Cotton fell to 61.55 USd/Lbs on December 2, 2025, down 2.03% from the previous day. Over the past month, Cotton's price has fallen 6.28%, and is down 13.31% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cotton - values, historical data, forecasts and news - updated on December of 2025.

This statistic shows the upland spot cotton price per pound in the United States from 1990 to 2018. In calendar year 2017, the average spot price per one pound of upland cotton was about 86.4 U.S. cents.

Graph and download economic data for Global price of Cotton (PCOTTINDUSDM) from Jan 1990 to Jun 2025 about cotton, World, and price.

Cotton prices in , September, 2025 For that commodity indicator, we provide data from January 1960 to September 2025. The average value during that period was 1.48 USD per kilogram with a minimum of 0.6 USD per kilogram in August 1969 and a maximum of 5.06 USD per kilogram in March 2011. | TheGlobalEconomy.com

In the 2020 calendar year, the global average price of cotton - from a selection of the principal upland cottons - stood at **** U.S. cents per pound. The global price of cotton was at its peak in the 2011 crop year, with an average price of *** cents per pound. Cotton in the U.S. The average farm price in the United States received by cotton growers, has been growing in the past few years. The United States is the leading global cotton exporter, and is among the leading cotton producers worldwide after India and China. As of 2017/2018, the United States produced about ** percent of cotton globally. Cottonseeds market Worldwide cottonseed production amounted to about **** million metric tons in 2018/2019, decreasing from around ** million metric tons in the previous year. In that year, India and China were by far the main cottonseed producers worldwide, followed by Pakistan and Brazil.

NCDEX: Spot Price: Cotton: Rajkot: First Session data was reported at 24,917.550 INR/Bale in 01 Dec 2025. This records an increase from the previous number of 24,871.200 INR/Bale for 28 Nov 2025. NCDEX: Spot Price: Cotton: Rajkot: First Session data is updated daily, averaging 25,515.800 INR/Bale from Jan 2024 (Median) to 01 Dec 2025, with 448 observations. The data reached an all-time high of 29,611.850 INR/Bale in 14 Mar 2024 and a record low of 24,827.900 INR/Bale in 20 Nov 2025. NCDEX: Spot Price: Cotton: Rajkot: First Session data remains active status in CEIC and is reported by National Commodity & Derivatives Exchange Limited. The data is categorized under India Premium Database’s Price – Table IN.PB: Commodity Spot Price: National Commodity & Derivatives Exchange Limited.

NCDEX: Spot Price: Cotton: Rajkot: Second Session data was reported at 26,034.550 INR/Bale in 16 May 2025. This records a decrease from the previous number of 26,086.700 INR/Bale for 15 May 2025. NCDEX: Spot Price: Cotton: Rajkot: Second Session data is updated daily, averaging 27,316.700 INR/Bale from Jan 2023 (Median) to 16 May 2025, with 548 observations. The data reached an all-time high of 30,289.350 INR/Bale in 10 Apr 2023 and a record low of 25,198.900 INR/Bale in 05 Mar 2025. NCDEX: Spot Price: Cotton: Rajkot: Second Session data remains active status in CEIC and is reported by National Commodity & Derivatives Exchange Limited. The data is categorized under India Premium Database’s Price – Table IN.PB001: Commodities Spot Price: National Commodity & Derivatives Exchange Limited.

View monthly updates and historical trends for US Cotton, Cottonseed Price Received. from United States. Source: US Department of Agriculture. Track econo…

NCDEX: Spot Price: Cotton Seed Oilcake: Rajkot: First Session data was reported at 3,230.000 INR/Quintal in 14 May 2025. This records an increase from the previous number of 3,220.000 INR/Quintal for 13 May 2025. NCDEX: Spot Price: Cotton Seed Oilcake: Rajkot: First Session data is updated daily, averaging 2,960.000 INR/Quintal from Jan 2024 (Median) to 14 May 2025, with 317 observations. The data reached an all-time high of 4,030.000 INR/Quintal in 22 Oct 2024 and a record low of 2,510.000 INR/Quintal in 13 Feb 2024. NCDEX: Spot Price: Cotton Seed Oilcake: Rajkot: First Session data remains active status in CEIC and is reported by National Commodity & Derivatives Exchange Limited. The data is categorized under India Premium Database’s Price – Table IN.PB001: Commodities Spot Price: National Commodity & Derivatives Exchange Limited.

A Training Dataset for Deep Neural Network Model Recognition of Common Cotton Diseases provides strong support for cotton disease monitoring and prevention and control. This dataset contains images of cotton plants under different disease states, covering five phenotypic state images of cotton plants, including anthracnose, bacterial angular spot, brown spot, wilt, and health. A total of 816 images of cotton with anthracnose, 919 images of bacterial angular spot, 917 images of brown spot, 538 images of fusarium wilt, and 264 images of healthy status were collected. The images under each disease state have corresponding file name prefixes for easy data retrieval and use.

ABSTRACT Ramularia leaf spot (RLS) is the major cotton disease in Brazil and one of the main causes of crop yield reduction. The disease causes defoliation reduces photosynthetic capacity and causes premature opening of bolls. Due to the impact of RLS on the production of Brazilian cotton and the lack of scientific publications investigating the disease, the present work aims to evaluate the efficiency of fungicides in controlling disease and their impact on yield and fiber quality. Three field experiments were carried out during the 2014/2015 and 2016/2017 seasons in Planaltina, Federal District and Cristalina, Goiás. Experiments followed a randomized complete block design (4 blocks) and treatments consisted of the application of fungicides, plus a non-treated plot. The fungicide applications began preventively and were repeated every 14 days until six sprays had been completed. Severity of RLS was assessed and used to calculate the area under disease progress curve (AUDPC). Yield and cotton fiber quality were also evaluated. All fungicides had reduced AUDPC and obtained higher cotton yields in relation to the non-treated plot. Strobilurin-group fungicides (azoxystrobin, pyraclostrobin and picoxystrobin) showed low effectiveness when sprayed alone. The demethylation inhibitor fungicides (difenoconazole, epoxiconazol, tetraconazol and metconazole) were more effective than the strobilurins. The highest efficiency rates were achieved by application of pyraclostrobin + fluxapyroxad, pyraclostrobin + epoxiconazole + fluxapyroxad and fentin hydroxide. Disease severity affected cotton yield, causing losses from 14.8% to 31.7%. Resultant reductions in cotton fiber quality negatively affect the micronaire composition, altering the length, strength and uniformity of fibers.

Usage of this work is restricted to activities that adhere to Shariah. Any use inconsistent with Shariah principles is strictly prohibited.

Here's a comprehensive summary of your new plant disease dataset:

📊 Dataset Summary

Dataset Name: Plant Disease Classification Dataset

Total Classes: 71 classes

• 70 Known Disease Classes: Each containing 400 images
• 1 Unknown Disease Class: Containing 500 images from 15 different plant species

Total Images: ~28,500 images

• Training Set: ~19,950 images (70%)
• Validation Set: ~4,275 images (15%)
• Test Set: ~4,275 images (15%)

🌱 Plant Species Covered

The dataset includes 20+ different plant species: 1. Apple 2. Blueberry 3. Cherry 4. Corn (Maize) 5. Grape 6. Orange 7. Peach 8. Pepper (Bell) 9. Potato 10. Raspberry 11. Soybean 12. Strawberry 13. Tomato 14. Mango 15. Pumpkin 16. Rice 17. Cotton 18. Sugarcane 19. Jackfruit 20. Cauliflower 21. Unknown class includes: Banana, Bean, Wheat, Watermelon, Pineapple, Papaya, Jujube, Guava

🦠 Disease Categories Covered

Fungal Diseases:

• Apple scab, Black rot, Cedar apple rust
• Powdery mildew (multiple plants)
• Early blight, Late blight
• Leaf blast, Brown spot
• Mosaic disease
• Rust diseases
• Septoria leaf spot
• And more...

Bacterial Diseases:

• Bacterial spot
• Bacterial blight
• Bacterial canker

Viral Diseases:

• Tomato Yellow Leaf Curl Virus
• Tomato mosaic virus
• Mosaic diseases

Pest-Related Issues:

• Spider mites
• Aphids
• Cutting weevil
• Gall midge
• Hispa

Physiological Disorders:

• Citrus greening (Haunglongbing)

Healthy Classes:

• Healthy leaf images for each plant species

📁 Dataset Structure

plant_disease_dataset.zip
├── train/ (70% - ~19,950 images)
│  ├── Apple scab (Apple)/
│  ├── Black rot (Apple)/
│  ├── Early blight (Tomato)/
│  ├── Bacterial Canker (Mango)/
│  ├── Unknown Disease/
│  └── ... (71 total classes)
├── val/ (15% - ~4,275 images)
│  └── ... (same 71 classes)
└── test/ (15% - ~4,275 images)
  └── ... (same 71 classes)

📚 Dataset Sources

Source 1: New Plant Diseases Dataset (Augmented)

Kaggle Link: /kaggle/input/new-plant-diseases-dataset/

Classes included (37 classes): 1. Apple - Apple scab 2. Apple - Black rot 3. Apple - Cedar apple rust 4. Apple - healthy 5. Blueberry - healthy 6. Cherry (including sour) - Powdery mildew 7. Cherry (including sour) - healthy 8. Corn (maize) - Cercospora leaf spot Gray leaf spot 9. Corn (maize) - Common rust 10. Corn (maize) - Northern Leaf Blight 11. Corn (maize) - healthy 12. Grape - Black rot 13. Grape - Esca (Black Measles) 14. Grape - Leaf blight (Isariopsis Leaf Spot) 15. Grape - healthy 16. Orange - Haunglongbing (Citrus greening) 17. Peach - Bacterial spot 18. Peach - healthy 19. Pepper, bell - Bacterial spot 20. Pepper, bell - healthy 21. Potato - Early blight 22. Potato - Late blight 23. Potato - healthy 24. Raspberry - healthy 25. Soybean - healthy 26. Strawberry - Leaf scorch 27. Strawberry - healthy 28. Tomato - Bacterial spot 29. Tomato - Early blight 30. Tomato - Late blight 31. Tomato - Leaf Mold 32. Tomato - Septoria leaf spot 33. Tomato - Spider mites Two-spotted spider mite 34. Tomato - Target Spot 35. Tomato - Tomato Yellow Leaf Curl Virus 36. Tomato - Tomato mosaic virus 37. Tomato - healthy

Images per class: 400 images each

Source 2: Mango Leaf Disease Dataset

Kaggle Link: /kaggle/input/mango-leaf-disease-dataset/

Classes included (8 classes): 1. Mango - Anthracnose 2. Mango - Bacterial Canker 3. Mango - Cutting Weevil 4. Mango - Die Back 5. Mango - Gall Midge 6. Mango - Healthy 7. Mango - Powdery Mildew 8. Mango - Sooty Mould

Images per class: 400 images each

Source 3: Pumpkin Leaf Diseases Dataset from Bangladesh

Kaggle Link: /kaggle/input/pumpkin-leaf-diseases-dataset-from-bangladesh/

Classes included (5 classes): 1. Pumpkin - Bacterial Leaf Spot 2. Pumpkin - Downy Mildew 3. Pumpkin - Healthy Leaf 4. Pumpkin - Mosaic Disease 5. Pumpkin - Powdery Mildew

Images per class: 400 images each

Source 4: Rice Leafs Dataset

Kaggle Link: /kaggle/input/riceleafs/

Classes included (4 classes): 1. Rice - BrownSpot 2. Rice - Healthy 3. Rice - Hispa 4. Rice - LeafBlast

Images per class: 400 images each

Source 5: Cotton Leaf Disease Dataset

Kaggle Link: /kaggle/input/cotton-leaf-disease-dataset/

Classes included (5 classes): 1. Cotton - Aphids 2. Cotton - Bacterial Blight 3. Cotton - Healthy 4. Cotton - Powdery Mildew 5. Cotton - Target spot

Images per class: 400 images each

Source 6: Sugarcane Plant Diseases Dataset

Kaggle Link: /kaggle/input/sugarcane-plant-diseases-dataset/

Classes included (6 classes): 1. Sugarcane - ...

This dataset is recreated using offline augmentation from the original dataset. The original dataset can be found here.

List of diseases - Aphids - Army worm - Bacterial Blight - Powdery Mildew - Target spot

It also includes healthy leaf dataset to compare with the diseased plant.

It mainly focus on the disease which occurs only on leaves and it does not have any reference images for diseases on stem, buds, flowers and boll.

The Wholesale Price Index of cotton yarn across India during financial year 2024 was around ***. The price index value increased by about ** percent from the base financial year of 2012. An overall increase in the index value was seen over the years from financial year 2013 in the south Asian country.

Dataset

This dataset was created by Abu Taher

Contents

This dataset comprises high-resolution images of cotton leaves categorized by disease type and health condition. It is structured into two parts: the Original Dataset and the Augmented Dataset.

Original Dataset
The original set contains real-world images of cotton leaves affected by various diseases, alongside healthy specimens. The images are labeled into the following five classes:

• Alternaria Leaf Spot: 173 images
• Bacterial Blight: 218 images
• Fusarium Wilt: 337 images
• Healthy Leaf: 333 images
• Verticillium Wilt: 312 images

Augmented Dataset
To enhance diversity and improve model robustness, data augmentation techniques were applied to the original images. The resulting augmented dataset includes:

• aug_Alternaria_Leaf: 987 images
• aug_Bacterial_Blight: 1027 images
• aug_Fusarium_Wilt: 957 images
• aug_Healthy_Leaf: 1015 images
• aug_Verticillium_Wilt: 977 images

This dataset is well-suited for research in plant pathology, machine learning, and image classification tasks related to agriculture and crop health monitoring.

NCDEX: Spot Price: Cotton Seed Oilcake: Kadi: First Session data was reported at 2,864.600 INR/Quintal in 01 Dec 2025. This records a decrease from the previous number of 2,902.850 INR/Quintal for 28 Nov 2025. NCDEX: Spot Price: Cotton Seed Oilcake: Kadi: First Session data is updated daily, averaging 2,643.400 INR/Quintal from Jan 2024 (Median) to 01 Dec 2025, with 458 observations. The data reached an all-time high of 3,494.250 INR/Quintal in 31 Oct 2025 and a record low of 2,442.450 INR/Quintal in 13 Feb 2024. NCDEX: Spot Price: Cotton Seed Oilcake: Kadi: First Session data remains active status in CEIC and is reported by National Commodity & Derivatives Exchange Limited. The data is categorized under India Premium Database’s Price – Table IN.PB: Commodity Spot Price: National Commodity & Derivatives Exchange Limited.

Although conventional hybrid breeding has paved the way for improving cotton production and other properties, it is undoubtedly time and labor consuming, while the cultivation of male sterile line can fix the problem. Here, we induced male sterile mutants by simultaneously editing three cotton EXCESS MICROSPOROCYTES1 (GhEMS1) genes by CRISPR/Cas9. Notably, the GhEMS1 genes are homologous to AtEMS1 genes, which inhibit the production of middle layer and tapetum cells as well, leading to male sterility in cotton. Interestingly, there are necrosis-like dark spots on the surface of the anthers of GhEMS1s mutants, which is different from AtEMS1 mutant whose anther surface is clean and smooth, suggesting that the function of EMS1 gene has not been uncovered yet. Moreover, we have detected mutations in GhEMS1 genes from T0 to T3 mutant plants, which had necrosis-like dark spots as well, indicating that the mutation of the three GhEMS1 genes could be stably inherited. Dynamic transcriptomes showed plant hormone pathway and anther development genetic network were differential expression in mutant and wild-type anthers. And the lower level of IAA content in the mutant anthers than that in the wild type at four anther developmental stages may be the reason for the male sterility. This study not only facilitates the exploration of the basic research of cotton male sterile lines, but also provides germplasms for accelerating the hybrid breeding in cotton.

Abstract Target spot is a disease that has caused serious damage to cotton crops. This study was carried out to examine if different cotton genotypes, plant heights and fungicide treatments can be used as tools of an integrated control methods of target spot. The experiment was carried out in the 2014/15 crop season, in cerrado biome of Chapadão do Sul - MS, Brazil. It was used a randomized block design in a 2 × 3 × 3 factorial arrangement with four replicates. The factors were two plant heights (1 and 1.5 m), three cultivars (FMT 701, FM 975, and FM 944), and three fungicide treatments (control, FT1, and FT2). Fungicide treatments consisted of sequential applications of different fungicides of the triazole, strobilurin, and carboxamide groups. Cultivar FM 944 showed lower susceptibility to target spot. The shorter plants exhibited lower disease severity. The fungicides pyraclostrobin + fluxapyroxad and trifloxystrobin + prothioconazole reduced the severity of target spot. Cultivar FM 975 had the highest yield. A higher yield was obtained in the upper stratum than in the lower stratum of the plant.

Information of the identified 55 DDP spots. (XLSX 16 kb)