Colorado potato beetle: instructions for use — Garden

How to breed Corado from the Colorado potato beetle

Among a wide variety of insecticides, one must also be able to choose a truly effective, safe and inexpensive means. It is very important to follow the instructions that are attached to the drug. Even the best drug will not give good results if used improperly. Many gardeners choose a product called «Corado». In this article we will see how to dilute and use this drug. And also learn some features of the substance.

Characteristics of the drug

The developers have worked well on the composition of the tool. The main active ingredient is imidacloprid. This is a highly effective high-speed component that is contained in the preparation in large quantities. It is he who is responsible for the destruction of the Colorado beetles. In addition, the product contains the avermectin complex, which is obtained from the fungi found in the soil.

Attention! This drug is dangerous for bees.

The substance is Packed in small ampoules and vials, from 1 to 20 ml. Due to the high content of toxic substances the drug has a rather pronounced unpleasant odor. Belongs to the third class of danger to human health. This means that during use it is necessary to adhere to safety rules.

In pests do not occur depending on the components of the drug. It can be used regularly in the same area. But still it is advised to change the tool after three times. The new drug must have a different main component.

«Corado» is able to penetrate to beetles in several ways (intestinal, systemic and contact). Thanks to this, you can completely get rid of pests in the garden in a short time. The drug has a triple effect:

  1. Kills adult individuals.
  2. Destroys the larvae.
  3. Reduces the ability of eggs to reproduce.

This substance fights not only with the Colorado potato beetle, but also with other pests of cultivated plants. For example, it helps to get rid of spider mites, potato bugs and aphids. The drug remains effective regardless of weather conditions. And this can not but rejoice, because you usually have to re-process bushes after prolonged rains.

Important! After processing, the components affect the nervous system of the beetles and reduce their performance. Within 2 or 3 days the pests completely die.

Manufacturers do not recommend the use of insecticide with other drugs. This will only harm the plants and reduce the effectiveness of the procedure. Substances contained in the tool, accumulate and continue to operate for 4 weeks after treatment. During this time, all pests die, and their reappearance is unlikely.

Preparation and application of the solution

The effectiveness of the drug depends on compliance with all the rules described in the instructions. It is necessary to consider the size of the area during the preparation of the mixture. Dilute «Corado» is advised with water at room temperature. For 1 ampoule of the drug will need 5 liters of fluid. After mixing the components, the solution is poured into the barrel of the sprayer and proceed to the treatment of the bushes. As a toxic agent, it is necessary to protect the skin and respiratory tract.

Attention! The last processing of potatoes should be carried out no later than 3 weeks before harvest.

The solution can be sprayed or sprayed. The best time for treatment is morning or late evening. Apply the drug should be careful not to miss the bushes. How the pests die quickly depends on the correct application. It is better not to use «Corado» during a strong wind or rain.

In the instructions for use «Korado» from the Colorado potato beetle indicated that the drug can not be combined with other insecticides. Also, during treatment with the agent, fertilizing and other procedures using chemicals are not allowed. One ampoule of the drug is enough to treat weaving beds with potatoes. The following procedures are performed as necessary.

Safety engineering

This remedy for the Colorado potato beetle can not be attributed to highly dangerous drugs. But it is still necessary to follow certain rules:

  • dilute and use the drug should be only in gloves and protective clothing;
  • for breeding «Corado» can not use soda;
  • eating food, drinking water and smoking during the procedure is strictly prohibited;
  • after treatment, you must rinse the nose and throat, as well as take a shower;
  • If the product has got on the skin or mucous membranes, immediately rinse these areas with plenty of water;
  • to eliminate poisoning with poison, you must drink activated charcoal.

Attention! The drug can not be used if there is an apiary near.


«Corado» from the Colorado potato beetle has established itself as an excellent tool for pests. If you need to get rid of adult beetles, larvae and eggs in a short jump, then this substance is for you. With it you can fight with other pests of agricultural crops. It is not surprising that many gardeners prefer this particular remedy.

Eggplant Vera: we grow a variety that is not afraid of cooling

Thanks to the tireless work of domestic breeders, the cultivation of heat-loving eggplants in open ground can now be carried out by residents of regions with a cool climate. Variety Vera grows and bears fruit well in the Urals, in Siberia and even in the Far East. But to get a stable harvest you need to know some tricks that we will be happy to share with you.

History and description of Vera eggplant

Eggplant is a universal vegetable. It can be fried, stewed, pickled, baked. And the famous «raw» eggplant caviar? Surely every mistress has her own secret to cooking this wonderful snack. Vera eggplant is ideal for all types of cooking. This variety was created for cultivation in open ground in garden plots and household plots. Vera eggplant is also recommended for small farms.

Eggplant Vera is a domestic variety included in the State Register in 2001. Although eggplant is a heat-loving plant, the tolerance regions for Vera are not in warm areas. Vera is considered a cold-resistant variety recommended for cultivation in the Ural, West Siberian and Far Eastern regions.

Vera eggplant — an excellent choice for small personal plots


Vera eggplant bushes can be called high — 73 — 75 cm, but compact at the same time. And this is not the limit, sometimes the height of the plant can exceed 1 m. The bushiness of the bush is average. Leaves of medium size, with notched edges, green-purple hue. A cup of flower is covered with rare spikes. The usual weight of Vera eggplant is 125 — 181 g, less often larger fruits grow, weighing up to 300 g. The shape of the fruit is pear-shaped. The skin is purple, glossy. The pulp is whitish, dense, without voids, without bitterness. Taste is excellent.

Eggplant Vera — video

Grade characteristics

  1. Eggplant Vera belongs to the early ripening varieties — from the appearance of full germination to the moment of maturity, from 100 to 118 days pass. Technical ripeness occurs in August — early September.
  2. Resistance to cold weather is one of the advantages of the variety, which allows it to be grown in an unstable climate in open ground.
  3. Fruiting is stable. But you cannot name the high yield — 0.9 — 1.2 kg per m². The maximum figure is 2.9 kg.
  4. Commercial quality of fruits is high. The output of marketable products is excellent — 90 — 100%.

Grade Features

Vera is distinguished from many other varieties by its good cold resistance and stable yield. But productivity has low indicators, which does not allow the use of the variety on an industrial scale, such as, for example, Diamond, bringing up to 7 kg m².

Vera eggplant has a stable yield

Advantages and disadvantages — table

Advantages disadvantages
Early harvest Inadequate yield allows you to grow
grade only in private gardens or small
Stable fruiting
Excellent commercial quality of fruits and
high yield of marketable products
Cold resistance

Landing Features

Vera eggplants can be grown in two ways — seed and seedlings. Directly in the soil, seeds are sown only in regions with a warm climate. During the growing season, the eggplant has time to develop and bring a crop. In cold regions where summers are short and cool, you need to grow a variety only in seedlings.

Sown seeds for seedlings in February or March. It all depends on the climate of the region. Before direct disembarkation into the ground, about 2 months should pass. Direct sowing of Vera eggplant seeds in open ground is carried out in mid-April or early May. Sowing is carried out when the soil warms up to 13 ° C.

In regions with unstable climates, it is best to plant a variety on a warm bed. The soil in it warms up quickly enough, and shelter on the box is easy to pull. Such a structure can easily be made with your own hands.

Warm beds with female hands — video

It is quite easy to grow Vera eggplants, it is no more difficult than growing, for example, tomatoes. But the culture has some features, knowing which you can get a great harvest.


Vera eggplant is a hygrophilous plant; the soil on the bed should be in a moderately moist state. Overdrying is not permissible. It will lead to shedding of flowers and ovaries, but the fruits will not grow to the right size and the flesh will become wooden. Waterlogging can turn into diseases of the root system.

Water must be pre-heated in the sun with water. From cold eggplants begin to hurt and stop growing.

  1. Before flowering, eggplant bushes are watered once every 6 to 8 days at the rate of 12 liters per 1 m². In hot weather, the frequency doubles.
  2. When flowering begins, and then the fruiting period begins — the variety Vera needs to be watered 2 times a week, with the above amount of water.

Remember that weather conditions often affect your watering schedule. If in hot weather the frequency of humidification can increase, then in the presence of precipitation and cooling it will decrease.

To plant seedlings successfully rooted, it is watered often — every 3 days.

In order to economically consume water, it is beneficial to water-loving culture by drip method

Top dressing

Eggplant Vera absorbs a lot of nutrients from the soil, especially during fruiting. The culture is most responsive to organics, but the plant can not do without mineral fertilizing.

  1. The first time top dressing is made in 15 — 20 days after transplanting seedlings into the ground. When grown in seedlings, they are fertilized after final thinning. On 1 m² of soil make:
    • ammonium nitrate 10 g;
    • potash fertilizers — 3-5 g.
      • Instead of these fertilizers, you can use Ammofosku, Nitrofosku or Kristallin — 25 g per 1 m².
  2. Every 3 weeks, top dressing is repeated. But the amount of fertilizer already increased by 1.5, and in poor soils by 2 times.

Organic Fertilizer Application — Table

Application Period What to feed How to make fertilizer Application rate
Build-up period
green mass
Dung grass
Shredded leaves of dandelion, plantain and chopped
nettle is placed in a 100-liter barrel. To 6 kg of raw materials
add a bucket of mullein and 10 tbsp. l ashes. Fill with water
mix and stand for a week.
1 liter of solution per 1 bush.
Fruiting period Bird solution
For 100 liters of water 1 bucket of bird droppings in a porridge
condition, 2 cups Nitrofoski. Insist 5 days. Before
mix well using.
The application rate is 12 liters per 1 m².

If the soil is nutritious, then you need not to overdo it with the addition of fertilizing, otherwise the plant will begin to «fatten» — that is, to build up green mass to the detriment of fruiting.

Vera eggplant is very fond of natural top dressing, which is easy to prepare on your own


If the height of the Vera eggplant does not exceed 70 cm, and the plant itself has a strong stem, then you can do without support. The variety is distinguished by a compact bush, therefore, to form more fruits, the plant is formed into 3 to 5 stems, but at the same time, no more than 10 ovaries must be left. Usually stepsons are not a big problem of the variety, but if they appear, remove them without regret, as well as leaves growing below the first branch.

To stimulate the formation of ovaries, use the drug Bud or Ovary. To attract bees for pollination, the eggplant is sprayed with a weak sugar or honey solution.

How to shape eggplant — video

Diseases and Pests

During the growing season, due to improper care, Vera eggplant can suffer from various diseases. Most often, the elimination of errors (normalization of watering, feeding, elimination of thickening) corrects the situation and restores the normal development of the plant. But sometimes you have to resort to more radical methods. In addition to diseases, insects can harm eggplant. The most insidious of them is the Colorado potato beetle.


Most often, this dangerous disease manifests itself at the stage of development of seedlings. But the plants transplanted into the open ground are not immune from this danger. The stem at the base begins to darken, thins and becomes covered with a grayish coating. The plant gradually fades. If the disease penetrates the roots, the bush will die. Ideal conditions for the development of the disease is increased humidity, acidic soil, temperature changes.

To prevent fungal infection, the seeds are disinfected in preparation for sowing. You also need to remember that:

  • before planting eggplant, acid soil is leached;
  • nitrogen-containing fertilizers can cause a problem, so do not get carried away with them;
  • crop rotation significantly reduces the risk of developing this disease.

If the black leg could not be prevented, urgently need to remove the affected plants along with the root lump and destroy. The hole is treated with a 1% solution of copper sulfate, or one of the biological products — Alirin, Glyocladin, Gamair or Trichocin. Apply according to instructions.

The black leg can hit eggplant in seedlings

Late blight

This is the most common nightshade disease. First, the leaves are affected. Brownish-red spots appear on them, bordered by a light green stripe. Further, the disease captures the stems and fruits. Depending on weather conditions, late blight is manifested in different ways. In dry weather, the affected leaves dry out and quickly fall off. In raw — they are covered on the underside with a whitish coating. On peduncles with fruits brown-brown blurry spots appear. Morning mists, high humidity, thickened plantings and temperature spikes are the most favorable factors for the development of the disease.

To fight late blight, the following drugs are used:

  • Quadris;
  • Consento;
  • Anthracol;
  • a solution of 1% Bordeaux fluid;
  • 0.2% solution of copper sulfate.

In order to prevent the need to comply with agricultural technology. Alternative methods also come to the rescue.

  • after harvesting, all plant residues should be collected from the garden. If late blight is noticed on tomatoes or potatoes, treat the eggplants with the infusion of garlic — chop 200 g of the product, pour 3 liters of water and insist for several days. Before use, strain the tincture and dilute with clean water 1: 1;
  • you can spray the bushes with milk diluted with water in a ratio of 1: 1.

Blight affects eggplant leaves

Colorado beetle

This pest is familiar to many gardeners. The most dangerous are the larvae of the Colorado potato beetle. It is they who are capable in the blink of an eye to destroy foliage, flowers and ovary, leaving only the stem from the eggplant. Of course, you can forget about the crop.

There are many ways to deal with the Colorado potato beetle. Very often the beetle is collected manually, but, as a rule, these actions do not bring the desired result. It is best to turn to folk methods or purchase chemicals in specialized stores. In addition, there are plants whose smell is unpleasant to the pest.

Folk remedies

Folk remedies are effective when the Colorado potato beetle is just beginning to appear and its quantity is too small.

  1. In 10 l of water add a glass of chopped garlic, stand for 4 days, filter and dissolve a little laundry soap in the infusion.
  2. A decoction of horsetail and dandelion. Shredded plants (1 glass each) pour 10 liters of boiling water and insist 2 days.
  3. 50 g of hot pepper pour 5 l of boiling water. Boil for 2 hours over low heat. Cool, filter and add 50 g of laundry soap.
  4. 1/2 capacity is filled with poplar leaves. Pour to the top with water and insist 4 days. Filter.
  5. Each eggplant bush is sprinkled with wood ash.

Alternative methods can be used against the Colorado potato beetle, but they are effective for a small amount of insect.


Chemicals are used when the pest has already multiplied. The following drugs are considered most effective.

But it should be remembered that the Colorado potato beetle easily adapts to chemicals. Every year you need to use new tools, so you should follow the news.

When the Colorado potato beetle began to breed, only chemicals would save

Strong odor plants

The Colorado potato beetle does not like strongly smelling plants — marigolds, marigold, wormwood, celery. It is them that can be planted between eggplant bushes or laid out between rows.

Marigolds will not only decorate the garden, but also scare away the Colorado potato beetle

Vera eggplant reviews

I planted Vera’s eggplant in the garden under the arches with lutrasil. It ripens early. About 70-80 cm high. There were not many fruits on the bush, but large ones. There are seeds left. I will plant this year.



I grew in OG Veru and Bagheera. Bagheera bought this year, I liked it.

Hope AA


wrote about this variety, my germination was not very good, but there were a lot of seeds in the package, one bush came across a re-sorting. All plain in the photo — Vera. To taste normal, not bitter, there were not too many seeds either.



Vera eggplants are unpretentious. Therefore, to grow a healthy vegetable in the garden is not difficult. But how nice it is to observe the ripening fruits. And while Vera’s eggplant ripens in the garden, the housewives have time to look for unusual recipes for its preparation.

Taboo from the Colorado potato beetle — characteristics and rules of use

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Detection of potato beetle damage using remote sensing from small unmanned aircraft systems

E. Raymond Hunt, 1 Silvia I. Rondon 2

1 USDA-ARS Beltsville Agricultural Research Center (United States)
2 Oregon State University (United States)




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Colorado potato beetle (CPB) adults and larvae devour leaves of potato and other solanaceous crops and weeds, and may quickly develop resistance to pesticides. With early detection of CPB damage, more options are available for precision integrated pest management, which reduces the amount of pesticides applied in a field. Remote sensing with small unmanned aircraft systems (sUAS) has potential for CPB detection because low flight altitudes allow image acquisition at very high spatial resolution. A five-band multispectral sensor and up-looking incident light sensor were mounted on a six-rotor sUAS, which was flown at altitudes of 60 and 30 m in June 2014. Plants went from visibly undamaged to having some damage in just 1 day. Whole-plot normalized difference vegetation index (NDVI) and the number of pixels classified as damaged ( 0.70 ≤ NDVI ≤ 0.80 ) were not correlated with visible CPB damage ranked from least to most. Area of CPB damage estimated using object-based image analysis was highly correlated to the visual ranking of damage. Furthermore, plant height calculated using structure-from-motion point clouds was related to CPB damage, but this method required extensive operator intervention for success. Object-based image analysis has potential for early detection based on high spatial resolution sUAS remote sensing.


Potatoes (Solanum tuberosum L.) were the first crop for which insecticides were routinely used and currently require more pesticides than other major crops. 1 , 2 One of the most important insect pests of potato is the Colorado potato beetle (CPB) Leptinotarsa decemlineata (Coleoptera: Chrysomelidae); larvae and adults are voracious leaf eaters that can rapidly defoliate a field of potatoes. 3 CPB quickly develops resistance to insecticides leading to an unsustainable cycle of crop failure and spread of resistant populations. 4 , 5 Integrated pest management (IPM) is a collection of control methods, including insecticides, that considers the whole system to keep insect damage to acceptable levels. 2 , 5 – 7 Early detection allows a larger range of IPM options, reducing the amount of insecticides applied for control.

Insect defoliation of a crop canopy may be remotely sensed by the reduction of leaf area or biomass as measured by spectral vegetation indices, such as the normalized difference vegetation index (NDVI). 8 , 9 Early detection of CPB damage using satellites depends on overpass frequency, cloud cover, sensor pixel size, and the delivery speed of data to the user. Pixel size is an important determinant for early detection because there has to be more visible foliar damage when using larger pixels. Small unmanned aircraft systems (sUAS) acquire imagery at low altitudes for higher spatial resolution and may be ideal for early detection of damage from insects. 10 Frequent monitoring of crops during the growing season with unmanned aircraft was envisioned long before the technology evolved to make it practical. 11 – 13

Aerial photographs and remotely sensed imagery with very small pixel sizes have usually been interpreted visually, but this becomes burdensome with large numbers of images. Scale-invariant feature transform is used to mosaic a large number of images (stitching). 14 Two methods for analysis of the stitched images have gained attention over the past 15 years. First is object-based image analysis (OBIA), which capitalizes on high-spatial resolution to group adjacent pixels with similar spectral and textural properties for classification of land-cover objects. 15 – 18 Second is photogrammetric structure from motion (SfM), which is used to generate image point clouds and digital surface elevations from large numbers of overlapping images. 19 – 21 The resulting digital elevation data are used to generate orthomosaic images. Furthermore, the SfM point clouds can also be used to determine plant height for estimating growth and biomass. 22 – 25

In contrast to spatial variation in soils, which is the basis for precision agriculture, insect emergence from the soil or immigration from other fields is essentially random. This increases the dependence on early detection of insect damage with remote sensing and automated processing. In order to evaluate possible algorithms for sUAS remote sensing, we set up an experiment in which CPB were added to irrigated potatoes in order to vary the amount of infestation during the tuber initiation and bulking growth stages. Ten flights were conducted over 15 days in June 2014 to acquire imagery just before and just after canopy damage from CPB became visible. The objective was to compare traditional spectral indices, OBIA classification, and SfM plant height at the time when CPB damage just becomes visible.


The study was conducted at Oregon State University’s Hermiston Agricultural Research and Extension Center (HAREC) located in Hermiston, Oregon (45.82021°N and 119.28364°W, 180-m elevation). July is the hottest month with average high and low temperatures of 32°C and 14°C, respectively. The average annual precipitation is 266 mm, with 51 mm during the growing season. The soil type is an Adkins Sandy Loam (coarse-loamy, mixed, superactive, mesic Xeric Haplocalcids).

Small plots of potatoes (Solanum tuberosum L. “Ranger Russet”) were established on April 22, 2014, using a randomized block design with four treatments and four replications [Fig. 1(a)]. Plot size was 9.2 m × 2.6 m (three rows wide). No insecticides were applied onto the plants; one application of acetamiprid (Assail 30SG, United Phosphorus, Inc., King of Prussia, Pennsylvania) was made on the soil around the experiment to control CPB migrating from surrounding areas. Irrigation, herbicide application, and fungicide application followed commercial practices. 26 Fertilization was about 450 kg / ha nitrogen, 310 kg / ha phosphorus, 220 kg / ha potassium, and 80 kg / ha sulfur.

Fig. 1

(a) Plot layout for additional CPB on “Ranger Russet” potatoes. Treatments consisted of placing additional CPB per plant: control, 0; low, 1.5; medium, 4.5; and high, 7.5. (b) Color-infrared orthomosaic image from flights on June 23, 2014, at 60-m altitude above ground level. (c) Color-infrared orthomosaic from flights on June 24, 2014, at 60-m altitude.

CPB were collected early in the season and maintained on potato plants in bug dorms (Bioquip, Inc., Rancho Dominguez, California). Before introduction into the colony, beetles were checked for the presence of parasitoids. The colony was maintained at a temperature of 20 ± 5 ° C and 50% to 60% relative humidity. Potato plants were changed twice a week and bug dorms were changed weekly.

On June 9, 2014, different numbers of CPB were placed in each plot: low, 1.5 CPB/plant; medium, 4.5 CPB/plant; and high, 7.5 CPB/plant [Fig. 1(a)]. The control treatment had no additional CPB; any larvae or adults found in the control plots either emerged from the soil or migrated from other plots. There was no apparent plant damage on June 23, 2014 [Fig. 1(b)]. However, on the next day, June 24, 2014, visual plant damage was obvious [Fig. 1(c)]. The first CPB population survey was conducted on July 2, 2014; 10 plants per plot were randomly selected and inspected for eggs, larvae, and adults.

All sUAS flights were conducted under a Certificate of Authorization from the United States Federal Aviation Administration. Ten flights of a “Spreading Wings” S800 hexacopter (DJI, Shenzhen, Guangdong, China) were made over the plots between 15:00 and 16:00 hours from June 10, 2014 to June 24, 2014. The sUAS was flown using an autopilot, first at 60 m and then at 30-m altitude above ground level. The sensor was a six-channel Mini Multi Camera Array (mini-MCA, Tetracam, Inc., Chatworth, California). Five channels were narrow bands (center wavelength ± 10 nm ) in the blue (470 nm), green (550 nm), red (660 nm), red-edge (710 nm), and near-infrared (NIR, 810 nm). The sixth channel was used for an upward-looking incident light sensor. 27 The focal length of the mini-MCA was 9.6 mm, so ground sample distances (pixel sizes on the ground) were about 30 and 15 mm for 60- and 30-m altitude, respectively.

Because the objective was to compare imagery before and after detection of CPB damage, only the flights on June 23, 2014 and June 24, 2014 were analyzed. If there were any previsual-damage symptoms, it was assumed that the symptoms would be most detectable in the June 23, 2014 images. The images acquired on both days were initially processed using Tetracam’s PixelWrench-2 software to reformat the 10-bit raw imagery to 16-bit Tagged Interchange File Format (*.tif) images. Then, PixelWrench-2 was used to ratio the digital numbers from the first five channels with digital numbers from the incident light sensor channel to calculate apparent surface reflectance from 0% to 100%, scaled from 0 to 65535, respectively. Agisoft Photoscan Pro (version 1.2.6, Agisoft LLC, St. Petersburg, Russia) was used to create five-band orthomosaic images and three-dimensional digital surface elevation models from photogrammetric point clouds. Unfortunately, ground control points were not established, so the orthomosaic images were created using only the sUAS log files. Furthermore, because mini-MCA lenses were not well calibrated, the result was a pronounced curvature of the surface elevation model generated from the point cloud after optimization of camera parameters. 28

The Environment for Visualizing Images (ENVI) version 5.3 (Harris Geospatial Solutions, Boulder, Colorado) was used to calculate various spectral vegetation indices. Results from the different indices were highly correlated. Therefore, only NDVI was used:

The ENVI 5.3 Feature Extraction module was used for OBIA classification. 29 First, the NDVI image was segmented into objects by determining gradients of NDVI within a kernel of 9 × 9 pixels . 30 The Watershed transform 31 was used for initial segmentation of the image. Based on the cumulative frequency distribution of NDVI gradients (potential object boundaries), the scale parameter was used to define the steepness of the NDVI gradient for selecting object boundaries. 32 Based on the cumulative frequency distribution of object mean NDVI, the merge parameter was used to determine if adjacent objects are sufficiently similar to be combined. 32 Both the scale and merge parameters were set to 70, in order to define fewer objects and to aggressively merge adjacent objects. Then, a series of spectral, spatial, and textural variables was calculated for each image object, including: mean NDVI, maximum NDVI, minimum NDVI, texture range, texture mean, texture variance, and texture entropy. Using two plots for training areas (102 and 302), we developed simple classification rules using object mean NDVI to classify the orthomosaics into three classes: healthy plants, CPB damage, and soil. Classification rules using object maximum NDVI, minimum NDVI, texture range, or texture variance produced similar classifications; creating rules with several variables did not improve the classifications.

The 16 plots were visually ranked from the least damaged to the most damaged. Side-by-side comparisons of both the color infrared and true-color images were made for all plots individually to determine if one plot had more canopy damage than the next plot. Ties were assigned the average ranking of the two plots. Spearman rank correlation coefficients ( r s ) were calculated and t -tests were used to determine significance. 33

Results and Discussion

There was no indication of potato leaf loss or plant damage from the images acquired on June 23, 2014 [Fig. 1(b)]. There were visibly damaged areas in all plots on the very next day, June 24, 2014 [Fig. 1(c)]. From the visual ranking, the least impacted plots were 201 and 401, and the plot with the most damage was 102 [Fig. 1(c)]. The number of CPB found during the census and the visual ranking of damage was not related to the treatments of artificially applied CPB, based on a Kruskal–Wallace one-way analysis of variance test 33 (data not shown). Furthermore, the CPB population was not related to the rank of visual damage [Fig. 2(a)] with r s = 0.046 . Whole-plot average NDVI was not related ( r s = 0.23 ) to the visual ranking of damage [Fig. 2(b)]. Plot NDVI was high for all plots, at both 30- and 60-m altitudes, with NDVI occurring within a narrow range of 0.84 to 0.89 [Fig. 2(b)]. High NDVI was expected because on June 22, 2013, the measured canopy leaf area index was ≥ 3.0 m 2 m − 2 and remotely sensed NDVI was ≥ 0.85 with the same potato variety. 34

Fig. 2

CPB damage per plot was ranked from least to most. (a) The number of CPB counted on ten plants on July 2, 2014. (b) Whole-plot-mean NDVI on June 24, 2014, from an altitude of 30 m. The Spearman rank correlation coefficients were not significant.

For undamaged areas, pixel-based NDVI showed a much larger range from 0.78 to 0.93 (Fig. 3), which was not apparent in the whole-plot averages [Fig. 2(b)]. Canopy damage in the color-infrared images [Fig. 1(c)] corresponded to areas of low NDVI [Fig. 3(b)]. The cumulative frequency distribution of pixel NDVI from both altitudes, 30 and 60 m, was used to determine that a threshold of NDVI ≤ 0.8 was a good criterion for distinguishing between damaged and undamaged plants within a plot. An NDVI of ≤ 0.7 was a good criterion for separating vegetation from cultivated bare soil.

Fig. 3

NDVI on (a) June 23, 2014 and (b) June 24, 2014, from orthomosaic images acquired at 30-m above ground level. Plots are aligned the same as in Fig. 1(a).

The number of pixels classified as damaged from the NDVI threshold was not related ( r s = 0.27 ) to the visual ranking of CPB damage [Fig. 4(a)]. The ranking of visual damage was highly correlated ( r s = 0.85 , t = 6.08 with 14 degrees of freedom) to the plot area classified as CPB damaged by feature extraction [Fig. 4(b)]. However, for most plots, the total plot area classified as damaged was less for feature extraction than for the NDVI threshold, because some pixels with low NDVI were included in image objects that had higher mean NDVI. The difference between pixel classifications using an NDVI threshold [Fig. 4(a)] and using objects from NDVI feature extraction [Fig. 4(b)] may not be important depending on the overall goals. If the goal was to detect any plant damage and its approximate location, then a NDVI threshold would have been sufficient. However, if the area of damage was used to trigger different options based on severity, then the feature extraction method would have to be considered because of its higher correlation with the visual damage rating.

Fig. 4

Analysis of the June 24, 2014, images acquired from an altitude of 30 m. (a) Area (% of plot) classified with CPB damage using 0.7 ≤ NDVI ≤ 0.80 . (b) Relative plot area classified with CPB damage using feature extraction of the NDVI image.

For the most impacted plot [plot 102, Fig. 1(a)], the area classified as damaged was less than 10%, which was too small to have a strong effect on whole-plot mean NDVI ( 10 % area × 0.75 + 90 % area × 0.85 = 0.84 ). Based on the plot area of 24 m 2 , an equivalent satellite pixel size would be about 5 m, which is close to the 6-m multispectral resolution of the SPOT 7 satellite. These calculations suggest that a multispectral satellite with a 5-m pixel size would not detect the changes that occurred over just the 1 day. The WorldView-2 and WorldView-3 multispectral sensors have 1.84-m pixel resolution for an area of 3.4 m 2 . Assuming the same area damaged occurred in just one WorldView-2 pixel [ ( 2.4 m 2 × 0.75 + 1.0 m 2 × 0.85 ) / 3.4 m 2 = 0.78 ], canopy damage would be visible. However, if the canopy damage was divided by 8 WorldView-2 pixels (the maximum number possible based on plot dimensions), then the amount of damage would not be detectable. Based on these calculations, it is likely that high-resolution commercial satellites would not be able to detect CPB damage just after it occurred. As the 2014 growing season progressed, CPB damage accumulated to over 75% of the area in each plot, so at some point later in the growing season, CPB damage would become detectable by satellites with larger pixel sizes. Therefore, remote sensing by aircraft, manned or unmanned, remains the best option for early detection of CPB damage. However, studies have not been conducted that show whether manned or unmanned aircraft are more cost effective.

Is there a means of acquiring more accurate information about the amount of CPB damage to a potato canopy? SFM point clouds are intermediate photogrammetric products during the creation of orthomosaic images from numerous overlapping images. With higher spatial resolution available from low-altitude sUAS, digital surface models show spatial variations in plant height. 22 – 25 We constructed digital surface models from NDVI, true-color data, color-infrared data, and single bands. On June 23, 2014, the canopy surface was uniform except for the areas between rows [Fig. 5(a)]. Areas of the canopy that were visibly lower on June 24, 2014 [Fig. 5(b)] corresponded with areas of CPB damage [Figs. 1(c) and 3(b)]. The digital surface models had overall curvature; there was an overall convex shape in Fig. 5(a) and an overall concave shape in Fig. 5(b). The digital surface curvatures were least in the center of the image, so plots 102 (the most damaged) and 302 (ranked 7th) were selected for comparisons.

After the overall curvature was taken into consideration, the maximum height of the potato canopy above the soil surface was constant for the 16 plots on both days (3D Multimedia 1). With a single image, variation in height could be attributed to nonuniform increases in plant growth instead of CPB damage. Furthermore, areas of increased growth are expected to have increased NDVI, so similar correlations between the canopy surface elevation and NDVI would result. 22 – 25 Comparison of the two images showed that the lower areas of the canopy on June 24 were clearly the result of leaf removal, and also showed that frequent monitoring is required for distinguishing CPB damage, but daily flights as done in this study would be costly and burdensome. However, estimates of plant height could be made by crop simulation models, incorporating weather and phenotypic differences, so differences between expected height and the digital surface elevation models would provide similar information compared to more frequent UAS flights.

Fig. 5

Three-dimensional perspectives looking east on (a) June 23, 2014 and (b) June 24, 2014. Damage from CPB created depressions in the canopy surface elevation model visible after 1 day. The images were mosaics of 59 and 55 near-infrared images for (a) and (b), respectively. Altitude of sUAS was 30-m above ground level, which resulted in a 15-mm ground sample distance. The full point cloud models can be viewed as a multimedia 3-D PDF file (3D Multimedia 1, PDF, 45 MB) [URL:].

The canopy areas assessed visually as damaged were either soil or shadows created by gaps in the canopy [Fig. 6(a)]. Within a plot, CPB damage was defined when the image object’s mean NDVI was ≥ 0.7 and ≤ 0.80 [Fig. 6(c)]. There was more area classified as damaged from the threshold criteria applied to pixel-based NDVI [Fig. 6(b)] compared to the criteria for the image objects [Fig. 6(c)].

Fig. 6

(a) True color subset of plots 302 (top) and 102 (bottom) from the June 24, 2014, orthomosaic acquired at 30-m altitude. These two plots were near the center of the point cloud, which had the least overall curvature. Plot 102 was visually ranked 16th (the most visual damage), whereas plot 302 was ranked 7th. Edge pixels were not included in the analyses. (b) NDVI with color ranges selected to show damage. (c) Rule-based classification of damage (red) and no damage (green). (d) Relative elevation above ground level determined from the point cloud.

Canopy surface elevation generated from the SfM point clouds showed depressions at the same locations, where damage was indicated by NDVI. However, the area classified as damaged was larger [Fig. 6(d)]. Comparing the three methods [Figs. 6(b)–6(d)] with the true-color image [Fig. 6(a)], the amount of area classified as CPB damaged is subjective, whether by visual interpretation or by the choice of algorithm for detection. 35 , 36

There are many options in workflows for acquiring and analyzing sUAS imagery. 37 – 40 For determining in-season nitrogen fertilizer requirements, transects of single images over large fields would be most cost effective, because variation of fertilizer requirements is largely caused by variation in soil properties. 41 Each image should have very-high spatial resolution to determine plant cover and chlorophyll content of single leaves. With insect pests, the pattern of damage is unpredictable, so frequent coverage of the whole field may be required. However, if the spatial distribution of damage is clumped (as in Fig. 2), then pixel sizes could be somewhat larger and would still be effective.


Leaf and plant damage caused by CPBs was spatially unpredictable and appeared just over 1 day, so frequent sUAS flights with extensive coverage were needed for early detection. We compared three methods for supervised classification of early CPB damage: pixel-based NDVI thresholds, object-based image analysis, and plant height. Using an orthomosaic image, all three methods found small areas of CPB damage on the day that the damage was first visually detectable. Based on calculations and ignoring problems with cloud cover, satellite data with 5-m pixels would not have been effective for monitoring CPB damage. We are intrigued by the potential for using plant height from SfM point clouds, because undamaged plants could serve as field-by-field references making the overall assessment somewhat more objective. When compared to a visual damage ranking, feature extraction based on object-based image analysis was the most accurate method for detecting the relative amount of plant damage. However, both the feature extraction and plant heights required extensive operator intervention for success. Because the different methods for classification of CPB damage did not result in similar areas of damage, it is necessary for precision IPM to ascertain whether early detection is sufficient or accurate estimates of the amount of damage are required.


The project was funded in part by Boeing Research & Technology, Kent, Washington, United States. We thank Alan E. Bruce and Robert W. Turner from Boeing Research & Technology for the initial image processing. Also, we thank Josh J. Brungardt from Paradigm ISR (Bend, Oregon, United States) for managing the UAS and FAA COA. Finally, we thank Philip B. Hamm for facilitating the research at the Hermiston Agricultural Research and Extension Center.


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