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AI-Driven Coffee Cultivation

3380. Predictive Analytics for Revolutionizing Coffee Farming

6 min read January 29, 2026 Plantation & Spice Crops
High-quality visualization of 3380. predictive analytics for revolutionizing coffee farming featuring advanced farming techniques, hydroponics, and sustainable agriculture.

Predictive Analytics for Revolutionizing Coffee Farming

In the vast and ever-evolving landscape of agriculture, coffee farming has long been a cherished tradition, deeply rooted in the lives of millions around the world. However, as the global climate continues to shift and the demand for this beloved beverage rises, coffee growers face a myriad of challenges that threaten the sustainability and profitability of their operations. But amidst this uncertainty, a beacon of hope has emerged – the power of predictive analytics.

Predictive analytics, a field that harnesses the power of data, machine learning, and advanced algorithms, holds the key to unlocking a new era of coffee farming. By leveraging this transformative technology, coffee growers can gain unprecedented insights into their crops, weather patterns, and market trends, enabling them to make more informed decisions and adapt to the ever-changing landscape of agriculture.

Understanding the Challenges of Coffee Farming

Coffee farming is a complex and delicate endeavor, with growers facing a multitude of challenges that can significantly impact their yields and profitability. From unpredictable weather patterns and pest infestations to fluctuating market prices and shifting consumer preferences, the challenges are both diverse and daunting.

One of the most pressing concerns for coffee growers is the impact of climate change. As global temperatures rise and precipitation patterns become more erratic, the traditional growing regions for coffee are experiencing dramatic shifts, forcing growers to adapt their cultivation practices and explore new areas for cultivation. Without a comprehensive understanding of these changes, coffee farmers risk catastrophic losses, jeopardizing their livelihoods and the communities that depend on this vital crop.

Another significant challenge in coffee farming is the management of pests and diseases. Coffee plants are susceptible to a wide range of pests and pathogens, from the devastating coffee leaf rust to the devastating coffee berry borer. Effective pest management strategies are crucial, but they require in-depth knowledge of the specific threats faced by each region and the optimal timing for intervention.

The Power of Predictive Analytics in Coffee Farming

Predictive analytics holds the promise of revolutionizing the way coffee farming is approached and managed. By harnessing the power of data, machine learning, and advanced algorithms, coffee growers can gain unprecedented insights into the factors that influence their crops, enabling them to make more informed decisions and adapt to the ever-changing landscape of agriculture.

One of the primary applications of predictive analytics in coffee farming is the ability to forecast weather patterns and their impact on crop yields. By analyzing historical weather data, satellite imagery, and other environmental factors, predictive models can accurately predict the likelihood of extreme weather events, changes in precipitation patterns, and other climate-related risks. Armed with this knowledge, coffee growers can make proactive decisions to mitigate the impact of these events, such as adjusting planting schedules, implementing irrigation systems, or adopting protective measures for their crops.

Furthermore, predictive analytics can be leveraged to optimize pest and disease management strategies. By analyzing data on pest populations, disease incidence, and the effectiveness of various control methods, predictive models can identify the most effective and efficient ways to manage these threats. This information can guide coffee growers in the timing and application of pesticides, the deployment of biological control agents, and the implementation of integrated pest management (IPM) strategies, ultimately reducing the environmental impact and improving the overall health of their crops.

Beyond the immediate concerns of weather and pest management, predictive analytics can also provide valuable insights into market trends and consumer preferences. By analyzing data on global coffee production, consumption patterns, and price fluctuations, coffee growers can make informed decisions about which varieties to cultivate, when to sell their crop, and how to best position their products in the market. This knowledge can help them adapt to changing consumer demands, capitalize on emerging market opportunities, and ensure the long-term sustainability of their operations.

Case Studies: Predictive Analytics in Action

To illustrate the transformative power of predictive analytics in coffee farming, let’s explore a few real-world case studies:

Case Study 1: Predicting Coffee Yields in Colombia

In Colombia, researchers have developed a predictive model that combines weather data, soil conditions, and crop management practices to forecast coffee yields at the farm level. By analyzing historical data and incorporating the latest advancements in machine learning, the model has been able to predict yields with a high degree of accuracy, enabling coffee growers to make more informed decisions about resource allocation, harvesting schedules, and market strategies.

Case Study 2: Optimizing Pest Management in Costa Rica

In Costa Rica, coffee growers have partnered with researchers to leverage predictive analytics for effective pest management. By integrating data on pest populations, weather patterns, and the efficacy of various control methods, the predictive model identifies the optimal timing and application of pesticides, reducing the environmental impact and improving the overall health of the coffee plants. This approach has led to a significant reduction in pest-related crop losses and a more sustainable approach to coffee farming.

Case Study 3: Forecasting Market Trends in Brazil

Brazil, the world’s largest producer and exporter of coffee, has been at the forefront of utilizing predictive analytics to navigate the complex coffee market. By analyzing data on global supply and demand, price fluctuations, and consumer preferences, Brazilian coffee growers are able to make more informed decisions about when to sell their crops, which varieties to focus on, and how to position their products in the global marketplace. This has enabled them to better manage their risk, capitalize on emerging opportunities, and ensure the long-term profitability of their operations.

The Road Ahead: Embracing the Future of Coffee Farming

As the world continues to grapple with the challenges of climate change, food security, and sustainable development, the role of predictive analytics in coffee farming has become increasingly crucial. By harnessing the power of data-driven insights, coffee growers can navigate the complexities of their industry with greater confidence, resilience, and adaptability.

To fully embrace the transformative potential of predictive analytics, coffee farming communities must be supported through the following initiatives:

  • Data infrastructure development: Investing in the collection, storage, and management of comprehensive data sets on weather patterns, pest populations, crop yields, and market trends. This will provide the foundation for robust predictive models.
  • Collaboration and knowledge sharing: Fostering partnerships between coffee growers, researchers, and technology experts to facilitate the exchange of knowledge and best practices, ensuring that the benefits of predictive analytics are widely disseminated.
  • Capacity building and training: Providing coffee growers with the necessary skills and tools to effectively utilize predictive analytics, empowering them to make informed decisions and adapt to the changing landscape of their industry.
  • Policy and regulatory support: Encouraging governments and policymakers to create enabling environments that support the adoption of predictive analytics in coffee farming, through incentives, subsidies, or regulations that promote sustainable and data-driven practices.

By embracing the power of predictive analytics, the coffee farming community can unlock a future of greater resilience, sustainability, and prosperity. As we navigate the challenges of the 21st century, the integration of cutting-edge technology with the timeless art of coffee cultivation holds the promise of revolutionizing the way we produce and consume this beloved beverage, ultimately enhancing human welfare and safeguarding the livelihoods of millions around the world.

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Crop Intelligence

Every crop, one table

Sowing window, duration, spacing, soil pH, water need, temperature, seed rate, yield and key pests — across 163 crops and plants, from cereals to medicinals. Indicative planning ranges for Indian conditions; varieties and regions vary.

163 crops shown
Agronomic reference for common Indian crops
Group Season Sowing Spacing Soil pH Temp °C Seed / ha Yield / ha Watch for
Rice Cereal Kharif Jun–Jul 120–150 20 × 15 cm 5.5–6.5 1200–1800 22–32 40–50 kg 4–6 t Stem borer, blast, BPH
Wheat Cereal Rabi Nov–Dec 120–150 22 cm rows 6.0–7.5 400–650 15–25 100–125 kg 4–5 t Yellow rust, aphid, termite
Maize Cereal Kharif · Rabi Jun–Jul, Oct–Nov 90–110 60 × 20 cm 5.5–7.5 500–800 21–30 18–20 kg 5–8 t Fall armyworm, stem borer
Barley Cereal Rabi Nov–Dec 110–130 22 cm rows 6.5–8.0 300–450 12–25 75–100 kg 3–4 t Aphid, yellow rust
Oats Cereal Rabi Oct–Nov 100–120 22 cm rows 5.5–7.0 350–500 15–25 80–100 kg 2.5–3.5 t Rust, aphid
Buckwheat Cereal Rabi Sep–Oct 75–90 30 × 10 cm 5.0–7.0 300–450 15–25 40–50 kg 1–1.5 t Aphid, leaf spot
Grain Amaranth Cereal Kharif · Rabi Jun–Jul, Oct 90–110 45 × 20 cm 5.5–7.5 300–450 20–30 2–3 kg 1–1.5 t Stem weevil, leaf webber
Sorghum (Jowar) Millet Kharif · Rabi Jun–Jul, Sep–Oct 100–120 45 × 15 cm 6.0–7.5 400–600 26–32 10–12 kg 2.5–4 t Shoot fly, midge, downy mildew
Pearl Millet (Bajra) Millet Kharif Jun–Jul 75–90 45 × 15 cm 6.5–7.8 350–500 25–35 4–5 kg 2–3 t Downy mildew, ergot
Finger Millet (Ragi) Millet Kharif Jun–Jul 100–120 30 × 10 cm 5.0–7.5 400–600 20–30 10–12 kg 2–3 t Blast, stem borer
Foxtail Millet Millet Kharif Jun–Jul 70–90 25 × 10 cm 5.5–7.0 250–400 20–30 8–10 kg 1.5–2 t Blast, shoot fly
Kodo Millet Millet Kharif Jun–Jul 100–120 25 × 10 cm 5.5–7.5 300–450 25–32 10–12 kg 1–1.5 t Head smut, shoot fly
Little Millet Millet Kharif Jun–Jul 70–90 25 × 10 cm 5.5–7.5 250–400 22–32 8–10 kg 0.8–1.2 t Shoot fly, grain smut
Barnyard Millet Millet Kharif Jun–Jul 75–90 25 × 10 cm 5.5–7.0 250–400 22–30 10–12 kg 1–1.5 t Grain smut, shoot fly
Proso Millet Millet Kharif · Zaid Jun–Jul, Feb 60–75 25 × 10 cm 5.5–7.5 200–350 20–30 10–12 kg 1–1.5 t Shoot fly, head smut
Chickpea (Gram) Pulse Rabi Oct–Nov 95–120 30 × 10 cm 6.0–8.0 250–400 15–25 75–100 kg 1.5–2.5 t Pod borer, wilt
Pigeon Pea (Tur) Pulse Kharif Jun–Jul 150–180 60 × 20 cm 6.0–7.5 400–600 20–30 12–15 kg 1.5–2 t Pod borer, wilt, sterility mosaic
Green Gram (Moong) Pulse Kharif · Zaid Jun–Jul, Mar–Apr 60–75 30 × 10 cm 6.2–7.2 250–350 25–35 15–20 kg 0.8–1.2 t Yellow mosaic, thrips
Black Gram (Urad) Pulse Kharif Jun–Jul 70–90 30 × 10 cm 6.0–7.5 250–400 25–35 15–20 kg 0.8–1.2 t Yellow mosaic, powdery mildew
Lentil (Masur) Pulse Rabi Oct–Nov 100–120 25 × 5 cm 6.0–7.5 200–350 15–25 30–40 kg 1–1.5 t Rust, wilt, aphid
Cowpea Pulse Kharif · Zaid Jun–Jul, Feb–Mar 70–90 45 × 15 cm 5.5–7.5 250–400 25–35 20–25 kg 1–1.5 t Aphid, pod borer
Field Pea Pulse Rabi Oct–Nov 100–130 30 × 10 cm 6.0–7.5 250–400 13–23 75–100 kg 1.5–2.5 t Powdery mildew, pod borer
Horse Gram Pulse Kharif · Rabi Aug–Sep 110–130 30 × 10 cm 5.0–7.5 200–300 20–30 25–30 kg 0.6–1 t Leaf spot, pod borer
Moth Bean Pulse Kharif Jul 70–90 30 × 10 cm 6.0–8.0 150–300 25–35 10–12 kg 0.5–0.8 t Yellow mosaic, jassid
Rajma (Kidney Bean) Pulse Rabi Oct–Nov 110–130 40 × 15 cm 5.5–6.5 300–450 15–25 80–100 kg 1.5–2 t Anthracnose, bean fly
Faba Bean Pulse Rabi Oct–Nov 120–150 45 × 15 cm 6.0–7.5 350–500 12–22 100–120 kg 2–3 t Chocolate spot, aphid
Lablab (Sem) Pulse Kharif Jun–Jul 110–140 60 × 30 cm 5.5–7.5 300–450 20–30 15–20 kg 1–1.5 t Pod borer, aphid
Cluster Bean (Guar) Pulse Kharif Jun–Jul 90–110 45 × 20 cm 7.0–8.5 250–400 25–35 15–20 kg 1–1.5 t Bacterial blight, jassid
Groundnut Oilseed Kharif Jun–Jul 100–130 30 × 10 cm 6.0–7.0 500–700 25–30 100–120 kg 2–2.5 t Leaf miner, tikka leaf spot
Mustard Oilseed Rabi Oct–Nov 110–140 30 × 10 cm 6.0–7.5 250–400 10–25 4–5 kg 1.5–2 t Aphid, white rust, alternaria
Rapeseed (Toria) Oilseed Rabi Sep–Oct 85–100 30 × 10 cm 6.0–7.5 200–350 10–25 4–5 kg 1–1.5 t Aphid, alternaria blight
Soybean Oilseed Kharif Jun–Jul 90–110 45 × 5 cm 6.0–7.5 450–700 20–30 65–75 kg 2–2.5 t Girdle beetle, yellow mosaic
Sunflower Oilseed Rabi · Zaid Oct–Nov, Jan–Feb 90–110 60 × 30 cm 6.5–8.0 400–600 20–28 8–10 kg 1.5–2 t Head borer, necrosis, downy mildew
Sesame (Til) Oilseed Kharif · Zaid Jun–Jul, Feb–Mar 80–95 30 × 15 cm 5.5–8.0 300–450 25–32 4–5 kg 0.6–1 t Phyllody, leaf webber
Castor Oilseed Kharif Jun–Aug 150–180 90 × 60 cm 5.5–7.5 500–700 20–30 5–8 kg 1.5–2.5 t Semilooper, capsule borer, wilt
Safflower Oilseed Rabi Oct–Nov 120–140 45 × 20 cm 6.0–8.0 250–400 15–25 10–15 kg 1–1.5 t Aphid, wilt, alternaria
Linseed Oilseed Rabi Oct–Nov 110–130 25 × 5 cm 6.0–7.5 250–400 15–25 25–30 kg 1–1.5 t Bud fly, rust, wilt
Niger Oilseed Kharif Jul–Aug 90–110 30 × 10 cm 5.5–7.0 300–450 18–28 5–6 kg 0.4–0.6 t Leaf spot, capsule fly
Cotton Fibre Kharif May–Jun 160–200 90 × 60 cm 6.0–8.0 700–1200 21–30 1.5–2.5 kg (Bt) 2–3 t seed cotton Pink bollworm, whitefly, jassid
Jute Fibre Kharif Mar–May 110–140 25 × 7 cm 6.0–7.5 500–750 24–35 5–8 kg 2.5–3 t fibre Stem rot, semilooper
Mesta (Kenaf) Fibre Kharif Apr–Jun 120–150 30 × 10 cm 6.0–7.5 450–700 22–32 12–15 kg 2–2.5 t fibre Stem rot, spiral borer
Sunn Hemp Fibre Kharif Jun–Jul 100–120 30 × 10 cm 5.5–7.5 350–500 22–32 25–30 kg 1.5–2 t fibre Hairy caterpillar, wilt
Sugarcane Plantation Perennial Oct–Nov, Feb–Mar 300–365 90–120 cm rows 6.5–7.5 1500–2500 20–35 35–40 k setts 80–100 t Early shoot borer, red rot, woolly aphid
Tea Plantation Perennial Jun–Aug (planting) 3–4 yr to pluck 1.2 × 0.75 m 4.5–5.5 2000–2500 18–30 13 k plants 2–3 t made tea Red spider mite, blister blight
Coffee Plantation Perennial Jun–Jul (planting) 3–4 yr to bear 2.5 × 2.5 m 6.0–6.5 1500–2000 15–28 1,600 plants 1–1.5 t clean White stem borer, leaf rust
Rubber Plantation Perennial Jun–Jul (planting) 6–7 yr to tap 4.9 × 4.9 m 4.5–6.0 2000–3000 25–34 420 plants 1.5–2 t dry rubber Abnormal leaf fall, pink disease
Coconut Plantation Perennial Jun–Jul (planting) 5–6 yr to bear 7.5 × 7.5 m 5.5–7.5 1300–2300 20–32 175 palms 80–120 nuts/palm Rhinoceros beetle, red palm weevil, root wilt
Arecanut Plantation Perennial Jun–Jul (planting) 5–7 yr to bear 2.7 × 2.7 m 5.5–7.0 1500–2500 20–32 1,350 palms 2–3 t dry kernel Koleroga, yellow leaf disease
Cashew Plantation Perennial Jun–Jul (planting) 3–4 yr to bear 7.5 × 7.5 m 5.5–7.0 800–1200 20–35 175 plants 1–1.5 t nuts Tea mosquito bug, stem borer
Cocoa Plantation Perennial Jun–Jul (planting) 3–4 yr to bear 2.7 × 2.7 m 5.5–7.0 1500–2000 20–30 1,100 plants 1–1.5 t dry bean Black pod, tea mosquito bug
Oil Palm Plantation Perennial Jun–Sep (planting) 3–4 yr to bear 9 m triangular 5.0–7.0 2000–2500 24–32 143 palms 20–25 t FFB Rhinoceros beetle, bud rot
Tobacco Plantation Rabi Sep–Oct 110–130 90 × 60 cm 5.5–6.5 400–600 20–30 250–300 g 1.5–2.5 t cured Aphid, budworm, black shank
Tomato Vegetable Year-round Jun–Jul, Oct–Nov, Jan–Feb 110–140 60 × 45 cm 6.0–7.0 400–600 20–27 250–400 g 25–40 t Fruit borer, leaf curl virus, early blight
Onion Vegetable Rabi · Kharif Oct–Nov, Jun–Jul 120–150 15 × 10 cm 6.0–7.5 350–550 13–25 8–10 kg 25–35 t Thrips, purple blotch, basal rot
Potato Vegetable Rabi Oct–Nov 90–120 60 × 20 cm 5.5–6.5 450–650 15–22 2.5–3 t tubers 25–35 t Late blight, aphid, tuber moth
Brinjal Vegetable Year-round Jun–Jul, Oct–Nov, Feb–Mar 120–150 60 × 60 cm 5.5–6.8 400–600 22–30 400–500 g 25–35 t Shoot & fruit borer, wilt
Okra (Bhindi) Vegetable Kharif · Zaid Jun–Jul, Feb–Mar 55–70 45 × 30 cm 6.0–6.8 350–500 24–32 8–10 kg 10–15 t Yellow vein mosaic, shoot borer, jassid
Chilli Vegetable Kharif · Rabi Jun–Jul, Oct–Nov 150–180 60 × 45 cm 6.0–7.0 500–700 20–30 1–1.5 kg 2–3 t dry Thrips, leaf curl, anthracnose
Capsicum Vegetable Rabi Sep–Oct 110–130 45 × 30 cm 6.0–6.8 400–600 18–27 750 g–1 kg 20–30 t Thrips, mites, anthracnose
Cabbage Vegetable Rabi Sep–Oct 90–120 45 × 45 cm 6.0–6.5 350–500 15–21 400–500 g 25–35 t Diamondback moth, black rot
Cauliflower Vegetable Rabi Sep–Oct 90–120 45 × 45 cm 6.0–7.0 350–500 15–20 400–500 g 20–30 t Diamondback moth, downy mildew
Broccoli Vegetable Rabi Sep–Oct 90–110 45 × 45 cm 6.0–7.0 350–500 15–20 400–500 g 12–18 t Aphid, diamondback moth
Knol-khol Vegetable Rabi Sep–Oct 60–80 30 × 20 cm 6.0–7.0 300–450 15–22 1–1.5 kg 20–25 t Aphid, black rot
Cucumber Vegetable Zaid · Kharif Feb–Mar, Jun–Jul 50–70 150 × 60 cm 6.0–7.0 350–500 20–30 2–3 kg 15–20 t Downy mildew, fruit fly, red pumpkin beetle
Bottle Gourd Vegetable Zaid · Kharif Feb–Mar, Jun–Jul 60–80 250 × 60 cm 6.0–7.0 400–550 22–32 3–5 kg 20–25 t Fruit fly, downy mildew
Bitter Gourd Vegetable Zaid · Kharif Feb–Mar, Jun–Jul 55–75 150 × 60 cm 6.0–6.7 350–500 24–32 4–5 kg 12–18 t Fruit fly, mosaic virus
Ridge Gourd Vegetable Zaid · Kharif Feb–Mar, Jun–Jul 55–75 200 × 60 cm 6.0–7.0 350–500 24–32 3–4 kg 12–16 t Fruit fly, powdery mildew
Sponge Gourd Vegetable Zaid · Kharif Feb–Mar, Jun–Jul 55–75 200 × 60 cm 6.0–7.0 350–500 24–32 3–4 kg 12–16 t Fruit fly, downy mildew
Ash Gourd Vegetable Kharif Jun–Jul 90–120 250 × 90 cm 6.0–7.0 400–600 24–32 4–6 kg 25–35 t Fruit fly, mosaic
Pumpkin Vegetable Zaid · Kharif Feb–Mar, Jun–Jul 90–120 250 × 60 cm 6.0–7.0 400–600 20–30 4–6 kg 20–30 t Red pumpkin beetle, powdery mildew
Watermelon Vegetable Zaid Jan–Mar 80–100 200 × 60 cm 6.0–7.0 400–600 24–32 2.5–3.5 kg 25–35 t Fruit fly, anthracnose, wilt
Muskmelon Vegetable Zaid Jan–Mar 75–95 150 × 60 cm 6.0–7.0 350–550 24–32 2–2.5 kg 15–25 t Fruit fly, downy mildew
French Bean Vegetable Rabi · Zaid Oct–Nov, Feb 60–80 45 × 15 cm 5.5–6.5 300–450 16–24 60–80 kg 8–12 t Anthracnose, bean fly
Garden Pea Vegetable Rabi Oct–Nov 90–110 30 × 10 cm 6.0–7.5 300–450 13–22 80–100 kg 8–12 t Powdery mildew, pod borer
Radish Vegetable Rabi · Year-round Sep–Jan 40–60 30 × 10 cm 6.0–7.0 250–400 15–25 10–12 kg 20–30 t Aphid, white rust
Carrot Vegetable Rabi Aug–Nov 90–110 30 × 8 cm 6.0–7.0 350–500 15–22 5–6 kg 20–30 t Leaf blight, aphid, nematode
Beetroot Vegetable Rabi Sep–Nov 80–100 30 × 10 cm 6.0–7.5 300–450 15–24 7–8 kg 20–30 t Leaf spot, aphid
Turnip Vegetable Rabi Sep–Nov 55–75 30 × 10 cm 6.0–7.0 250–400 13–22 4–5 kg 20–25 t Aphid, white rust
Spinach (Palak) Vegetable Rabi · Year-round Sep–Feb 35–50 25 × 5 cm 6.0–7.5 200–350 15–25 25–30 kg 12–18 t Leaf spot, aphid
Fenugreek (Methi) Vegetable Rabi Oct–Nov 40–60 25 × 5 cm 6.0–7.5 200–350 15–25 25–30 kg 8–12 t Powdery mildew, aphid
Amaranth (Leafy) Vegetable Year-round Feb–Sep 30–45 20 × 10 cm 6.0–7.5 200–350 22–32 2–3 kg 10–15 t Leaf webber, stem weevil
Lettuce Vegetable Rabi Sep–Nov 60–80 30 × 30 cm 6.0–7.0 250–400 13–20 400–500 g 15–20 t Aphid, downy mildew
Celery Vegetable Rabi Sep–Oct 110–130 40 × 25 cm 6.0–7.0 400–600 15–22 2–3 kg 20–25 t Leaf spot, aphid
Sweet Potato Vegetable Kharif · Rabi Jun–Jul, Oct–Nov 100–130 60 × 20 cm 5.5–6.8 400–600 21–30 35–40 k vines 20–25 t Weevil, leaf curl
Colocasia (Arbi) Vegetable Kharif Jun–Jul 150–180 60 × 45 cm 5.5–7.0 800–1200 21–32 2–2.5 t corms 15–20 t Leaf blight, aphid
Elephant Foot Yam Vegetable Kharif Apr–May 210–240 90 × 90 cm 5.5–7.0 800–1200 25–35 10–12 t corms 30–40 t Collar rot, mosaic
Drumstick (Moringa) Vegetable Perennial Jun–Jul 180–240 2.5 × 2.5 m 6.0–7.5 500–800 25–35 600 g 25–30 t pods Hairy caterpillar, fruit fly
Banana Fruit Perennial Jun–Jul, Feb–Mar 300–365 1.8 × 1.8 m 6.0–7.5 1200–2000 20–35 3,000 suckers 50–70 t Sigatoka, panama wilt, weevil
Mango Fruit Perennial Jul–Aug (planting) 4–5 yr to bear 10 × 10 m 5.5–7.5 700–1000 24–30 100 grafts 8–12 t Hopper, powdery mildew, fruit fly
Papaya Fruit Year-round Feb–Mar, Jun–Jul 270–300 1.8 × 1.8 m 6.0–7.0 1000–1500 22–32 250–300 g 40–60 t Ring spot virus, mealybug
Guava Fruit Perennial Jul–Aug (planting) 2–3 yr to bear 6 × 6 m 6.0–7.5 800–1000 23–30 270 plants 20–25 t Fruit fly, wilt, anthracnose
Sweet Orange Fruit Perennial Jul–Aug (planting) 4–5 yr to bear 6 × 6 m 6.0–7.5 900–1200 20–32 270 plants 20–25 t Citrus canker, leaf miner, psylla
Mandarin (Kinnow) Fruit Perennial Jul–Aug (planting) 4–5 yr to bear 6 × 6 m 6.0–7.5 900–1200 18–30 270 plants 20–30 t Citrus canker, greening, leaf miner
Lemon Fruit Perennial Jul–Aug (planting) 3–4 yr to bear 5 × 5 m 6.0–7.5 800–1100 20–32 400 plants 15–20 t Canker, leaf miner, gummosis
Grapes Fruit Perennial Jan–Feb (planting) 2–3 yr to bear 3 × 2 m 6.5–7.5 600–900 15–35 1,650 vines 20–30 t Downy mildew, powdery mildew, thrips
Pomegranate Fruit Perennial Jul–Aug (planting) 2–3 yr to bear 5 × 5 m 6.5–7.5 600–900 20–35 400 plants 15–20 t Bacterial blight, fruit borer
Apple Fruit Perennial Dec–Jan (planting) 4–6 yr to bear 5 × 5 m 5.5–6.5 800–1200 10–24 400 plants 15–20 t Scab, codling moth, woolly aphid
Pear Fruit Perennial Dec–Jan (planting) 4–6 yr to bear 6 × 6 m 6.0–7.0 800–1100 10–25 270 plants 15–20 t Scab, leaf blight
Peach Fruit Perennial Dec–Jan (planting) 3–4 yr to bear 5 × 5 m 6.0–7.0 700–1000 12–26 400 plants 10–15 t Leaf curl, fruit fly
Plum Fruit Perennial Dec–Jan (planting) 3–4 yr to bear 5 × 5 m 6.0–7.0 700–1000 12–26 400 plants 10–15 t Brown rot, aphid
Litchi Fruit Perennial Jun–Sep (planting) 5–7 yr to bear 8 × 8 m 5.5–7.0 1200–1600 20–35 156 plants 8–12 t Fruit borer, mite, fruit cracking
Sapota (Chikoo) Fruit Perennial Jun–Jul (planting) 4–5 yr to bear 8 × 8 m 6.0–8.0 900–1300 20–32 156 plants 15–20 t Bud borer, leaf spot
Custard Apple Fruit Perennial Jun–Jul (planting) 3–4 yr to bear 5 × 5 m 6.5–7.5 600–800 23–32 400 plants 8–10 t Mealybug, anthracnose
Jackfruit Fruit Perennial Jun–Jul (planting) 5–7 yr to bear 10 × 10 m 6.0–7.5 1000–1500 22–35 100 plants 15–20 t Fruit rot, shoot borer
Pineapple Fruit Perennial Jul–Sep 450–540 60 × 30 cm 5.0–6.0 1000–1500 22–32 43 k suckers 50–60 t Mealybug, heart rot
Ber (Indian Jujube) Fruit Perennial Jul–Aug (planting) 2–3 yr to bear 6 × 6 m 6.0–8.5 400–600 20–35 270 plants 15–20 t Fruit fly, powdery mildew
Amla Fruit Perennial Jul–Aug (planting) 4–5 yr to bear 8 × 8 m 6.0–8.0 600–900 20–35 156 plants 10–15 t Rust, bark eating caterpillar
Fig Fruit Perennial Jun–Jul (planting) 2–3 yr to bear 5 × 5 m 6.0–7.5 600–800 20–32 400 plants 10–15 t Rust, stem borer
Date Palm Fruit Perennial Feb–Mar (planting) 5–7 yr to bear 8 × 8 m 7.0–8.5 1200–1800 25–40 156 palms 10–15 t Graphiola leaf spot, borer
Strawberry Fruit Rabi Sep–Oct 90–120 30 × 30 cm 5.5–6.5 400–600 15–25 55 k runners 10–15 t Grey mould, mite, leaf spot
Kiwi Fruit Perennial Dec–Jan (planting) 4–5 yr to bear 4 × 5 m 5.5–7.0 900–1200 10–25 500 vines 12–18 t Root rot, leaf spot
Avocado Fruit Perennial Jun–Jul (planting) 4–5 yr to bear 8 × 8 m 5.5–6.5 1000–1400 20–30 156 plants 8–12 t Anthracnose, root rot
Dragon Fruit Fruit Perennial Jun–Jul (planting) 18–24 mo to bear 3 × 3 m 5.5–7.0 600–900 20–35 1,100 posts 10–15 t Stem canker, mealybug
Almond Nut Perennial Dec–Jan (planting) 4–5 yr to bear 6 × 6 m 6.0–7.5 700–1000 10–28 270 plants 1.5–2 t Leaf blight, hairy caterpillar
Walnut Nut Perennial Dec–Jan (planting) 6–8 yr to bear 10 × 10 m 6.0–7.5 800–1200 10–25 100 plants 2–3 t Anthracnose, walnut blight
Pecan Nut Perennial Dec–Jan (planting) 6–8 yr to bear 10 × 10 m 6.0–7.0 900–1300 15–30 100 plants 1.5–2.5 t Scab, aphid, shuck decline
Pistachio Nut Perennial Jan–Feb (planting) 6–8 yr to bear 6 × 6 m 7.0–8.0 600–900 15–35 270 plants 1.5–2 t Alternaria blight, twig borer
Hazelnut Nut Perennial Dec–Jan (planting) 4–5 yr to bear 5 × 5 m 6.0–7.0 700–1000 10–24 400 plants 1.5–2 t Blight, filbert weevil
Turmeric Spice Kharif May–Jun 240–270 30 × 20 cm 5.5–7.5 1200–1500 20–30 2–2.5 t rhizome 25–30 t fresh Rhizome rot, leaf spot, shoot borer
Ginger Spice Kharif Apr–May 210–240 25 × 20 cm 5.5–6.5 1300–1800 20–30 1.5–2 t rhizome 15–20 t fresh Soft rot, bacterial wilt
Coriander Spice Rabi Oct–Nov 90–110 30 × 15 cm 6.0–8.0 250–400 15–25 10–15 kg 1–1.5 t Powdery mildew, aphid, wilt
Cumin Spice Rabi Nov–Dec 100–120 30 × 10 cm 6.8–8.3 250–350 15–25 12–15 kg 0.6–0.8 t Wilt, blight, aphid
Fennel Spice Rabi Oct–Nov 140–160 45 × 20 cm 6.5–8.0 350–500 15–25 8–10 kg 1.5–2 t Aphid, blight, wilt
Fenugreek (Seed) Spice Rabi Oct–Nov 120–140 25 × 10 cm 6.0–7.5 250–400 15–25 20–25 kg 1.2–1.8 t Powdery mildew, root rot
Garlic Spice Rabi Oct–Nov 130–160 15 × 10 cm 6.0–7.0 350–500 12–24 500–600 kg cloves 8–12 t Thrips, purple blotch, basal rot
Black Pepper Spice Perennial Jun–Jul (planting) 3–4 yr to bear 3 × 3 m 5.5–6.5 2000–3000 20–32 1,100 vines 2–3 t dry Quick wilt, pollu beetle
Cardamom (Small) Spice Perennial Jun–Jul (planting) 2–3 yr to bear 2 × 2 m 5.0–6.5 1500–2500 15–28 2,500 plants 150–250 kg dry Katte virus, thrips, rot
Cardamom (Large) Spice Perennial Jun–Jul (planting) 3 yr to bear 1.5 × 1.5 m 5.0–6.5 2000–3000 10–25 4,400 plants 200–300 kg dry Chirke, foorkey virus
Clove Spice Perennial Jun–Jul (planting) 6–8 yr to bear 6 × 6 m 5.5–7.0 1500–2500 20–30 270 plants 1–2 kg/tree Leaf rot, seedling wilt
Cinnamon Spice Perennial Jun–Jul (planting) 3–4 yr to harvest 2 × 2 m 5.0–7.0 1500–2500 20–30 2,500 plants 150–200 kg quill Leaf spot, stripe canker
Nutmeg Spice Perennial Jun–Jul (planting) 6–8 yr to bear 8 × 8 m 5.5–7.0 1500–2500 20–32 156 plants 500–1000 fruits/tree Fruit rot, die-back
Ajwain Spice Rabi Oct–Nov 140–160 45 × 20 cm 6.5–8.0 250–400 15–25 3–4 kg 0.8–1.2 t Powdery mildew, aphid
Dill Spice Rabi Oct–Nov 110–130 30 × 15 cm 6.0–7.5 250–400 15–25 8–10 kg 0.8–1 t Aphid, powdery mildew
Tamarind Spice Perennial Jun–Jul (planting) 6–8 yr to bear 10 × 10 m 6.0–8.0 700–1000 22–35 100 plants 150–200 kg/tree Fruit borer, scale
Vanilla Spice Perennial Jun–Jul (planting) 3 yr to bear 2 × 1.5 m 6.0–7.0 1500–2500 21–32 1,600 vines 300–500 kg green Bean rot, stem rot
Marigold Flower Year-round Jun, Sep, Jan 60–90 45 × 30 cm 6.0–7.5 350–500 18–30 1–1.5 kg 15–20 t Leaf spot, thrips, red spider mite
Rose Flower Perennial Sep–Oct (planting) 90–120 to flower 60 × 45 cm 6.0–7.0 600–900 15–28 37 k plants 8–10 lakh blooms Black spot, powdery mildew, thrips
Jasmine Flower Perennial Jun–Jul (planting) 1–2 yr to bear 1.5 × 1.5 m 6.5–7.5 700–1000 20–32 4,400 plants 8–12 t Bud worm, leaf webber, gall mite
Chrysanthemum Flower Rabi Jun–Jul 110–130 30 × 30 cm 6.0–7.0 400–600 15–25 1.1 lakh cuttings 15–20 t Leaf spot, aphid, thrips
Tuberose Flower Kharif Mar–Apr 90–120 30 × 20 cm 6.5–7.5 500–700 20–30 2–2.5 lakh bulbs 15–20 t spikes Aphid, thrips, stem rot
Gladiolus Flower Rabi Sep–Nov 90–120 30 × 20 cm 6.0–7.0 400–600 15–25 2–2.5 lakh corms 2–2.5 lakh spikes Fusarium wilt, thrips
Gerbera Flower Protected Year-round 90–100 to flower 30 × 30 cm 5.5–6.5 Drip fertigation 18–26 60 k plants 200–250 stems/m² Powdery mildew, whitefly, mite
Carnation Flower Protected Year-round 120–150 to flower 15 × 15 cm 6.0–7.0 Drip fertigation 13–22 2.5 lakh plants 250–300 stems/m² Fusarium wilt, thrips, mite
Orchid Flower Protected Year-round 18–24 mo to bear 30 × 30 cm 5.5–6.5 Misting 20–30 40 k plants 4–6 spikes/plant Black rot, scale, thrips
Anthurium Flower Protected Year-round 12–18 mo to bear 30 × 30 cm 5.5–6.5 Misting 18–28 60 k plants 6–8 blooms/plant Bacterial blight, mite
Aloe Vera Medicinal Perennial Jun–Jul 240–300 60 × 45 cm 6.0–8.0 400–600 20–35 25 k suckers 30–40 t leaf Leaf spot, mealybug
Ashwagandha Medicinal Kharif Jun–Jul 150–180 30 × 10 cm 6.5–8.0 300–450 20–32 10–12 kg 0.6–0.8 t root Leaf spot, aphid
Tulsi (Holy Basil) Medicinal Kharif Apr–May 90–110 45 × 45 cm 6.0–7.5 400–600 20–32 300–400 g 10–12 t herb Leaf roller, powdery mildew
Lemongrass Medicinal Perennial Jun–Jul 90 per cut 60 × 45 cm 5.5–7.5 800–1200 20–32 35 k slips 15–20 t herb Leaf blight, rust
Mentha (Menthol Mint) Medicinal Zaid Jan–Feb 110–130 45 × 30 cm 6.0–7.5 600–900 20–30 400–500 kg suckers 100–150 kg oil Leaf spot, hairy caterpillar
Stevia Medicinal Perennial Feb–Mar 90 per cut 45 × 30 cm 6.0–7.5 600–900 18–30 90 k plants 3–4 t dry leaf Leaf spot, wilt
Isabgol (Psyllium) Medicinal Rabi Nov–Dec 110–130 30 × 10 cm 7.0–8.5 250–350 15–25 4–5 kg 0.8–1.2 t Downy mildew, aphid
Senna Medicinal Kharif · Rabi Jul, Oct 110–130 45 × 30 cm 7.0–8.5 250–400 20–35 15–20 kg 1–1.5 t leaf Leaf spot, pod borer
Safed Musli Medicinal Kharif Jun–Jul 180–210 30 × 20 cm 6.0–7.5 600–900 20–32 5–6 q roots 2–2.5 t fresh root Root rot, leaf spot
Vetiver (Khus) Medicinal Perennial Jun–Jul 540–600 60 × 45 cm 5.5–8.0 800–1200 20–35 35 k slips 20–25 kg oil Root borer, leaf blight
Patchouli Medicinal Perennial Jun–Jul 150 per cut 60 × 60 cm 5.5–7.0 1500–2000 22–30 28 k cuttings 40–60 kg oil Leaf blight, wilt, nematode
Berseem Fodder Rabi Oct–Nov 50 per cut Broadcast 6.5–7.5 500–700 15–25 20–25 kg 80–100 t green Root rot, stem rot
Lucerne (Alfalfa) Fodder Perennial Oct–Nov 45 per cut 30 cm rows 6.5–7.5 600–900 15–30 12–15 kg 80–100 t green Wilt, aphid
Napier (Hybrid) Fodder Perennial Jun–Jul 60 per cut 90 × 60 cm 5.5–7.5 1000–1500 25–35 20 k slips 200–250 t green Leaf blight, stem borer
Fodder Maize Fodder Kharif · Zaid Jun–Jul, Feb 60–70 30 × 15 cm 6.0–7.5 400–600 21–30 50–60 kg 40–50 t green Stem borer, leaf blight
Fodder Sorghum Fodder Kharif Jun–Jul 60–75 30 × 10 cm 6.0–7.5 350–500 25–32 35–40 kg 40–50 t green Shoot fly, anthracnose
Fodder Cowpea Fodder Kharif Jun–Jul 55–70 30 × 10 cm 5.5–7.5 300–450 25–35 35–40 kg 25–30 t green Aphid, leaf spot
Oats (Fodder) Fodder Rabi Oct–Nov 60–70 25 cm rows 5.5–7.0 350–500 15–25 80–100 kg 35–45 t green Rust, aphid

Figures are planning ranges, not prescriptions. Confirm against your local KVK or state agricultural university before committing an acre to them.

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