giữa câu hỏi và passage, và lý do tại sao mỗi đáp án là đúng. Đây là yếu tố then chốt giúp bạn không chỉ biết đáp án mà còn hiểu được logic làm bài – kỹ năng quan trọng để tự tin đối mặt với bất kỳ đề thi nào.

Bảng từ vựng tổng hợp hơn 40 từ và cụm từ quan trọng kèm phiên âm, nghĩa và collocations sẽ giúp bạn xây dựng vốn từ vựng học thuật vững chắc. Những từ này không chỉ hữu ích cho chủ đề nông nghiệp mà còn có thể áp dụng cho nhiều chủ đề khoa học công nghệ khác trong IELTS.

Hãy sử dụng đề thi này như một công cụ luyện tập nghiêm túc: đặt thời gian 60 phút, làm bài trong điều kiện giống thi thật, sau đó đối chiếu đáp án và đọc kỹ phần giải thích. Việc phân tích sai lầm và hiểu rõ cách làm đúng sẽ giúp bạn cải thiện kỹ năng Reading một cách bền vững và hiệu quả. Chúc bạn ôn tập tốt và đạt được band điểm mong muốn trong kỳ thi IELTS sắp tới.