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Juanulloa Climate Stress Modeling in Texas: Expert Guide, Best Practices & Pro Tips

6 min read April 30, 2026

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Juanulloa Climate Stress Modeling in Texas: Expert Guide, Best Practices & Pro Tips

In the face of an ever-changing climate, agricultural communities in Texas are grappling with the pressing challenge of understanding and mitigating the impact of environmental stressors on crop yields and overall human welfare. One critical tool in this endeavor is the Juanulloa climate stress modeling framework, a powerful analytical approach that enables farmers, policymakers, and researchers to navigate the complexities of climate-related risks.

This comprehensive guide will delve into the intricacies of Juanulloa climate stress modeling, offering expert insights, best practices, and pro tips to help you unlock the full potential of this invaluable resource. Whether you’re a seasoned agricultural professional or a newcomer to the field, this guide will equip you with the knowledge and strategies to effectively leverage Juanulloa for the betterment of your community and the environment.

Understanding Juanulloa Climate Stress Modeling For more on this, see our related guide: Kinnikinnick Climate Stress Modeling in Texas: Expert Guide, Best Practices & Pro Tips.

The Juanulloa climate stress modeling framework is a sophisticated analytical tool that combines historical weather data, crop growth models, and advanced statistical techniques to assess the potential impact of climate-related stressors on agricultural systems. By considering factors such as temperature, precipitation, and soil moisture, Juanulloa enables users to simulate various climate scenarios and their implications for crop yields, water resources, and overall food security.

At the core of the Juanulloa model is the integration of plant physiology and environmental data, allowing for a nuanced understanding of how crops respond to changes in their growing conditions. This approach empowers agricultural professionals to make informed decisions, implement targeted adaptation strategies, and enhance the resilience of their operations in the face of a shifting climate.

Expert Guide: Leveraging Juanulloa for Climate Stress Modeling in Texas For more on this, see our related guide: Kentucky Coffee Tree Climate Stress Modeling in Texas: Expert Guide, Best Practices & Pro Tips.

To effectively utilize the Juanulloa climate stress modeling framework in the context of Texas agriculture, consider the following expert guidance:

1. Understand the Regional Climate Dynamics

Texas is known for its diverse and often unpredictable climate, ranging from the arid conditions of the Panhandle to the subtropical environments of the Gulf Coast. Familiarize yourself with the unique weather patterns, seasonal variations, and long-term trends that characterize your specific region. This contextual knowledge will be crucial in interpreting the Juanulloa model outputs and tailoring your adaptation strategies accordingly.

2. Collect and Curate High-Quality Data For more on this, see our related guide: Japanese Forest Grass Climate Stress Modeling in Brazil: Expert Guide, Best Practices & Pro Tips.

The accuracy and reliability of the Juanulloa model are heavily dependent on the quality of the input data. Ensure that you have access to comprehensive, up-to-date weather records, soil surveys, and crop yield statistics for your target area. Collaborate with local meteorological agencies, agricultural extension services, and research institutions to gather the most relevant and reliable data sources.

3. Understand the Juanulloa Model Structure and Assumptions

Take the time to familiarize yourself with the underlying structure and assumptions of the Juanulloa model. This includes understanding the specific crop growth algorithms, the way the model handles climate variability, and the limitations or uncertainties inherent in the modeling approach. By grasping the technical foundations of Juanulloa, you’ll be better equipped to interpret the model outputs and draw meaningful conclusions.

4. Engage in Collaborative Modeling Efforts

Leverage the expertise of researchers, policymakers, and fellow agricultural professionals by participating in collaborative modeling efforts. Juanulloa is a complex tool, and engaging with a multidisciplinary team can provide valuable insights, facilitate knowledge sharing, and ensure that the model is being used to its full potential.

5. Communicate Findings Effectively

As you work with the Juanulloa model, prioritize clear and effective communication of your findings. Develop intuitive visualizations, such as heat maps and scenario comparisons, to help stakeholders, including farmers, industry leaders, and policymakers, understand the implications of your analysis. This will enable more informed decision-making and facilitate the implementation of targeted adaptation strategies.

Best Practices for Juanulloa Climate Stress Modeling

To optimize the use of Juanulloa in your Texas-based agricultural operations, consider the following best practices:

1. Incorporate Local Knowledge and Expertise

Leverage the valuable insights and on-the-ground experience of local farmers, extension agents, and industry experts. Their intimate understanding of the region’s unique environmental characteristics and agricultural challenges can inform the parameterization of the Juanulloa model and enhance the relevance of its outputs.

2. Utilize Ensemble Modeling Approaches

Rather than relying on a single Juanulloa model run, consider employing an ensemble modeling approach. By running the model multiple times with varied inputs and assumptions, you can gain a more robust understanding of the range of potential climate-related risks and their probabilities.

3. Prioritize Scenario-based Planning

Use the Juanulloa model to explore a variety of climate scenarios, from best-case to worst-case, to develop comprehensive adaptation strategies. This will help you identify the most vulnerable crops, regions, and practices, and enable you to proactively implement measures to mitigate the impacts of climate-related stressors.

4. Integrate with Other Decision Support Tools

Complement the Juanulloa climate stress modeling framework with other decision support tools, such as water management systems, crop insurance programs, and supply chain optimization platforms. By integrating these resources, you can build a more holistic and informed approach to managing climate-related risks in your agricultural operations.

5. Continuously Monitor and Refine the Model

As climate patterns and agricultural practices evolve over time, it’s crucial to regularly review and update the Juanulloa model to ensure its continued relevance and accuracy. Incorporate new data sources, validate the model’s predictions against observed outcomes, and make necessary adjustments to maintain the model’s effectiveness in supporting your decision-making processes.

Pro Tips for Maximizing the Impact of Juanulloa Climate Stress Modeling

To further enhance the value of Juanulloa climate stress modeling in your Texas-based agricultural endeavors, consider the following pro tips:

  • Leverage Interdisciplinary Collaboration: Engage with experts from diverse fields, such as climatology, agronomy, hydrology, and economics, to ensure a comprehensive and holistic approach to climate risk management.
  • Advocate for Improved Data Infrastructure: Work with policymakers and funding agencies to invest in the development of robust, interoperable data systems that can seamlessly feed into the Juanulloa modeling framework, enhancing its accuracy and responsiveness.
  • Explore Novel Modeling Techniques: Stay informed about the latest advancements in climate modeling, machine learning, and data analytics, and consider integrating these emerging techniques into your Juanulloa-based analyses to unlock new insights and innovative solutions.
  • Facilitate Knowledge Sharing and Capacity Building: Develop training programs, workshops, and knowledge-sharing platforms to empower farmers, extension agents, and other stakeholders to effectively utilize the Juanulloa model and apply its findings in their decision-making processes.
  • Advocate for Policy and Regulatory Changes: Leverage the insights gained from Juanulloa climate stress modeling to inform and influence policymakers, advocating for the implementation of robust climate adaptation and mitigation strategies that support the long-term sustainability of Texas agriculture.

By embracing the Juanulloa climate stress modeling framework and following the expert guidance, best practices, and pro tips outlined in this comprehensive guide, you can unlock the full potential of this invaluable tool in addressing the pressing challenges faced by the agricultural community in Texas. Through informed decision-making, collaborative efforts, and a commitment to continuous improvement, you can help safeguard the long-term resilience and productivity of Texas’ agricultural systems, ensuring the well-being of both the environment and the people it sustains. For more on this, see our related guide: Japanese Pieris Climate Stress Modeling in Brazil: Expert Guide, Best Practices & Pro Tips.

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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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