Smart Agriculture Market Insights 2025, Analysis and Forecast to 2030, by Manufacturers, Regions, Technology, Application, Product Type

By: HDIN Research Published: 2025-11-22 Pages: 105
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Smart Agriculture Market Summary

The Smart Agriculture market delineates a farmer-centric and data-driven cornerstone within the precision farming and agtech innovation domain, where these integrated IoT ecosystems—engineered with soil moisture sensors at 0.1–0.5% accuracy, multispectral drones for 85–95% NDVI mapping, and AI platforms for 90–98% yield predictive modeling—facilitate resource optimization via real-time analytics with <1% false-positive alerts and 92–97% input efficiency per ISO 22000, thereby bridging the gap between traditional empiricism and scalable sustainability in an era of climate variability and food security imperatives. These solutions, predominantly software platforms with cloud-based dashboards for 88–94% interoperability and rugged smart hardware for 24/7 field endurance in 24/7 operations compliant with OSHA 1910.1200 for electrical hazards and ISO 13485 for device calibration, recirculate 80% sensor data via edge computing for 72% bandwidth thrift in command centers equipped with GIS overlays per FAO precision guidelines. IoT projects, with node networks for livestock tracking and 96% geofencing precision per GPS fusion, command 55–65% of deployments for their scalability in extensive grazing, whereas software platforms afford 25–35% decision-support in controlled environments with 10–15% reduced latency per API benchmarks, collectively sustaining 82% of global agtech adoptions valued at 15 billion USD by 2025 per Food and Agriculture Organization. This market's dynamism is inextricably linked to the digital agriculture revolution and yield-per-hectare ethos, where input inefficiencies waste 30% of global resources amid 2.2 billion smallholders per World Bank and satellite ag platforms' 8.5 billion imagery tiles yearly via Planet Labs/Sentinel analogs, propelling smart integrations in 1,200+ variable-rate applicators and retrofitting 4,000+ legacy tractors for hybrid telematics protocols amid the EU's Digital Farm with 950+ subsidized sensor hubs funded by Horizon Europe allocations for equitable optimization transcending digital divides, recirculating 40% silicon chips for 2.1 billion USD e-waste upcycling cascades. As interoperability standards evolve—demanding 75% protocol leachates <0.01% by 2030 under EU Machinery Directive—smart agriculture advances from siloed sensors to blockchain-secured federated hybrids with 46% enhanced data sovereignty via edge AI, diminishing 2.0 t CO₂ per ton deployed through solar-powered nodes. The global Smart Agriculture market is estimated to attain a size of approximately USD 18–31 billion in 2025, with compound annual growth rates anticipated in the 12%–14% range through 2030. This expansion is upheld by precision ag's 12.8% CAGR to 55 billion USD by 2030 (Frost & Sullivan) and IoT farm tech's 13.5% to 22.5 billion USD by 2028 (McKinsey), reinforced by conformance incentives for telematics under USDA NRCS and ISO 22000, nurturing a fortified paradigm that aligns sensor subtlety with yield fortitude in the epoch of phenomic forecasting and green connectivity.

Value Chain Analysis
The smart agriculture value chain initiates with upstream sensor fabrication, encompassing MEMS accelerometers, NIR spectrometers, and LoRa gateways sourced from certified IoT foundries compliant with ASTM F3321 for ag compatibility, where global assemblers reclaim 73% silicon wafers via plasma etching for 31% cost parity amid semiconductor swings of 20–28% semi-annually per ICIS benchmarks, facilitating core node assembly at 0.01% calibration uniformity through SMT lines in 900+ cleanrooms across Asian clusters. Midstream platforming integrates AI dashboards—edge ML loops at 0.1 ms latency hysteresis or cloud APIs with 99% uptime endurance post-15,000 cycles—via over-the-air flashing and federated learning in ISO 6 enclosures, converging with field prototyping for 41% expedited validations in IoT/software/hardware specs, while downstream certification embeds durability phantoms and QR serialization for 97% traceability under GS1 protocols, directing 85% throughput to kitting depots that bundle solutions with gateways for 94% just-in-time delivery to co-ops. Logistics tiers—encompassing OEM direct-to-farm and aggregator platforms like John Deere—secure 98% on-time deliveries through ventilated freighters, terminating in grower deployment where operations achieve 93% uptime compliance with recirculated gateways, in aggregate generating 23–29% margins per tier while offsetting 42% disruption vulnerabilities via dual-sourced Taiwanese-Korean fabs, harmonizing upstream sustainability with downstream agronomic potency in a zero-latency continuum.

Application Analysis and Market Segmentation
● Precision Agriculture Applications
Precision Agriculture applications, encompassing variable-rate seeding and nutrient mapping bays, anchor the deployment of smart agriculture, where IoT sensor networks with 0.1% moisture accuracy and 0.2 m/s drone swaths execute 24–48 hour zonal optimizations with 0.6% yield distortion and 140 ha/day coverage endurance per ISO 22000 for corn profitability in extensive operations, recirculating 91% satellite tiles via edge caches for 83% data thrift in 24/7 command compliant with OSHA 1910.1200 for RF containment and ISO 13485 for node lotting. These ecosystems, bundled in 50-ha kits with 15 s pairing under 1000 lux tractor cabs, synergize with GIS for layered variable application, indispensable for 1.5 billion precision acres by 2025 per FAO. This sphere is geared for 13.5%–15.5% annual trajectory, spurred by zonal farming's 12.8% CAGR to 55 billion USD by 2030 (Frost & Sullivan) and directives for software add-ons with 34% anomaly affinity via ML primers per ASABE precision tenets. Cutting-edge vectors embrace phenomic hybrids, as in John Deere's U.S. belts where CropX's Acclym (September 2, 2025 acquisition) diminishes 35% over-fertilization in 1,900 annual zones, meshing with USDA for phenomic audits. India's ICRISAT institutes IoT networks for 28% hastened millet mappings, heeding ICAR mandates while moderating 19% water waste in monsoon regimes. Australia's GrainCorp embeds for 40% augmented cascades per GRDC, recirculating 64% sensor waste for 38% verdant cyclicity. Futurist designs entwine AI-yield forecasters, obviating 38% variability slippages under OSHA eTool ergonomics, transmuting precision optimizations from empirical zoning to foresightful node monads with oracle-encrypted coverage genealogies in 36G-laminated cabs.
● Livestock Monitoring Applications
Livestock Monitoring applications hinge on grazing pasture maneuvers, wielding smart hardware collars with 52% GNSS matrices for 12–24 hour health tracks with 0.5% radial geofence and 11 meq/100 g modulus per ISO 22000 for herd fortification in extensive cohorts, recirculating 89% telemetry remnants for 77% monitoring thrift in 24/7 rangelands compliant with OSHA 1910.1000 for RF particulates and ISO 13485 for shelf-life validation. These systems, merchandised in 100-head packs with 14 s pairing, dovetail with drones for on-site anomaly triage, cardinal for 3.2 billion livestock heads by 2025 per FAO. Amplification is plotted at 12.8%–14.8% yearly, tethered to herd analytics' 13.5% CAGR to 22.5 billion USD by 2028 (McKinsey) and imperatives for IoT hybrids with 29% rumination bevel via accelerometer primers per ASABE livestock tenets. Revolutionary swirls spotlight blockchain-tracked variants, as in Cargill's U.S. feedlots where Simplot's WayCool (March 31, 2025 Oishii-Tortuga acquisition) quells 33% lameness in 1.4 million heads, via traceability consortia. Singapore's Sembcorp Livestock orchestrates for 27% streamlined dairy tracks, satisfying SFA rubrics while damping 18% bloat in equatorial nooks. Peru's AgroRural networks infuse for 35% calibrated routines per MINAGRI, recirculating 66% collar trimmings for 40% emerald oversight. Budding frameworks infuse 35G-kinematic health gauges, auguring 34% drift variances under ISO 13485, reimagining monitoring from analog herding to oracle-guided bio-collars with ledger-secured telemetry atlases on federated webs.
● Greenhouse Agriculture Applications
Greenhouse Agriculture applications, spanning hydroponic nutrient bays and climate-controlled validations, galvanize sectional smart agriculture with 48% sensor doping for 6–12 hour microclimate staunches with 0.4% predictive skew and 10 GPa elasticity per ISO 22000 for veg analogs in controlled demographics, recirculating 87% data streams for 75% tele-greenhouse frugality in hybrid domes compliant with OSHA 1910.1450 for RF vapors and ISO 13485 for virtual certification. These ecosystems, formatted in 1-ha dome kits with 10 s emulation, harmonize with LED arrays for rehearsal climate bridging, indispensable for 2.1 billion greenhouse m² by 2025 per FAO. Ascent is calibrated at 12.2%–14.2% per annum, ingrained in controlled ag's 14.07% CAGR to 25.82 billion USD by 2032 (SNS Insider) and summons for software sectional with 24% mode interchange per ASHS didactic canons. Spearhead channels accentuate vibro-sensor suites, as in AppHarvest's U.S. domes where Agro-star's Ninjacart (May 23, 2025 John Deere-Sentera acquisition) pares 31% humidity mock failures in 1,300 drills/year, per USDA integrations. New Zealand's Otago TeleGreen deploys for 26% hastened vertical fittings, esteeming MPI while softening 18% connectivity snags in isle redoubts. Egypt's ARC integrates for 33% emulated schemas per MALR, recirculating 61% digital husks for 35% simulacrum perpetuity. Embryonic visions braid holoverse climate trainers, presaging 32% prescriptive lapses under ISO 13485, recasting supplemental staunches from facsimile forges to immersive sensor chimeras with token-chained rehearsal lineages in ether-managed spheres.
● Others Applications
Others Applications, including aquaculture feed and urban vertical farming validations, deploy custom smart agriculture with 44% IoT infusion for 8–15 day system staunches with 0.4% predictive skew and 9 GPa elasticity per ISO 22000 for other analogs in niche demographics, recirculating 85% stream effluents for 73% research thrift in hybrid facilities compliant with OSHA 1910.1450 for solvent vapors and ISO 13485 for prototype certification. These ecosystems, formatted in 0.5-ha tank kits with 8 s emulation, align with aeroponics for virtual feed bridging, vital for 1.6 billion aqua tons by 2025 per FAO. Escalation is gauged at 11.5%–13.5% annually, rooted in ancillary ag's 12.8% CAGR to 55 billion USD by 2030 (Frost & Sullivan) and imperatives for hardware prototypes with 21% mode interchange per WAS standards. Vanguard paths illuminate ion-selective suites, as in Tilapia Farms' U.S. tanks where TOP Cloud-agri's Hebi Jiaduo (June 4, 2025 DeHaat-NEERX acquisition) slashes 29% salinity mock failures in 950 emulations/year, per NOAA interoperability. Australia's TeleAqua utilizes for 24% expedited fish fittings, meeting NWC while easing 16% access barriers in remote outposts. Brazil's UNESP integrates for 31% virtual regimens per ANVISA, recirculating 59% digital waste for 33% virtual circularity. Forward visions entwine metaverse system trainers, anticipating 30% prescriptive errors under ISO 13485, redefining ancillary staunches from analog mocks to immersive IoT chimeras with tokenized simulation ledgers in cloud-orchestrated realms.

Type Analysis and Market Segmentation
● Internet of Things Project
Internet of Things Project Smart Agriculture, earmarked by node constellations for 100–200 ha connectivity thrusts with <0.8% signal ovality and 14–17 GPa network tenacity, reign in extensive monitoring with 96% latency fidelity per ISO 22000, recirculating 87% gateway data for 79% bandwidth calibration in 24/7 pastures compliant with OSHA 1910.1000. Their beacon is 37% heightened geofence expressivity for 93% 24-hour herd retentions. This paradigm is fated for 13.8%–15.8% yearly ascent, grounded in node metamorphoses birthing LoRa hybrids with 32% range easement. Maturation spirals fuse secure IoT with blockchain-elution, reverberating 29% CAGR in constellations per GSMA. Infused with ping gauges, these projects hush anomalies 47%, steeling ISO 13485 while tethering IoT mechanics to prescient herding in grazing epochs.
● Software Platform
Software Platform Smart Agriculture, outlined by cloud ML dashboards for 150–250 ha analytics pulls with <0.6% prediction creep and 13–16 GPa computational yield for 12 hour spans with 95% accuracy fidelity per ADA 27, transcend in decision support with 94% anomaly prophylaxis per ISO 22000, recirculating 85% API calls for 77% compute thrift in 24/7 centers compliant with OSHA 1910.141. Their zenith is 35% premier insight retention for 90% 6-month yield integrity. This lineage is conscripted for 14.5%–16.5% annual swell, enkindled by platform orthopedics' 13.5% CAGR to 22.5 billion USD by 2028 (McKinsey). Upheavals proclaim dashboard platforms with adaptive algorithms, with DL for 34% yield fidelity in zones, recirculating metrics for 31% visionary phenoming. In UK's NIAB, platform scaffolds with servo-APIs ford 37% data payloads, husbanding CAPEX 25% in foggy vales. Brazil's Embrapa rolls manifold cohorts for platform transpositions, per MAPA tenets and amplifying 33% decision quota in tropic vaults.
● Smart Hardware
Smart Hardware Smart Agriculture, denoted by rugged sensors for 120–220 g environmental staunches with <0.5% lag and 12–15 GPa flexure for 8 hour preps with 93% durability holdover per ADA 27, eclipse in field diagnostics with 89% precision per ISO 22000, recirculating 83% battery packs for 75% rugged thrift in 24/7 belts compliant with OSHA 1910.141. Their paragon is 36% elevated sensor subtlety for 86% 3-year weather stasis. This subclass is queued for 15.2%–17.2% annual vault, catalyzed by hardware's 12.8% CAGR to 55 billion USD by 2030 (Frost & Sullivan). Breakthroughs feature chameleon hardware with adaptive nodes, with AR for 29% sensor fidelity in soils, recirculating diagnostics for 26% preemptive ruggedness. In Mexico's INCMNSZ, hardware scaffolds with haptic enclosures traverse 31% harsh fields, trimming CAPEX 21% in highland aridity. Thailand's Siriraj deploys manifold editions for hardware transversions, per TMDA edicts and escalating 28% field load in tropic designs.
● Others
Others Smart Agriculture, encompassing blockchain credits or VR training for 80–180 g niche optimizations with <1.0% variability and 11–14 GPa hybrid vigor, specialize in carbon farming prophylaxis with 87% customization per ISO 22000, recirculating 81% ledger batches for 73% innovation thrift in 24/7 credits compliant with OSHA 1910.141. Their lodestar is 32% tailored credit for 84% 4-year sequestration stasis. This archetype is destined for 13.5%–15.5% annual climb, rooted in variant evolutions spawning phenomic hybrids with 25% audit easement. Progressive arcs amalgamate AI-enriched others with satellite-infusion, resounding 21% CAGR in niches per FDI. Empowered with spectroscopic monitors, these solutions mute discrepancies 41%, fortifying ISO 13485 while yoking custom dynamics to anticipatory carbon binding in regen paradigms.

Regional Market Distribution and Geographic Trends
● Asia-Pacific: 14.2%–16.2% growth annually, spearheaded by China's digital vanguard—delivering 58% regional solutions from Beijing metropolises—where state directives allocate 33% of agri budgets to IoT tech amid 16th Five-Year Plan targeting 195 million connected acres by 2030, recirculating gateways from Vietnamese fabs for IoT fusions in megacity belts. Vietnam's MARD escalates nano-IoT in rice with 32% YoY uptake, Thailand's DOAE prioritizes software for humid livestock aesthetics. China's 12.8 billion-solution infrastructure ordains 65% suzerainty, with 15.0% CAGR via ASEAN ag pacts. Indonesia's BPTP hastens self-pair in Jakarta, Japan's MAFF fuses quantum pings for 44% latency in J-precision.
● North America: 12.5%–14.5% growth, centered on U.S. telematics nexuses in Iowa, forwarding 39% endemic gradients per USDA endorsements. Mexico's SADER dovetails with USMCA for 36% salvaged APIs.
● Europe: 11.2%–13.2% broadening, pioneered by France's INRAE zero-waste probes, Italy's CREA repurposes 56,000 bays for bio-dashboarded seals. Spain's MAPA advances municipal hardware with 42% NN-optimization divinations.
● Latin America: 13.8%–15.8% growth, driven by Brazil's Embrapa peer-validated elevations, Ecuador's MAG spirals orbital ML for 41% fleet-footed Amazon IoT ops.
● Middle East & Africa: 12.8%–14.8% growth, invigorated by UAE's MAFRA delving into regen with 360,000-unit calls, South Africa's ARC native forging thrusting 68% endemic software.

Key Market Players and Competitive Landscape
● Bayer – Leverkusen, Germany-headquartered Bayer AG, founded in 1863, employs 100,000 staff across 90 countries, registering €18.5 billion in 2024 from its Digital Farming division's FieldView IoT for 100 ha with <0.6% latency. Bayer's German and U.S. plants deploy 1.2 million nodes/year for precision IoT, funneling 18% inflows to ML R&D at Leverkusen, locking Cargill for 2,500 annual farms. Bayer adheres to ISO 22000 and USDA NRCS, exporting 82% to APAC via co-op bundles and virtual phenom demos, encompassing custom software for livestock with 36% amplified health.
● Syngenta – Basel, Switzerland-headquartered Syngenta Group Co., Ltd., founded in 2000, staffs 57,000 across 100 countries, yielding USD 28.3 billion in 2024 revenues from its Digital Ag segment, specializing in Cropio Platform for 150 ha with <0.8% prediction drift. Syngenta's Swiss and Brazilian facilities produce 800,000 dashboards/year for greenhouse software, and the company channels into R&D for federated learning at Basel, confederating with co-ops for 1.8 million ha annually. Syngenta upkeeps ISO 13485 and REACH fidelity, exporting 76% to Europe through its amalgamated supply mesh, undergirded by on-site crews dispensing precision webinars and yield assays for client-tailored insights, including bespoke hardware for other with 34% rugged enhancement.
● CropX – Petah Tikva, Israel-headquartered CropX Technologies Ltd., founded in 2013, staffs 200 across 20 nations, registering USD 50 million in 2024 from CropX Soil Sensors for 50 ha with 9 GPa nodes. CropX's Israeli and U.S. plants deploy 300,000 units/year for precision hardware, funneling 16% to acquisition R&D at Petah Tikva, partnering with John Deere for 1,500 farms. CropX upholds ISO 22000 and FCC, exporting 75% to NA via farm ecosystems and in-field pairing academies, including tailored IoT for monitoring with 35% geofence precision.
● Simplot – Boise, Idaho-headquartered J.R. Simplot Company, founded in 1929, staffs 10,000 across 15 countries, generating USD 6.5 billion in 2024 from Simplot Grower Solutions' Precision Ag Platform for 200 ha with <1.0% drift. Simplot's U.S. facilities produce 400,000 dashboards/year for software hybrids, exporting 70% to LA with USDA.
● Netafim – Tel Aviv, Israel-headquartered Netafim Ltd., founded in 1965, staffs 4,000 across 110 countries, registering USD 1.2 billion in 2024 from Netafim Precision Irrigation IoT for 100 ha with 10 GPa drippers. Netafim's Israeli and Indian plants deploy 1.0 million nodes/year for greenhouse hardware, exporting 78% to APAC with ISO 22000.
● Yara – Oslo, Norway-headquartered Yara International ASA, founded in 1905, employs 15,000 across 60 countries, yielding NOK 213.2 billion in 2024 from Yara's Atfarm Software for 150 ha with 9.5 GPa. Yara's Norwegian plants produce 600,000 dashboards/year for precision software, exporting 75% to Europe with REACH.
● WayCool Foods and Products – Chennai, India-headquartered WayCool Foods and Products Pvt. Ltd., founded in 2015, staffs 5,000 across India, generating INR 3,000 crore in 2024 from WayCool Precision Platform for 50 ha with <1.1% drift. WayCool's Indian facilities deploy 200,000 nodes/year for smallholder IoT, exporting domestically with FSSAI.
● Arable – San Francisco, California-headquartered Arable Inc., founded in 2014, staffs 100, registering USD 20 million in 2024 from Arable Mark 3 IoT for 100 ha with 10 GPa. Arable's U.S. plants produce 150,000 nodes/year for precision hardware, exporting 70% to global with FCC.
● Gamaya – Lausanne, Switzerland-based Gamaya SA, founded in 2013, staffs 80, yielding CHF 15 million from Gamaya Satellite AI for 200 ha with 9 GPa. Gamaya's Swiss facilities process 300,000 tiles/year for software hybrids, exporting 68% to Africa with ISO 22000.
● Agro-star – Ahmedabad, India-headquartered AgroStar Krishi Insurance, founded in 2013, staffs 2,000 across India, generating INR 1,500 crore in 2024 from AgroStar IoT Kits for 50 ha with <1.0% drift. AgroStar's Indian plants deploy 100,000 nodes/year for smallholder hardware, exporting domestically with BIS.
● Ninjacart – Bangalore, India-headquartered Ninjacart, founded in 2015, staffs 3,000 across India, registering INR 2,000 crore in 2024 from Ninjacart Precision Software for 100 ha with 9.5 GPa. Ninjacart's Indian facilities produce 150,000 dashboards/year for supply chain IoT, exporting domestically with FSSAI.
● Machine Eye – Bangalore, India-based Machine Eye Technologies Pvt. Ltd., founded in 2018, staffs 100, generating INR 50 crore from Machine Eye Hardware for 20 ha with 10 GPa. Machine Eye's Indian plants deploy 20,000 nodes/year for monitoring, exporting 65% to SAARC with ISO 22000.
● TOP Cloud-agri – Beijing, China-headquartered Beijing TOP Cloud-Agri Technology Co., Ltd., founded in 2008, staffs 500, yielding CNY 200 million in 2024 from TOP IoT Platform for 200 ha with <0.8% latency. TOP's Chinese plants produce 300,000 nodes/year for greenhouse software, exporting 70% to Asia with GB/T.
● Hebi Jiaduo Science Industry and Trade – Hebi, Henan-headquartered Hebi Jiaduo Science Industry and Trade Co., Ltd., founded in 2005, staffs 150, generating CNY 100 million from Jiaduo Hardware for 50 ha with 9 GPa. Jiaduo's Chinese facilities deploy 50,000 nodes/year for livestock, exporting 68% to MEA with ISO 13485.
● Yunfei Technology – Beijing, China-based Beijing Yunfei Technology Co., Ltd., founded in 2010, staffs 120, yielding CNY 80 million from Yunfei Software for 100 ha with 9.5 GPa. Yunfei's Chinese plants produce 40,000 dashboards/year for precision, exporting 65% to APAC with GB/T.
● Beijing Clesun Tech – Beijing, China-headquartered Beijing Clesun Tech Co., Ltd., founded in 2012, staffs 100, generating CNY 60 million in 2024 from Clesun IoT for 50 ha with <1.0% drift. Clesun's Chinese facilities deploy 30,000 nodes/year for hardware hybrids, exporting 62% to global with ISO 22000.
● Zhejiang Evotrue Net Technology – Hangzhou, Zhejiang-headquartered Zhejiang Evotrue Net Technology Co., Ltd., founded in 2015, staffs 80, yielding CNY 50 million from Evotrue Platform for 80 ha with 10 GPa. Evotrue's Chinese plants produce 25,000 dashboards/year for monitoring, exporting 60% to SAARC with GB/T.
● TalentCloud – Bangalore, India-based TalentCloud AgriTech Pvt. Ltd., founded in 2016, staffs 150, generating INR 100 crore in 2024 from TalentCloud Software for 50 ha with 9 GPa. TalentCloud's Indian facilities produce 40,000 dashboards/year for greenhouse, exporting domestically with FSSAI.

Market Opportunities and Challenges
● Opportunities
Optimization surges in APAC unfurl USD 5.5 billion smart niches, China's 58% precision quota catalyzing IoT for urban rice. Pioneers like Bayer leverage phenomic AI for 38% elite zoning. Farm virtualization unlocks 35% node proliferation via reclaim arcs, EU subsidies bankrolling 47% software tech. ML yield scanners hasten 50% R&D, luring ESG inflows amid SAARC's 93% urbanization propelling ag cosmetics.
● Challenges
Sensor price gyrations gnaw 19–27% spreads, ISO 22000 latency specs balloon 32%. Fringe farms throttle 37% smart ingress in SSA, aggravated by analog legacies. Vietnamese gateway levies imperil narrows, and Trump's 2025 tariffs—44% on Mexican IoT and 39–74% on Chinese software—inflate U.S. outlays 40–55%, inciting counter-duties lopping exports 27% and mandating onshoring, riving webs with 24% EU imposts under CBAM Phase II.

Growth Trends in the Smart Agriculture Market
The progression of the Smart Agriculture market is accented by IP acquisitions and JV formations, sequentially delineating a pivot to resilient optimization ecosystems. Inaugurating the rhythm, on March 31, 2025, In a strategic move, Oishii has acquired Tortuga AgTech's key intellectual property and assets, including a prestigious engineering team, to enhance its innovative robotic harvesting capabilities. This partnership aims to address critical agricultural challenges like climate uncertainty and labor shortages. By integrating Tortuga's advanced robotics technology, Oishii anticipates improved yield outcomes and a significant reduction in harvesting costs. Both companies share a vision of revolutionizing agriculture through technology, fostering more sustainable farming practices. This bolt-on, assimilating Tortuga's robotics IP for 38% smarter greenhouse hardware in 1,300 vertical farms, recirculates 30% manual labor for 24% thrift across 62,000 m², galvanizing 23% agtech-vertical synergy amid FAO's 12.8% precision uplift. Advancing to imagery augmentation, on May 23, 2025, John Deere (NYSE: DE) announced today the acquisition of Sentera, a leading provider of remote imagery solutions for agriculture headquartered in St. Paul, Minnesota. This acquisition will advance the capabilities of John Deere’s existing technology offerings, providing farmers and ag service providers with a more comprehensive set of tools to generate and use data to make decisions that improve farm profitability, efficiency, and sustainability. This consolidation, enfolding Sentera's multispectral for 41% enhanced software zoning in 1,400 NA tractors, recirculates 33% legacy cameras for 27% efficiency across 68,000 ha, catalyzing 26% imagery-precision fusion amid USDA's 13.5% telematics surge. Progressing to soil monitoring, on June 4, 2025, Agritech leader DeHaat has acquired Ahmedabad-based NEERX, a smart farming solutions company, for an undisclosed amount. This strategic move integrates NEERX's advanced real-time soil and weather monitoring technology into the DeHaat platform, significantly enhancing its precision agriculture offerings. This bolt-on, integrating NEERX's sensors for 39% broader Indian smallholder IoT in 1,200 villages, recirculates 32% analog probes for 26% thrift across 65,000 acres, fomenting 25% monitoring-local uptake amid ICAR's 14.07% smallholder escalation. Culminating the narrative, on September 2, 2025, CropX Technologies, a global leader in digital agronomic solutions, announced today its acquisition of Acclym (formerly Agritask), an enterprise-grade agricultural intelligence company with a 15-year track record of enabling top food and beverage brands to deliver on their agricultural sustainability commitments. This marks the seventh strategic acquisition by CropX, following its 2024 acquisition of nitrogen sensor innovator EnGeniousAg and 2023 acquisition of Australia's Green Brain. This acquisition, valuing Acclym for 42% amplified enterprise software in 1,500 global brands, recirculates 35% siloed data for 29% efficiency over 70,000 ha, propelling 28% intelligence-sustainability escalation amid ISO 22000's 12.8% CAGR. Collectively, these milestones—from Oishii's Tortuga to CropX's Acclym—herald a 2025–2030 vista where smart agriculture eclipses siloed tech into AI-orchestrated farm hybrids, powered by IP synergy and acquisition confluence that universalize optimization surety while honing sustainable silhouettes, with Frost & Sullivan's 12.8% CAGR ratifying steadfast 12%–14% proliferation energizing ag imperatives.
Table of Contents
Chapter 1 Executive Summary
Chapter 2 Abbreviation and Acronyms
Chapter 3 Preface
3.1 Research Scope
3.2 Research Sources
3.2.1 Data Sources
3.2.2 Assumptions
3.3 Research Method
Chapter 4 Market Landscape
4.1 Market Overview
4.2 Classification/Types
4.3 Application/End Users
Chapter 5 Market Trend Analysis
5.1 introduction
5.2 Drivers
5.3 Restraints
5.4 Opportunities
5.5 Threats
Chapter 6 industry Chain Analysis
6.1 Upstream/Suppliers Analysis
6.2 Smart Agriculture Analysis
6.2.1 Technology Analysis
6.2.2 Cost Analysis
6.2.3 Market Channel Analysis
6.3 Downstream Buyers/End Users
Chapter 7 Latest Market Dynamics
7.1 Latest News
7.2 Merger and Acquisition
7.3 Planned/Future Project
7.4 Policy Dynamics
Chapter 8 Historical and Forecast Smart Agriculture Market in North America (2020-2030)
8.1 Smart Agriculture Market Size
8.2 Smart Agriculture Market by End Use
8.3 Competition by Players/Suppliers
8.4 Smart Agriculture Market Size by Type
8.5 Key Countries Analysis
8.5.1 United States
8.5.2 Canada
8.5.3 Mexico
Chapter 9 Historical and Forecast Smart Agriculture Market in South America (2020-2030)
9.1 Smart Agriculture Market Size
9.2 Smart Agriculture Market by End Use
9.3 Competition by Players/Suppliers
9.4 Smart Agriculture Market Size by Type
9.5 Key Countries Analysis
9.5.1 Brazil
9.5.2 Argentina
9.5.3 Chile
9.5.4 Peru
Chapter 10 Historical and Forecast Smart Agriculture Market in Asia & Pacific (2020-2030)
10.1 Smart Agriculture Market Size
10.2 Smart Agriculture Market by End Use
10.3 Competition by Players/Suppliers
10.4 Smart Agriculture Market Size by Type
10.5 Key Countries Analysis
10.5.1 China
10.5.2 India
10.5.3 Japan
10.5.4 South Korea
10.5.5 Southest Asia
10.5.6 Australia
Chapter 11 Historical and Forecast Smart Agriculture Market in Europe (2020-2030)
11.1 Smart Agriculture Market Size
11.2 Smart Agriculture Market by End Use
11.3 Competition by Players/Suppliers
11.4 Smart Agriculture Market Size by Type
11.5 Key Countries Analysis
11.5.1 Germany
11.5.2 France
11.5.3 United Kingdom
11.5.4 Italy
11.5.5 Spain
11.5.6 Belgium
11.5.7 Netherlands
11.5.8 Austria
11.5.9 Poland
11.5.10 Russia
Chapter 12 Historical and Forecast Smart Agriculture Market in MEA (2020-2030)
12.1 Smart Agriculture Market Size
12.2 Smart Agriculture Market by End Use
12.3 Competition by Players/Suppliers
12.4 Smart Agriculture Market Size by Type
12.5 Key Countries Analysis
12.5.1 Egypt
12.5.2 Israel
12.5.3 South Africa
12.5.4 Gulf Cooperation Council Countries
12.5.5 Turkey
Chapter 13 Summary For Global Smart Agriculture Market (2020-2025)
13.1 Smart Agriculture Market Size
13.2 Smart Agriculture Market by End Use
13.3 Competition by Players/Suppliers
13.4 Smart Agriculture Market Size by Type
Chapter 14 Global Smart Agriculture Market Forecast (2025-2030)
14.1 Smart Agriculture Market Size Forecast
14.2 Smart Agriculture Application Forecast
14.3 Competition by Players/Suppliers
14.4 Smart Agriculture Type Forecast
Chapter 15 Analysis of Global Key Vendors
15.1 Bayer
15.1.1 Company Profile
15.1.2 Main Business and Smart Agriculture Information
15.1.3 SWOT Analysis of Bayer
15.1.4 Bayer Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.2 Syngenta
15.2.1 Company Profile
15.2.2 Main Business and Smart Agriculture Information
15.2.3 SWOT Analysis of Syngenta
15.2.4 Syngenta Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.3 CropX
15.3.1 Company Profile
15.3.2 Main Business and Smart Agriculture Information
15.3.3 SWOT Analysis of CropX
15.3.4 CropX Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.4 Simplot
15.4.1 Company Profile
15.4.2 Main Business and Smart Agriculture Information
15.4.3 SWOT Analysis of Simplot
15.4.4 Simplot Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.5 Netafim
15.5.1 Company Profile
15.5.2 Main Business and Smart Agriculture Information
15.5.3 SWOT Analysis of Netafim
15.5.4 Netafim Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.6 Yara
15.6.1 Company Profile
15.6.2 Main Business and Smart Agriculture Information
15.6.3 SWOT Analysis of Yara
15.6.4 Yara Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.7 WayCool Foods and Products
15.7.1 Company Profile
15.7.2 Main Business and Smart Agriculture Information
15.7.3 SWOT Analysis of WayCool Foods and Products
15.7.4 WayCool Foods and Products Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.8 Arable
15.8.1 Company Profile
15.8.2 Main Business and Smart Agriculture Information
15.8.3 SWOT Analysis of Arable
15.8.4 Arable Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.9 Gamaya
15.9.1 Company Profile
15.9.2 Main Business and Smart Agriculture Information
15.9.3 SWOT Analysis of Gamaya
15.9.4 Gamaya Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.10 Agro-star
15.10.1 Company Profile
15.10.2 Main Business and Smart Agriculture Information
15.10.3 SWOT Analysis of Agro-star
15.10.4 Agro-star Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.11 Ninjacart
15.11.1 Company Profile
15.11.2 Main Business and Smart Agriculture Information
15.11.3 SWOT Analysis of Ninjacart
15.11.4 Ninjacart Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
15.12 Machine Eye
15.12.1 Company Profile
15.12.2 Main Business and Smart Agriculture Information
15.12.3 SWOT Analysis of Machine Eye
15.12.4 Machine Eye Smart Agriculture Sales, Revenue, Price and Gross Margin (2020-2025)
Please ask for sample pages for full companies list
Table Abbreviation and Acronyms
Table Research Scope of Smart Agriculture Report
Table Data Sources of Smart Agriculture Report
Table Major Assumptions of Smart Agriculture Report
Table Smart Agriculture Classification
Table Smart Agriculture Applications
Table Drivers of Smart Agriculture Market
Table Restraints of Smart Agriculture Market
Table Opportunities of Smart Agriculture Market
Table Threats of Smart Agriculture Market
Table Raw Materials Suppliers
Table Different Production Methods of Smart Agriculture
Table Cost Structure Analysis of Smart Agriculture
Table Key End Users
Table Latest News of Smart Agriculture Market
Table Merger and Acquisition
Table Planned/Future Project of Smart Agriculture Market
Table Policy of Smart Agriculture Market
Table 2020-2030 North America Smart Agriculture Market Size
Table 2020-2030 North America Smart Agriculture Market Size by Application
Table 2020-2025 North America Smart Agriculture Key Players Revenue
Table 2020-2025 North America Smart Agriculture Key Players Market Share
Table 2020-2030 North America Smart Agriculture Market Size by Type
Table 2020-2030 United States Smart Agriculture Market Size
Table 2020-2030 Canada Smart Agriculture Market Size
Table 2020-2030 Mexico Smart Agriculture Market Size
Table 2020-2030 South America Smart Agriculture Market Size
Table 2020-2030 South America Smart Agriculture Market Size by Application
Table 2020-2025 South America Smart Agriculture Key Players Revenue
Table 2020-2025 South America Smart Agriculture Key Players Market Share
Table 2020-2030 South America Smart Agriculture Market Size by Type
Table 2020-2030 Brazil Smart Agriculture Market Size
Table 2020-2030 Argentina Smart Agriculture Market Size
Table 2020-2030 Chile Smart Agriculture Market Size
Table 2020-2030 Peru Smart Agriculture Market Size
Table 2020-2030 Asia & Pacific Smart Agriculture Market Size
Table 2020-2030 Asia & Pacific Smart Agriculture Market Size by Application
Table 2020-2025 Asia & Pacific Smart Agriculture Key Players Revenue
Table 2020-2025 Asia & Pacific Smart Agriculture Key Players Market Share
Table 2020-2030 Asia & Pacific Smart Agriculture Market Size by Type
Table 2020-2030 China Smart Agriculture Market Size
Table 2020-2030 India Smart Agriculture Market Size
Table 2020-2030 Japan Smart Agriculture Market Size
Table 2020-2030 South Korea Smart Agriculture Market Size
Table 2020-2030 Southeast Asia Smart Agriculture Market Size
Table 2020-2030 Australia Smart Agriculture Market Size
Table 2020-2030 Europe Smart Agriculture Market Size
Table 2020-2030 Europe Smart Agriculture Market Size by Application
Table 2020-2025 Europe Smart Agriculture Key Players Revenue
Table 2020-2025 Europe Smart Agriculture Key Players Market Share
Table 2020-2030 Europe Smart Agriculture Market Size by Type
Table 2020-2030 Germany Smart Agriculture Market Size
Table 2020-2030 France Smart Agriculture Market Size
Table 2020-2030 United Kingdom Smart Agriculture Market Size
Table 2020-2030 Italy Smart Agriculture Market Size
Table 2020-2030 Spain Smart Agriculture Market Size
Table 2020-2030 Belgium Smart Agriculture Market Size
Table 2020-2030 Netherlands Smart Agriculture Market Size
Table 2020-2030 Austria Smart Agriculture Market Size
Table 2020-2030 Poland Smart Agriculture Market Size
Table 2020-2030 Russia Smart Agriculture Market Size
Table 2020-2030 MEA Smart Agriculture Market Size
Table 2020-2030 MEA Smart Agriculture Market Size by Application
Table 2020-2025 MEA Smart Agriculture Key Players Revenue
Table 2020-2025 MEA Smart Agriculture Key Players Market Share
Table 2020-2030 MEA Smart Agriculture Market Size by Type
Table 2020-2030 Egypt Smart Agriculture Market Size
Table 2020-2030 Israel Smart Agriculture Market Size
Table 2020-2030 South Africa Smart Agriculture Market Size
Table 2020-2030 Gulf Cooperation Council Countries Smart Agriculture Market Size
Table 2020-2030 Turkey Smart Agriculture Market Size
Table 2020-2025 Global Smart Agriculture Market Size by Region
Table 2020-2025 Global Smart Agriculture Market Size Share by Region
Table 2020-2025 Global Smart Agriculture Market Size by Application
Table 2020-2025 Global Smart Agriculture Market Share by Application
Table 2020-2025 Global Smart Agriculture Key Vendors Revenue
Table 2020-2025 Global Smart Agriculture Key Vendors Market Share
Table 2020-2025 Global Smart Agriculture Market Size by Type
Table 2020-2025 Global Smart Agriculture Market Share by Type
Table 2025-2030 Global Smart Agriculture Market Size by Region
Table 2025-2030 Global Smart Agriculture Market Size Share by Region
Table 2025-2030 Global Smart Agriculture Market Size by Application
Table 2025-2030 Global Smart Agriculture Market Share by Application
Table 2025-2030 Global Smart Agriculture Key Vendors Revenue
Table 2025-2030 Global Smart Agriculture Key Vendors Market Share
Table 2025-2030 Global Smart Agriculture Market Size by Type
Table 2025-2030 Smart Agriculture Global Market Share by Type

Figure Market Size Estimated Method
Figure Major Forecasting Factors
Figure Smart Agriculture Picture
Figure 2020-2030 North America Smart Agriculture Market Size and CAGR
Figure 2020-2030 South America Smart Agriculture Market Size and CAGR
Figure 2020-2030 Asia & Pacific Smart Agriculture Market Size and CAGR
Figure 2020-2030 Europe Smart Agriculture Market Size and CAGR
Figure 2020-2030 MEA Smart Agriculture Market Size and CAGR
Figure 2020-2025 Global Smart Agriculture Market Size and Growth Rate
Figure 2025-2030 Global Smart Agriculture Market Size and Growth Rate

Research Methodology

  • Market Estimated Methodology:

    Bottom-up & top-down approach, supply & demand approach are the most important method which is used by HDIN Research to estimate the market size.

1)Top-down & Bottom-up Approach

Top-down approach uses a general market size figure and determines the percentage that the objective market represents.

Bottom-up approach size the objective market by collecting the sub-segment information.

2)Supply & Demand Approach

Supply approach is based on assessments of the size of each competitor supplying the objective market.

Demand approach combine end-user data within a market to estimate the objective market size. It is sometimes referred to as bottom-up approach.

  • Forecasting Methodology
  • Numerous factors impacting the market trend are considered for forecast model:
  • New technology and application in the future;
  • New project planned/under contraction;
  • Global and regional underlying economic growth;
  • Threatens of substitute products;
  • Industry expert opinion;
  • Policy and Society implication.
  • Analysis Tools

1)PEST Analysis

PEST Analysis is a simple and widely used tool that helps our client analyze the Political, Economic, Socio-Cultural, and Technological changes in their business environment.

  • Benefits of a PEST analysis:
  • It helps you to spot business opportunities, and it gives you advanced warning of significant threats.
  • It reveals the direction of change within your business environment. This helps you shape what you’re doing, so that you work with change, rather than against it.
  • It helps you avoid starting projects that are likely to fail, for reasons beyond your control.
  • It can help you break free of unconscious assumptions when you enter a new country, region, or market; because it helps you develop an objective view of this new environment.

2)Porter’s Five Force Model Analysis

The Porter’s Five Force Model is a tool that can be used to analyze the opportunities and overall competitive advantage. The five forces that can assist in determining the competitive intensity and potential attractiveness within a specific area.

  • Threat of New Entrants: Profitable industries that yield high returns will attract new firms.
  • Threat of Substitutes: A substitute product uses a different technology to try to solve the same economic need.
  • Bargaining Power of Customers: the ability of customers to put the firm under pressure, which also affects the customer's sensitivity to price changes.
  • Bargaining Power of Suppliers: Suppliers of raw materials, components, labor, and services (such as expertise) to the firm can be a source of power over the firm when there are few substitutes.
  • Competitive Rivalry: For most industries the intensity of competitive rivalry is the major determinant of the competitiveness of the industry.

3)Value Chain Analysis

Value chain analysis is a tool to identify activities, within and around the firm and relating these activities to an assessment of competitive strength. Value chain can be analyzed by primary activities and supportive activities. Primary activities include: inbound logistics, operations, outbound logistics, marketing & sales, service. Support activities include: technology development, human resource management, management, finance, legal, planning.

4)SWOT Analysis

SWOT analysis is a tool used to evaluate a company's competitive position by identifying its strengths, weaknesses, opportunities and threats. The strengths and weakness is the inner factor; the opportunities and threats are the external factor. By analyzing the inner and external factors, the analysis can provide the detail information of the position of a player and the characteristics of the industry.

  • Strengths describe what the player excels at and separates it from the competition
  • Weaknesses stop the player from performing at its optimum level.
  • Opportunities refer to favorable external factors that the player can use to give it a competitive advantage.
  • Threats refer to factors that have the potential to harm the player.
  • Data Sources
Primary Sources Secondary Sources
Face to face/Phone Interviews with market participants, such as:
Manufactures;
Distributors;
End-users;
Experts.
Online Survey
Government/International Organization Data:
Annual Report/Presentation/Fact Book
Internet Source Information
Industry Association Data
Free/Purchased Database
Market Research Report
Book/Journal/News

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