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Genomines Bandeau

Réseaux Sociaux

PSI

31169–31184 sur 38177 — page 1949/2387

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  • Patrick Muriithilinkedin
    Nvidia just bought Hugging Face for $12.9 billion. Here's why smallholder farmers should care. The AI quietly transforming African agriculture, crop disease detection from a phone photo, yield prediction from satellite imagery, credit scoring for farmers with no bank statements, mostly runs on open-source models. Models a small team can download, fine-tune on local crops and local data, and deploy without a Silicon Valley budget. Hugging Face was the front door to all of that. Now the world's biggest chipmaker owns it. Maybe nothing changes. Nvidia profits when more people build. But agriculture in emerging markets has learned this lesson before with seeds and fertilizer: when the inputs get consolidated, the smallest players pay the price. For those of us building AI for smallholder finance, the takeaway is clear: Fine-tune and own your models. A crop-yield model trained on Ethiopian teff or Kenyan maize is an asset no acquisition can take from you. The real moat was never the base model, it's the local data and the trust of the farmers behind it. The next decade of agricultural AI in Africa shouldn't depend on decisions made in a boardroom in Santa Clara. #AgriTech #AI #FinancialInclusion #Smallholders #Africa #AgriFinance
    4 Septembre 2026
  • Serge Zakalinkedin
    [GRAPHIQUE 1] L’été 2026 est, de loin, le + chaud jamais observé en France, devançant 2003 de 0,8°C. Seulement 5 jours sous les normales, contre 86 au-dessus. Il laisse derrière lui une agriculture en lambeaux et des écosystèmes à l’agonie. Le froid durable sous les normes n'existe clairement plus depuis 5 ans en France. Avec +3.8°C en juin, +3.7°C en juillet et +3.3°C en août, jamais la France n'avait enchainé de telles anomalies. Et la chaleur fera son reto ur dès le début du mois de septembre, de façon durable, notamment dans le sud de la France… L’été météorologique s’achève, mais nous sommes loin d’être tirés d’affaire. -------------------------------------------------------------------------------- [GRAPHIQUE 2, CARTE 3 et CARTE 4] En termes d’intensité, la sécheresse de 2026 (courbe noir du graphique) est clairement la plus intense jamais observée en France à l’échelle nationale. À l’échelle régionale, le constat est tout aussi exceptionnel : du Poitou jusqu’à l’Alsace, une vaste partie du pays connaît la sécheresse la plus intense jamais enregistrée (rouge sur la carte). Le retour des pluies ces dix derniers jours a permis de limiter un peu la casse. Mais le répit pourrait être de courte durée : avec le retour de la chaleur début septembre, la sécheresse pourrait de nouveau atteindre des niveaux records pour cette période de l’année (sous 2022 et 1976). En terme de sévérité (intensité * durée), on ne peut pas encore se prononcer, la sécheresse 2026 étant encore loin d'être terminée.
    31 Août 2026
  • Serge Zakalinkedin
    Je pense que l’on peut désormais affirmer que la France traverse la plus grandes catastrophe agricole nationale depuis 1945. Sans aide publique, 30 000 à 35 000 exploitations pourraient se retrouver en situation de faillite, soit près de 10 % des exploitations agricoles françaises. C’est monstrueux. Le constat devient donc difficile à éviter : notre modèle agricole n’est pas suffisamment préparé au changement climatique qui arrive. C’est aussi le résultat d’un échec politique collectif : les gouvernements successifs n’ont pas suffisamment pris la mesure de l’ampleur des bouleversements que le changement climatique impose déjà, et imposera demain, à notre agriculture. Voici 3 propositions nationales pour adapter notre agriculture au changement climatique.
    29 Août 2026
  • Serge Zakalinkedin
    La fin de la sécheresse (météorologique) a été marquée par le début de la saison des orages méditerranéens offrant un spectacle grandiose durant l'intégralité de la nuit passée. Quelques centaines de photos entre l'Hortus (ici à droite) et le Pic Saint Loup (ici sortant du nuage à gauche), dont de nombreux coups de foudre ramifiés ! Il va me falloir des semaines pour tout traiter !
    20 Août 2026
  • Dr. Serge Zaka (Dr. Zarge)x
    Après 70 jours à la suite au-dessus des normes, des milliers de records battus, 5 canicules, 3 vagues de chaleur, demain, c'est enfin fini. Cette fin août se finira avec des températures normales pour la saison. Si la pluie (ENFIN!) fait sont retour sur les côtes de la Manche et https://t.co/57sdYoy1Tn
    18 Août 2026

Riya Vora

linkedin

🌱 Part 2 — Sentinel-2 & NDVI-Based Crop Stress Analysis Continuing my long-term learning journey in Geospatial AI, I’ve completed Part 2 of my end-to-end project: Multi-Sensor Satellite Data Fusion Using AI for Crop Stress, Urban Change & Climate Risk Analytics 🛰️ What I explored in this phase This stage focuses entirely on Sentinel-2 optical satellite data, building the foundation for crop stress analysis using vegetation indices. Key steps in this phase included: ➡️ Cloud-masked preprocessing of Sentinel-2 L2A imagery ➡️ NDVI (Normalized Difference Vegetation Index) generation ➡️ Multi-date NDVI time-series analysis ➡️ Feature engineering from vegetation dynamics ➡️ ML-based crop stress classification ➡️ Spatial prediction map generation 📸 The attached image shows: Left: NDVI map representing vegetation health Right: NDVI-based crop stress prediction map derived using machine learning 🌱 Why NDVI (Normalized Difference Vegetation Index)? #NDVI is a physically meaningful indicator of vegetation vigor derived from red and near-infrared reflectance. In this project, NDVI serves as the baseline signal before introducing radar (Sentinel-1) and climate variables. This phase helped me understand: ➡️How raw satellite imagery translates into geospatial features ➡️How spatial ML models behave at pixel scale ➡️The importance of avoiding data leakage in geospatial ML workflows 📍 Study Area : Ahmedabad & surrounding districts, Gujarat (India) 🔜 What’s next Part 3 will focus on integrating Sentinel-1 SAR (radar) data to improve crop stress detection under: ➡️Cloud cover ➡️Moisture-driven conditions ➡️Structural crop changes This will move the project closer to true multi-sensor fusion. #GeospatialAI #RemoteSensing #EarthObservation #Sentinel2 #SatelliteData #NDVI #AgriTech #CropMonitoring #ClimateAnalytics #MachineLearning #SpatialAnalytics #GIS #LearningJourney #DataScience

28 Décembre 2025 à 05h16

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FPOSoft

@fposoft

x

Input pricing made practical for FPOs. FPOSoft uses farmer survey averages to: • Set input prices • Estimate demand • Calculate margins instantly No guesswork. Just data. 🎥 Watch the demo. #FPO #AgriTech #FarmerData https://t.co/AO7aUuD1cq

28 Décembre 2025 à 05h13

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HUB Network

@HUBNetworkVN

x

1/ Keynote: How Blockchain Empowers Real-World AgriTech Startups Mr. Minh Bui @VnmeseMarkbui (Cardano Vietnam) shared how Cardano enables immutable AgriTech traceability, using on-chain metadata & eUTxO, featuring Palmyra—a Cardano-based platform for verifiable agri data. https://t.co/pQpkIdte8i

28 Décembre 2025 à 05h09

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Lakhani Dhruv

linkedin

Sometimes you win the title, sometimes you win the experience—and this time, I won the experience. My experience with Team Kinetic Labs at the Smart India Hackathon (SIH) 2025 has been one of the most defining chapters of my engineering journey. Competing in the Hardware category, we cleared Nirma University’s internal round and secured a top nomination. We couldn’t make it to the Grand Finale — but what we built, learned, and experienced is a win in itself. Our project, SmartShield Farming, was developed under the theme "Swadeshi for Atmanirbhar Bharat": 🚁 An autonomous drone system designed to reduce pesticide usage by 40–60% through intelligent, targeted spraying. ________________________________________ My Role: Hardware-Driven System Engineer with Software Integration (70% Hardware | 30% Software) I contributed majorly to the hardware integration, drone architecture, and system implementation, while also building essential software intelligence for smart decision-making. o Hardware & System Engineering (70%) • Integrated Nvidia Jetson Orin Nano with flight controller, camera module & spraying mechanism • Worked on power distribution, component interfacing, sensors & wiring architecture • Supported drone frame building, assembly, balancing & prototype testing • Designed the spray actuation mechanism & controlled nozzle triggering system • Ensured stable communication flow between onboard electronics and AI logic o AI/Software & Computer Vision (30%) • Developed lightweight deep learning models for crop disease detection • Implemented real-time inference pipeline on edge device • Built decision logic to spray only when severity thresholds were detected • Worked on optimizations for image processing and detection flow A drone that doesn’t just fly — it senses, analyze and acts autonomously. ________________________________________ In machine learning, high loss isn't failure — it’s learning. It corrects, improves, and evolves. This chapter was just my first stage. The vision is stronger, the foundation is built. #SIH2025 #SmartIndiaHackathon #EdgeAI #Drone #ComputerVision #AgriTech #AI #Hardware #Innovation #BuildingInPublic ________________________________________

28 Décembre 2025 à 04h06

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Ohixo Crop Science

linkedin

खेत में अब अनुमान नहीं तकनीक से सही निर्णय! 🌾 #SmartFarming #AgriTech #ModernAgriculture #FarmersFirst #CropScience

28 Décembre 2025 à 04h00

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KUMARI JULI

linkedin

𝐒𝐮𝐬𝐭𝐚𝐢𝐧𝐚𝐛𝐥𝐞 𝐀𝐠𝐫𝐢𝐜𝐮𝐥𝐭𝐮𝐫𝐞: $16.2 𝐁𝐢𝐥𝐥𝐢𝐨𝐧 𝐆𝐫𝐞𝐞𝐧 𝐅𝐚𝐫𝐦𝐢𝐧𝐠 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐃𝐨𝐰𝐧𝐥𝐨𝐚𝐝 𝐏𝐃𝐅 𝐁𝐫𝐨𝐜𝐡𝐮𝐫𝐞: https://lnkd.in/dv7YrQCW 1. #𝐁𝐚𝐲𝐞𝐫 𝐂𝐫𝐨𝐩𝐒𝐜𝐢𝐞𝐧𝐜𝐞 (𝐆𝐞𝐫𝐦𝐚𝐧𝐲) • 𝐌𝐚𝐫𝐤𝐞𝐭 𝐕𝐚𝐥𝐮𝐞 (2025): US $3.2 billion • 𝐖𝐡𝐚𝐭: Global pioneer in regenerative agriculture and precision crop management. • 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: o Promoting low-carbon, water-efficient farming technologies o Investment in bio-based fertilizers and digital farm platforms o Collaborating with global sustainability initiatives 2. #𝐒𝐲𝐧𝐠𝐞𝐧𝐭𝐚 𝐆𝐫𝐨𝐮𝐩 (𝐒𝐰𝐢𝐭𝐳𝐞𝐫𝐥𝐚𝐧𝐝) • 𝐌𝐚𝐫𝐤𝐞𝐭 𝐕𝐚𝐥𝐮𝐞 (2025): US $2.8 billion • 𝐖𝐡𝐚𝐭: Leader in soil health, crop protection, and sustainable farm inputs. • 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: o Expanding regenerative agriculture programs across 40+ countries o Focus on biological pest control and soil carbon restoration o Partnerships for farmer training and climate-smart adoption 3. #𝐂𝐨𝐫𝐭𝐞𝐯𝐚 𝐀𝐠𝐫𝐢𝐒𝐜𝐢𝐞𝐧𝐜𝐞 (𝐔𝐒𝐀) • 𝐌𝐚𝐫𝐤𝐞𝐭 𝐕𝐚𝐥𝐮𝐞 (2025): US $2.3 billion • 𝐖𝐡𝐚𝐭: U.S.-based developer of climate-resilient seed genetics and crop systems. • 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: o AI-driven precision farming and soil analytics o Expanding regenerative seed programs for smallholder farmers o Major advocate for net-zero agriculture initiatives 4. #𝐈𝐂𝐀𝐑 𝐀𝐠𝐫𝐢𝐜𝐮𝐥𝐭𝐮𝐫𝐚𝐥 𝐈𝐧𝐬𝐭𝐢𝐭𝐮𝐭𝐞𝐬 (𝐈𝐧𝐝𝐢𝐚) • 𝐌𝐚𝐫𝐤𝐞𝐭 𝐕𝐚𝐥𝐮𝐞 (2025): US $1.7 billion • 𝐖𝐡𝐚𝐭: India’s leading research network driving sustainable and climate-smart agriculture. • 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: o Developing organic and integrated nutrient management systems o Supporting smallholder climate adaptation and agri-fintech programs o Expanding sustainable irrigation and soil health solutions 5. #𝐘𝐚𝐫𝐚 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐨𝐧𝐚𝐥 (𝐍𝐨𝐫𝐰𝐚𝐲) • 𝐌𝐚𝐫𝐤𝐞𝐭 𝐕𝐚𝐥𝐮𝐞 (2025): US $1.3 billion • 𝐖𝐡𝐚𝐭: Global leader in sustainable fertilizers and carbon-neutral nutrient solutions. • 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: o Promoting precision nutrition and digital soil monitoring o Investments in green ammonia and low-emission fertilizer plants o Active across Europe, Asia, and Africa for climate-smart farming #SustainableAgriculture #RegenerativeFarming #ClimateSmartAgriculture #AgriInnovation #GreenFarming #OrganicFertilizers #AgriTech #FarmSustainability #SoilHealth #CarbonFarming #AgriBiotech #FoodSecurity #SmartFarming #CircularAgriculture #AgriFintech #PrecisionAgriculture #Sustainability2025 #AgriBusiness #EcoFarming #NetZeroAgriculture

28 Décembre 2025 à 03h50

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Zoelle West

@ArmaniArnolr506

x

AI-driven authentication systems improve identity verification. #AIIdentity #SecureTech AI predicts crop yields based on weather and soil data. #AgriTech #SmartFarming

28 Décembre 2025 à 03h48

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Dr.Chinmay Rath

linkedin

Odisha is turning the Gandhamardan Hills in western Odisha into a centre for Ayurvedic and herbal medicine, leveraging the region’s rich biodiversity of 2,200–2,500 medicinal plants, including 350 rare species. The initiative aims to cultivate medicinal herbs over 25,000 acres, blending traditional knowledge with modern techniques to create sustainable livelihoods for thousands of local families. The project, spearheaded by the State Medicinal Plant Board (SMPB), seeks to establish Odisha as a leading global producer of Ayurvedic products. Experts emphasize the urgency of conservation as several rare herbs are dwindling due to overharvesting. Local vaidyas have long relied on Gandhamardan for herbal remedies, and the government’s plan will help bring these plants to national and international markets while protecting the ecosystem. The initiative gained momentum during the Pravasi Bharatiya Divas convention, with global Ayurvedic experts endorsing the plan. Officials say this project not only preserves heritage but also aligns with the booming global Ayurvedic market, projected to grow from $19 billion in 2025 to $46 billion by 2030. MY Bhubaneswar #MYBhubaneswar Share and Stay Updated ❣️ #GandhamardanHills #AyurvedaOdisha #MedicinalPlants #HerbalMedicine #OdishaEconomy #SustainableLivelihoods #AyurvedicParadise #OdishaNews #ViksitOdisha

28 Décembre 2025 à 01h48

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AJF Global (Private) Limited

linkedin

FUTURE OF RICE 🌾🚀 AI in Rice Grading: Smartphone + Computer Vision 📱👁️ Rice quality grading is entering a new era—where a smartphone camera and computer vision can help measure key quality parameters in seconds. At AJF Global 🇵🇰, we believe the future of rice isn’t just about exporting more—it’s about exporting smarter, with trust, consistency, and innovation across the value chain. ✅ What AI-based rice grading can detect Using image analysis + machine learning, a simple smartphone scan can identify: 🔹 Broken % — accurate estimation of broken grain ratio ⚪ Chalkiness — spotting opaque/white grains affecting appearance & cooking quality 🧹 Impurities — detecting foreign matter (husk, stones, dust, black grains, etc.) 📏 Grain length & uniformity — sizing and consistency checks 🎯 Batch-to-batch consistency — less variation, more reliability 🌍 Why this matters for the rice value chain AI grading isn’t just “cool tech”—it solves real trade problems: ⏱️ Faster decisions at procurement & loading points 📉 Reduced disputes between buyers & sellers 📊 Standardized quality reports for every shipment 🔍 More transparency for importers, distributors & retailers 🏆 Improved brand trust for Pakistani rice in global markets 🧠 AJF Global’s forward-looking approach At AJF Global, we continuously learn and adopt modern innovations to improve rice, maize, and sesame trade. Our goal is simple: 🌟 Delight the entire value chain — from farmers and millers to overseas buyers and end consumers. The future belongs to companies that invest in: 🚀 innovation 📌 quality assurance 🤝 trust-driven trade 🌱 continuous improvement 📣 CTA (Call to Action) Want to explore AI-enabled grading, quality verification, or data-backed rice procurement for your next shipment? 📩 Message AJF Global to discuss partnerships, sourcing, or export requirements. 🌐 www.ajf-global.com 📧 info@ajfglobal.com 📞 0300 8879494 📲 WhatsApp: 0300 8879494 🌐 Let’s build the future of rice trade—together. #FutureOfRice #AIInAgriculture #RiceGrading #ComputerVision #SmartFarming #AgriTech #QualityAssurance #RiceExport #PakistanRice #Basmati #RiceTrade #SupplyChainInnovation #FoodTech #ExportExcellence #AJFGlobal #Maize #Sesame #PakistanExports #AgriInnovation #TradeWithTrust #ConnectingOpportunities

28 Décembre 2025 à 01h40

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Solange Hinault

@shinault1411

x

J'ai conçu une maison-serre hybride en briques https://t.co/q4ENTuaK7w via @YouTube

28 Décembre 2025 à 01h14

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Mariano Larrazabal

@agrobialar

x

Annual awards program recognizes innovation in agricultural and food technologies around the globe. The post Micropep Wins ‘Precision Agriculture Solution Of The Year’ in 2023 AgTech Brea... @GlobalAgTech #Agtech #Agritech  https://t.co/Wj0uL33egR

27 Décembre 2025 à 22h21

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Yisahak Arba

linkedin

🚀 Day 5/20 #MLChallenge Complete: AI Crop Yield Prediction with 90% Accuracy! Just finished building an AI system that predicts crop yields 2-3 months before harvest using satellite data! Here's what I accomplished: 🎯 PROJECT HIGHLIGHTS: • 📊 Accuracy: R² = 0.90 (90% variance explained) • 🌱 Crops: 15 types (Rice, Wheat, Maize, Coffee, etc.) • 📡 Data: Satellite vegetation indices (NDVI, GNDVI, NDWI, SAVI) • 🤖 Model: XGBoost (Extreme Gradient Boosting) • 📍 Scope: 44 agricultural fields across India 🔧 KEY TECHNICAL FEATURES: 1️⃣ Feature Engineering: Temporal aggregation of vegetation indices 2️⃣ Model Selection: XGBoost for non-linear relationship handling 3️⃣ Error Metrics: RMSE = 2.7 units, MAE = 0.96 units 4️⃣ Practical Output: Yield predictions with 2-3 month lead time 🌍 WHY THIS MATTERS: • For Farmers: Early planning for harvest, storage, sales • For Food Security: Better supply chain management • For Sustainability: Optimized resource use (water, fertilizer) • For Ethiopia: Potential adaptation for our agricultural needs 📈 MOST PREDICTIVE FEATURES (Ranked): 1. NDVI values (plant health indicator) 2. GNDVI (nutrient/chlorophyll levels) 3. Soil moisture patterns 4. Temperature during growing season 5. Crop-specific characteristics 💡 INTERESTING FINDING: The combination of NDVI + GNDVI during mid-growing season provides the strongest yield correlation. Different crops require crop-specific calibration for optimal accuracy. 🔗 All developed on Google Colab via mobile phone - proving resource constraints can't limit innovation! 👇 ENGAGEMENT QUESTIONS: 🎯 FOR FARMERS/AGRI-PROFESSIONALS: What's ONE agricultural challenge in Ethiopia that AI could help solve? A) Water usage optimization B) Pest/disease early detection C) Soil fertility mapping D) Market price prediction E) Your suggestion below! 🧠 FOR TECH COMMUNITY: Which aspect interests you most? 1) The 90% accuracy with satellite data 2) Mobile-only development journey 3) Real-world impact on agriculture 4) XGBoost implementation details 🌱 PERSONAL REFLECTION: As someone from Ethiopia, seeing how AI can transform agriculture gives me hope for food security in our region. The same satellite data exists for African farms - we just need the tools to analyze it! 💬 YOUR THOUGHTS: What agricultural innovation are you most excited about in Africa? How can we make these technologies accessible to smallholder farmers? Share your insights below! Let's grow the conversation about AI for African agriculture! 🌍 #MachineLearning #Agriculture #AI #DataScience #PrecisionFarming #XGBoost #SatelliteImagery #FoodSecurity #Ethiopia #AfricanTech #AgriTech #RemoteSensing #GoogleColab #100DaysOfCode #PortfolioProject #CropYield #SustainableAgriculture

27 Décembre 2025 à 21h00

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Maroua Chander

linkedin

I am thrilled to share my participation in the International Conference on Artificial Intelligence, Embedded Systems, and Renewable Energy (AIESRE 2025), held at Mouloud Mammeri University of Tizi Ouzou. We presented our research paper: 'Comparative Analysis of YOLOv8, YOLOv11, and Faster R-CNN for Multi-Crop Plant Disease Detection'. This milestone would not have been possible without the extraordinary support and guidance of Dr.Rim Gasmi I owe her a huge debt of gratitude; her encouragement and academic mentorship were the driving forces behind this success. Truly, we could not have achieved this without her belief in our work and her constant pursuit of excellence. Thank you, Dr. Gasmi Rim, for being an inspiring mentor and for everything you have done for us. This experience has solidified my passion for AI research and its real-world impact. I am leaving this conference with new insights, a broader professional network, and a burning drive to push the boundaries of what’s possible. This is just the beginning of a long journey toward innovation. Onwards and upwards! #AI #DeepLearning #ComputerVision #IEEE #Conference #Research #PlantDiseaseDetection #AIESRE2025 #Innovation #AgriTech

27 Décembre 2025 à 20h36

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Agri-Pulse West

@agripulsewest

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AgriTech Unleashed: Smart Solutions for Global Food Challenges Part 4 https://t.co/VKNEV08FQ5

27 Décembre 2025 à 20h15

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Olisah E

linkedin

Beyond Revenue: Using Data to Drive Sustainable Agriculture & Smart Crop Rotation 🌱 This dataset tells a powerful story about how data can help us look beyond revenue generation in agriculture and focus on sustainability, crop rotation, and long-term yield optimization. This project pushed me to go beyond intuition and truly analyze the numbers behind agricultural performance, examining how seasonal changes, soil type, humidity, irrigation, fertilizer, and pesticide usage influence crop yield. The result was a shift from guesswork to clear, data-backed insight, useful not only for farmers but also for future agribusiness goals such as farm expansion and land acquisition. 🎯 The project objective was to understand effective crop rotation and optimize crop yields, then translate these insights into actionable farming strategies. Key Insights & Observations from the analysis 🌞 Seasonal Performance Zaid (summer) is the most productive season, which yielded 644.1 tons. Cotton and barley were the highest-yield crops, with 81 tons each. Cotton plants use the most water and pesticides, while potatoes used the most fertilizer 🌧️ Kharif (Rainy Season): Barley is the highest-yielding crop. Sugarcane consumes the most water. Cotton requires the most pesticide. and potatoes use the most fertilizer. ❄️ Rabi (Winter): Soybean is the largest harvested crop. Farm F028 is the most productive farmland. Tomatoes require the most water and pesticide. 🌾 Overall Dataset Highlights - Total yield: 1,352.96 tons across 50 farmlands - Highest-yielding crop: Tomatoes (202 tons) - Crop variety: 10 different crops - Total fertilizer used: 245.27 tons - Total pesticide used: 119.9 kg - Clay soil requires the most irrigation - Barley uses the most fertilizer; maize uses the least - Maize is the least-yielding crop and was harvested in only two seasons - Most productive farmland overall: F028 💡 Recommendations for the observations - Optimize planting schedules based on seasonal yield performance - Prioritize high-yield crops (especially tomatoes) with improved farming techniques - Allocate water, fertilizer, and pesticides efficiently based on crop and soil needs - Conduct soil testing to reduce fertilizer waste and environmental impact - Improve irrigation methods to minimize water loss and ensure soil moisture balance - Adopt integrated pest management to reduce chemical pesticide dependence - Study and replicate practices from top-performing farms across lower-performing ones - Diversify crops to mitigate market and climate risks and stabilize income 🔑 Finally, this project reminded me why I enjoy the analytics path; insight consistently beats intuition, and data has the power to bring clarity where assumptions often fail. So, do you have plans for the next planting season? #DataAnalytics #AgricultureAnalytics #MicrosoftExcel #DataVisualization #DataStorytelling #Dashboard #AgriTech #Sustainability #DataCommunity

27 Décembre 2025 à 19h07

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CI2T

linkedin

🚨 SCOOP 2025 🚨 CI2T franchit une nouvelle étape majeure : 👉 nous fabriquons désormais nos propres trieurs. Une avancée stratégique qui nous permet de maîtriser 100 % de la conception à l’utilisation, en toute autonomie. 🔧 4 modèles disponibles, de 8 à 24 m² de surface de grilles, conçus pour répondre aux exigences du terrain. CI2T, fabricant français autonome, engagé pour des solutions de triage et de traitement de semences performantes et durables. ▶️ La vidéo de présentation est disponible sur notre page Facebook 👉 https://lnkd.in/etRTYiu5 📩 Contactez-nous pour en savoir plus. #CI2T #Scoop2025 #FabricantFrançais #MadeInFrance #Triage #TraitementDeSemences #MachinesAgricoles #InnovationIndustrielle #IndustrieFrançaise #AgriTech

27 Décembre 2025 à 19h06

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