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Page 1 of 1Questions 1–10 of 76
Q1medium
Cost-benefit analysis before adopting precision tools is important because:
AAll technologies are always profitable on every farm✓
BReturns depend on field variability, farm size, crop value, and management capacity✓
CNo training or maintenance is ever required✓
DInput savings are guaranteed without data quality✓
💡 Explanation:
Economic value varies by context, so investment should be matched to farm conditions and capability.
Q2medium
A cybersecurity concern in connected farming systems is:
AUnauthorized access to or manipulation of farm data and equipment✓
BImproved backup of all records✓
CBetter calibration of soil sensors✓
DHigher biological nitrogen fixation directly✓
💡 Explanation:
Connected devices and platforms require protection against data theft, tampering, and service disruption.
Q3medium
API integration between farm software platforms is important because it:
ABlocks all data movement permanently✓
BReplaces agronomy with guesswork✓
CChanges crop species automatically✓
DAllows data exchange between equipment, sensors, and management systems✓
💡 Explanation:
APIs let different digital tools communicate, reducing duplicate data entry and improving workflows.
Q4medium
Edge computing in smart farming means:
AMoving all farms to city edges✓
BUsing only paper notebooks at field borders✓
CProcessing sensor data near the source before sending selected data onward✓
DStopping sensors from collecting data✓
💡 Explanation:
Edge processing can reduce latency, bandwidth needs, and dependence on continuous connectivity.
Q5medium
A digital elevation model is useful in farm planning because it helps analyze:
ASeed color and taste✓
BSlope, drainage patterns, water flow, and land leveling needs✓
CFertilizer brand popularity✓
DAnimal breed names only✓
💡 Explanation:
Elevation data support drainage design, erosion assessment, and irrigation layout.
Q6medium
Variable-rate pesticide application can reduce chemical use by:
ATreating pest or weed hotspots instead of spraying uniformly everywhere✓
BIncreasing dose in all areas regardless of need✓
CRemoving pest monitoring from the system✓
DApplying chemicals only after crop harvest✓
💡 Explanation:
Site-specific application targets areas requiring control and avoids unnecessary treatment.
Q7medium
Before using combine yield maps for decisions, the data should be:
AIgnored because maps are never useful✓
BConverted to handwritten notes only✓
CMixed with random numbers to hide variation✓
DCalibrated and cleaned to remove errors and outliers✓
💡 Explanation:
Yield data often contain errors from delays, overlaps, calibration, and edge effects that must be cleaned.
Q8medium
A management zone in precision farming is best defined as:
AA random area selected without data✓
BOnly the farm office building✓
CA field area with similar soil, yield, or management characteristics✓
DA legal district unrelated to field variability✓
💡 Explanation:
Zones group areas expected to respond similarly to inputs or management.
Q9medium
Differential GPS improves positioning by:
ARemoving all satellites from navigation✓
BUsing correction data from a reference station or network✓
CEstimating position from soil color only✓
DDisabling receivers during field operations✓
💡 Explanation:
DGPS corrects common errors using known reference locations.
Q10medium
A soil moisture sensor for irrigation scheduling should generally be installed:
AWithin the active crop root zone at representative field locations✓
BOn the tractor roof away from soil✓
CInside a sealed plastic bag above ground✓
DOnly in the driest corner regardless of crop area✓
💡 Explanation:
Representative root-zone placement gives meaningful readings for crop water availability.
Q11medium
An electronic rate controller on an applicator is used to:
AMake all nozzles different sizes randomly✓
BPrevent calibration of flow meters✓
CConvert pesticides into seed✓
DMaintain the target application rate despite speed changes✓
💡 Explanation:
Rate controllers adjust flow in response to speed and prescription to deliver the intended rate.
Q12medium
Hyperspectral sensing differs from multispectral sensing because it:
AUses only one broad visible band✓
BCannot be used for vegetation studies✓
CCaptures many narrow, contiguous spectral bands✓
DMeasures only machine fuel consumption✓
💡 Explanation:
Hyperspectral data provide detailed spectral signatures that may distinguish subtle crop or soil conditions.
Q13medium
Cloud-based farm platforms are useful because they:
AEliminate the need for data quality checks✓
BStore, analyze, and share farm data across devices and users✓
CWork only without internet at all times✓
DChange soil type instantly✓
💡 Explanation:
Cloud systems support data access, collaboration, analytics, and backup.
Q14medium
A smart greenhouse controller typically regulates:
ATemperature, humidity, ventilation, irrigation, and sometimes CO2✓
BOnly the color of the greenhouse frame✓
CMarket price of vegetables directly✓
DThe legal land title of the farm✓
💡 Explanation:
Sensors and controllers maintain greenhouse microclimate and irrigation within target ranges.
Q15medium
Blockchain is proposed in agri-food systems mainly to improve:
ASoil aeration by mechanical tillage✓
BPhotosynthesis rate directly in the leaf✓
CSeed germination without moisture✓
DTamper-resistant traceability and transaction records✓
💡 Explanation:
Distributed ledgers can support transparent records across supply chains.
Q16medium
Computer vision for pest detection relies on:
ASmelling leaves manually without records✓
BIncreasing pesticide concentration randomly✓
CImage recognition and classification of symptoms or insects✓
DIgnoring all visual field data✓
💡 Explanation:
Computer vision models analyze images to identify pests, diseases, or damage symptoms.
Q17medium
Variable-rate fertigation means:
AApplying the same fertilizer dose by hand everywhere✓
BApplying nutrients through irrigation at rates matched to zones or crop need✓
CUsing fertilizer only after harvest✓
DRemoving all irrigation equipment from the field✓
💡 Explanation:
Fertigation can be controlled spatially and temporally to improve nutrient and water efficiency.
Q18medium
Telemetry in agricultural machinery refers to:
ARemote transmission of machine location, performance, or sensor data✓
BManual counting of seeds in a tray✓
CDeep ploughing without guidance✓
DTraditional threshing by animal power only✓
💡 Explanation:
Telemetry sends equipment data to managers or platforms for monitoring and decisions.
Q19medium
A practical challenge for IoT adoption on many rural farms is:
AToo much rainfall caused by sensors✓
BGuaranteed zero equipment cost✓
CNo need for any calibration✓
DLimited connectivity, power supply, maintenance, and data skills✓
💡 Explanation:
Reliable networks, power, maintenance, and user capacity are essential for IoT systems.
Q20medium
A good UAV flight plan for mapping should consider:
AOnly the color of the drone✓
BFlying without batteries to save weight✓
CImage overlap, altitude, wind conditions, and desired ground sampling distance✓
DIgnoring legal and safety restrictions✓
💡 Explanation:
Flight parameters determine map quality, safety, and spatial resolution.
Q21medium
NDWI is commonly used in crop monitoring to assess:
AOnly soil nitrogen mineralization✓
BVegetation water content or moisture-related stress✓
CNumber of insects per leaf with certainty✓
DGrain taste after milling✓
💡 Explanation:
Water-related spectral indices help detect plant moisture status and stress.
Q22medium
Spatial interpolation of soil sample results is used to:
AEstimate values between sampled points and create continuous maps✓
BDestroy the original laboratory data✓
CConvert soil texture into rainfall data✓
DAvoid all sampling and calibration forever✓
💡 Explanation:
Interpolation methods such as kriging or inverse distance weighting estimate unsampled locations from nearby samples.
Q23medium
Laser land leveling improves irrigation performance by:
AMaking the field deliberately uneven✓
BReducing infiltration to zero✓
CReplacing all irrigation scheduling decisions✓
DCreating a uniform field grade for even water distribution✓
💡 Explanation:
Laser leveling reduces high and low spots, improving distribution uniformity and water savings.
Q24medium
Controlled traffic farming is a system in which:
AAll traffic is moved randomly across the field✓
BAnimals are banned from all farms✓
CMachinery wheels travel on fixed lanes to limit soil compaction✓
DEvery crop is harvested by hand only✓
💡 Explanation:
Keeping machinery on permanent traffic lanes confines compaction and protects crop beds.
Q25medium
Robotic weeders commonly distinguish crop plants from weeds using:
ARandom movement without sensing✓
BCameras, sensors, and image-analysis algorithms✓
COnly manual paper maps from previous decades✓
DNo power source or control system✓
💡 Explanation:
Machine vision and AI help robotic systems detect plants and target weeds precisely.
Q26medium
Use of RFID, barcode, or QR systems in agricultural supply chains mainly improves:
ATraceability from production to marketing✓
BSoil tilth without field operations✓
CRainfall amount during dry months✓
DChlorophyll synthesis inside leaves✓
💡 Explanation:
Identification technologies link products to records, improving tracking and accountability.
Q27medium
Machine learning is useful in agriculture because it can:
AGuarantee perfect weather forecasts without data✓
BReplace all sensors with paper records✓
CDetect patterns in large datasets for yield, disease, or management prediction✓
DIncrease fertilizer response by magic✓
💡 Explanation:
Machine learning models learn relationships from historical and sensor data for prediction or classification.
Q28medium
Thermal imagery can indicate crop water stress because stressed plants often have:
ANo leaves visible in any image✓
BHigher canopy temperature due to reduced transpiration cooling✓
CExactly the same temperature as irrigation water✓
DLower temperature caused by increased transpiration under severe stress always✓
💡 Explanation:
Water-stressed crops close stomata, reducing evaporative cooling and raising canopy temperature.
Q29medium
Ground control points in drone mapping are used to:
AImprove georeferencing accuracy of orthomosaics and maps✓
BIncrease pest resistance genetically✓
CBlock satellite signals over the field✓
DMake images intentionally blurry✓
💡 Explanation:
Accurately surveyed ground points help align drone imagery to real-world coordinates.
Q30medium
A farm management information system mainly provides:
AOnly a mechanical ploughing service✓
BA substitute for all field observations✓
CGuaranteed rainfall during drought✓
DDigital record keeping and integration of farm operations and data✓
💡 Explanation:
FMIS platforms organize inputs, field operations, costs, maps, and compliance records.
Q31medium
Variable-rate seeding decisions are commonly based on:
AThe number of shops in the nearby town✓
BOnly the color of the seed bag✓
CSoil productivity zones, yield goals, and plant population response✓
DThe operator height and age✓
💡 Explanation:
Seeding rate can be adjusted by zones where soil and yield potential differ.
Q32medium
Smart irrigation scheduling is often based on:
AThe color of tractor paint only✓
BEvapotranspiration, soil moisture, crop stage, and weather forecasts✓
CFixed flooding every day regardless of need✓
DMarket price of pesticide only✓
💡 Explanation:
Scheduling water according to crop demand and soil water status improves water-use efficiency.
Q33medium
A common limitation of optical satellite imagery for crop monitoring is:
ACloud cover and revisit interval can delay usable images✓
BIt can only work underground✓
CIt always measures yield perfectly without calibration✓
DIt cannot detect reflected light✓
💡 Explanation:
Clouds can block optical sensors, and satellite revisit frequency affects timeliness.
Q34medium
Automatic section control on a sprayer helps reduce:
ASeed germination percentage in a lab test✓
BThe need to clean spray nozzles forever✓
CAll wind drift under every condition✓
DOverlap and over-application at headlands and irregular field edges✓
💡 Explanation:
Section control turns boom sections on or off based on location to avoid double application.
Q35medium
Active optical crop sensors such as GreenSeeker are commonly used for:
AMeasuring tractor tyre pressure only✓
BKilling weeds by heat alone✓
CIn-season nitrogen management based on crop vigor✓
DReplacing all satellite navigation systems✓
💡 Explanation:
Optical sensors estimate canopy vigor and can guide nitrogen rates during crop growth.
Q36medium
LiDAR is especially useful in modern farming for mapping:
AProtein sequence of every crop variety✓
BElevation, canopy height, and three-dimensional structure✓
CSoil pH without calibration in all cases✓
DFertilizer price changes in markets✓
💡 Explanation:
LiDAR uses laser pulses to measure distance and create detailed elevation or structure models.
Q37medium
An agricultural decision support system is designed to:
ACombine data and models to recommend management actions✓
BReplace all farmer judgement with random choices✓
CIncrease soil erosion on slopes✓
DMeasure rainfall without any data input✓
💡 Explanation:
Decision support tools use rules, models, and datasets to guide agronomic decisions.
Q38medium
An IoT-based irrigation system commonly uses sensors to provide:
AManual paper maps only after harvest✓
BSynthetic seed treatment in the soil✓
CPermanent immunity from drought✓
DReal-time soil moisture, weather, or flow data for scheduling✓
💡 Explanation:
Internet-connected sensors can transmit field conditions for timely irrigation decisions.
Q39medium
A prescription map in precision agriculture tells equipment:
AWhich crop should be eaten by livestock first✓
BHow to change rainfall amount over the farm✓
CWhat input rate to apply at each location or management zone✓
DHow to remove GPS receivers from tractors✓
💡 Explanation:
Prescription maps translate spatial analysis into machine-readable input application instructions.
Q40medium
Soil electrical conductivity mapping is often used to indicate variation in:
AFlower color only✓
BTexture, salinity, moisture, or other soil properties✓
CTractor fuel brand✓
DSeed bag printing quality✓
💡 Explanation:
EC sensors help identify soil zones that may differ in water-holding capacity, salts, or texture.
Q41medium
The main advantage of RTK-GPS over ordinary handheld GPS is:
ACentimeter-level positional accuracy using correction signals✓
BAbility to kill insects without spraying✓
CLower accuracy for all field operations✓
DNo requirement for satellites✓
💡 Explanation:
RTK uses a base station or network corrections to greatly improve positioning accuracy.
Q42medium
Automatic steering guidance in tractors mainly reduces:
ASeed viability in storage✓
BPhotosynthesis in healthy plants✓
CAccuracy of field operations✓
DOverlaps, skips, operator fatigue, and input wastage✓
💡 Explanation:
Guidance systems keep implements on planned tracks, improving field efficiency and uniformity.
Q43medium
Multispectral drone imagery can help detect:
AThe exact taste of harvested grain✓
BThe legal ownership of all farm machinery✓
CCrop stress patterns before they are clearly visible to the eye✓
DThe price of fertilizer next year with certainty✓
💡 Explanation:
Spectral bands can reveal changes in vigor, chlorophyll, and canopy condition early.
Q44medium
Remote sensing in agriculture means obtaining crop or soil information:
AOnly by digging soil pits in every square meter✓
BWithout direct physical contact, using sensors on satellites, aircraft, or drones✓
COnly after harvesting and threshing the crop✓
DBy asking markets to estimate plant height✓
💡 Explanation:
Remote sensing measures reflected or emitted energy to infer crop and soil conditions.
Q45medium
Ultrasonic sensors on modern sprayers are often used to:
AMeasure protein content inside seeds directly✓
BReplace all nozzle calibration✓
CIdentify every weed species by smell✓
DMaintain boom height above the crop or soil surface✓
💡 Explanation:
Ultrasonic distance sensors help keep spray booms at a consistent height for uniform coverage.
Q46medium
A yield monitor on a combine harvester is used to:
AMeasure and map crop yield variation during harvesting✓
BSterilize grain before storage✓
CAutomatically change crop species in the field✓
DRemove the need for all weighing systems✓
💡 Explanation:
Yield monitors link flow and location data to produce yield maps for management decisions.
Q47medium
NDVI is commonly derived from which spectral bands?
AThermal and microwave sound only✓
BBlue and ultraviolet sound waves✓
CGamma rays and X-rays✓
DNear-infrared and red reflectance✓
💡 Explanation:
NDVI uses the contrast between high near-infrared and low red reflectance of healthy vegetation.
Q48medium
Variable-rate technology allows a farmer to:
AApply the same input rate everywhere regardless of variation✓
BEliminate calibration of machines✓
CApply inputs at different rates according to site-specific need✓
DUse only manual broadcasting in all fields✓
💡 Explanation:
VRT adjusts seed, fertilizer, pesticide, or water rates based on prescription maps or sensors.
Q49medium
A geographic information system in farming is primarily used for:
AIncreasing tractor horsepower mechanically✓
BStoring, analyzing, and displaying spatial layers of field data✓
CChanging seed genetics during planting✓
DMeasuring milk fat without instruments✓
💡 Explanation:
GIS integrates maps such as soil, yield, irrigation, and pest layers for spatial decisions.
Q50medium
In precision agriculture, GPS is used mainly to:
AGeoreference field operations and record exact locations✓
BMeasure seed germination inside a laboratory✓
CReplace all soil testing procedures✓
DConvert organic matter directly into fertilizer✓
💡 Explanation:
GPS provides location data needed for mapping, guidance, and site-specific management.
Q51medium
Use of RFID, barcode, or QR systems in agricultural supply chains mainly improves:
ATraceability from production to marketing✓
BSoil tilth without field operations✓
CRainfall amount during dry months✓
DChlorophyll synthesis inside leaves✓
💡 Explanation:
Identification technologies link products to records, improving tracking and accountability.
Q52medium
Robotic weeders commonly distinguish crop plants from weeds using:
ARandom movement without sensing✓
BCameras, sensors, and image-analysis algorithms✓
COnly manual paper maps from previous decades✓
DNo power source or control system✓
💡 Explanation:
Machine vision and AI help robotic systems detect plants and target weeds precisely.
Q53medium
Controlled traffic farming is a system in which:
AAll traffic is moved randomly across the field✓
BAnimals are banned from all farms✓
CMachinery wheels travel on fixed lanes to limit soil compaction✓
DEvery crop is harvested by hand only✓
💡 Explanation:
Keeping machinery on permanent traffic lanes confines compaction and protects crop beds.
Q54medium
Laser land leveling improves irrigation performance by:
AMaking the field deliberately uneven✓
BReducing infiltration to zero✓
CReplacing all irrigation scheduling decisions✓
DCreating a uniform field grade for even water distribution✓
💡 Explanation:
Laser leveling reduces high and low spots, improving distribution uniformity and water savings.
Q55medium
Spatial interpolation of soil sample results is used to:
AEstimate values between sampled points and create continuous maps✓
BDestroy the original laboratory data✓
CConvert soil texture into rainfall data✓
DAvoid all sampling and calibration forever✓
💡 Explanation:
Interpolation methods such as kriging or inverse distance weighting estimate unsampled locations from nearby samples.
Q56medium
NDWI is commonly used in crop monitoring to assess:
AOnly soil nitrogen mineralization✓
BVegetation water content or moisture-related stress✓
CNumber of insects per leaf with certainty✓
DGrain taste after milling✓
💡 Explanation:
Water-related spectral indices help detect plant moisture status and stress.
Q57medium
A good UAV flight plan for mapping should consider:
AOnly the color of the drone✓
BFlying without batteries to save weight✓
CImage overlap, altitude, wind conditions, and desired ground sampling distance✓
DIgnoring legal and safety restrictions✓
💡 Explanation:
Flight parameters determine map quality, safety, and spatial resolution.
Q58medium
A practical challenge for IoT adoption on many rural farms is:
AToo much rainfall caused by sensors✓
BGuaranteed zero equipment cost✓
CNo need for any calibration✓
DLimited connectivity, power supply, maintenance, and data skills✓
💡 Explanation:
Reliable networks, power, maintenance, and user capacity are essential for IoT systems.
Q59medium
Telemetry in agricultural machinery refers to:
ARemote transmission of machine location, performance, or sensor data✓
BManual counting of seeds in a tray✓
CDeep ploughing without guidance✓
DTraditional threshing by animal power only✓
💡 Explanation:
Telemetry sends equipment data to managers or platforms for monitoring and decisions.
Q60medium
Variable-rate fertigation means:
AApplying the same fertilizer dose by hand everywhere✓
BApplying nutrients through irrigation at rates matched to zones or crop need✓
CUsing fertilizer only after harvest✓
DRemoving all irrigation equipment from the field✓
💡 Explanation:
Fertigation can be controlled spatially and temporally to improve nutrient and water efficiency.
Q61medium
Computer vision for pest detection relies on:
ASmelling leaves manually without records✓
BIncreasing pesticide concentration randomly✓
CImage recognition and classification of symptoms or insects✓
DIgnoring all visual field data✓
💡 Explanation:
Computer vision models analyze images to identify pests, diseases, or damage symptoms.
Q62medium
Blockchain is proposed in agri-food systems mainly to improve:
ASoil aeration by mechanical tillage✓
BPhotosynthesis rate directly in the leaf✓
CSeed germination without moisture✓
DTamper-resistant traceability and transaction records✓
💡 Explanation:
Distributed ledgers can support transparent records across supply chains.
Q63medium
A smart greenhouse controller typically regulates:
ATemperature, humidity, ventilation, irrigation, and sometimes CO2✓
BOnly the color of the greenhouse frame✓
CMarket price of vegetables directly✓
DThe legal land title of the farm✓
💡 Explanation:
Sensors and controllers maintain greenhouse microclimate and irrigation within target ranges.
Q64medium
Cloud-based farm platforms are useful because they:
AEliminate the need for data quality checks✓
BStore, analyze, and share farm data across devices and users✓
CWork only without internet at all times✓
DChange soil type instantly✓
💡 Explanation:
Cloud systems support data access, collaboration, analytics, and backup.
Q65medium
Hyperspectral sensing differs from multispectral sensing because it:
AUses only one broad visible band✓
BCannot be used for vegetation studies✓
CCaptures many narrow, contiguous spectral bands✓
DMeasures only machine fuel consumption✓
💡 Explanation:
Hyperspectral data provide detailed spectral signatures that may distinguish subtle crop or soil conditions.
Q66medium
An electronic rate controller on an applicator is used to:
AMake all nozzles different sizes randomly✓
BPrevent calibration of flow meters✓
CConvert pesticides into seed✓
DMaintain the target application rate despite speed changes✓
💡 Explanation:
Rate controllers adjust flow in response to speed and prescription to deliver the intended rate.
Q67medium
A soil moisture sensor for irrigation scheduling should generally be installed:
AWithin the active crop root zone at representative field locations✓
BOn the tractor roof away from soil✓
CInside a sealed plastic bag above ground✓
DOnly in the driest corner regardless of crop area✓
💡 Explanation:
Representative root-zone placement gives meaningful readings for crop water availability.
Q68medium
Differential GPS improves positioning by:
ARemoving all satellites from navigation✓
BUsing correction data from a reference station or network✓
CEstimating position from soil color only✓
DDisabling receivers during field operations✓
💡 Explanation:
DGPS corrects common errors using known reference locations.
Q69medium
A management zone in precision farming is best defined as:
AA random area selected without data✓
BOnly the farm office building✓
CA field area with similar soil, yield, or management characteristics✓
DA legal district unrelated to field variability✓
💡 Explanation:
Zones group areas expected to respond similarly to inputs or management.
Q70medium
Before using combine yield maps for decisions, the data should be:
AIgnored because maps are never useful✓
BConverted to handwritten notes only✓
CMixed with random numbers to hide variation✓
DCalibrated and cleaned to remove errors and outliers✓
💡 Explanation:
Yield data often contain errors from delays, overlaps, calibration, and edge effects that must be cleaned.
Q71medium
Variable-rate pesticide application can reduce chemical use by:
ATreating pest or weed hotspots instead of spraying uniformly everywhere✓
BIncreasing dose in all areas regardless of need✓
CRemoving pest monitoring from the system✓
DApplying chemicals only after crop harvest✓
💡 Explanation:
Site-specific application targets areas requiring control and avoids unnecessary treatment.
Q72medium
A digital elevation model is useful in farm planning because it helps analyze:
ASeed color and taste✓
BSlope, drainage patterns, water flow, and land leveling needs✓
CFertilizer brand popularity✓
DAnimal breed names only✓
💡 Explanation:
Elevation data support drainage design, erosion assessment, and irrigation layout.
Q73medium
Edge computing in smart farming means:
AMoving all farms to city edges✓
BUsing only paper notebooks at field borders✓
CProcessing sensor data near the source before sending selected data onward✓
DStopping sensors from collecting data✓
💡 Explanation:
Edge processing can reduce latency, bandwidth needs, and dependence on continuous connectivity.
Q74medium
API integration between farm software platforms is important because it:
ABlocks all data movement permanently✓
BReplaces agronomy with guesswork✓
CChanges crop species automatically✓
DAllows data exchange between equipment, sensors, and management systems✓
💡 Explanation:
APIs let different digital tools communicate, reducing duplicate data entry and improving workflows.
Q75medium
A cybersecurity concern in connected farming systems is:
AUnauthorized access to or manipulation of farm data and equipment✓
BImproved backup of all records✓
CBetter calibration of soil sensors✓
DHigher biological nitrogen fixation directly✓
💡 Explanation:
Connected devices and platforms require protection against data theft, tampering, and service disruption.
Q76medium
Cost-benefit analysis before adopting precision tools is important because:
AAll technologies are always profitable on every farm✓
BReturns depend on field variability, farm size, crop value, and management capacity✓
CNo training or maintenance is ever required✓
DInput savings are guaranteed without data quality✓
💡 Explanation:
Economic value varies by context, so investment should be matched to farm conditions and capability.