Estimating damage

Part I

In this weeks lab we had to estimate damage on corn, soybean, and sorghum.

In the corn the damage looked like both fungal and feeding damage. The feeding damage looks like it could have occurred from some type of caterpillar, or another insect with chewing mouth parts. The corn stalk had borer holes in it which leads me to think that it may be a corn ear worm.

The soybean leaves looked like they had insect damage from an insect with chewing mouth parts. Some of the feeding occurred in the middle of the leaves and some of the feeding damage was all around the leaves. Some insects that may feed on soybean may be corn earworm or armyworm.

The sorghum damage looked like it was caused by an insect with chewing mouth parts such as a corn earworm or an armyworm. The damage may have also been caused by another type of pest - - a bird!

The sampling unit for corn was an ear of corn and the sample size was 30. For soybean the unit was one soybean leaf and the sample size was 50 leaves. The sorghum sampling unit was one head, and the sampling size was 30 heads. To estimate the damage for each of these systems I attempted to imagine all of the damage put together, then I tried to decide if I thought that all of the damage took up more or less than 50% of the sampling unit, and I went from there.  I used this strategies for all three of the sampling systems. I have never attempted to estimate damage, so this was a bit difficult for me to see. 


According the Flint and Gouveia the definition of absolute samples are samples that count every individual in a population in a given area and relative samples are sampling methods that provide an unbiased estimate of the population, with every sample unit having an equal chance of selection (2001). Therefore, according to these definitions the sampling we did by estimating damage is relative. This is because we selected leaves from a population - each leaf had an equal chance of selection, it did not include every individual in the population. 


Part II
Next, each sampling unit was looked at closer and the percent loss was determined. I did not estimate very well for any of the samples (sorghum, soybean, or corn). I did the best job at estimating sorghum damage (out of the three this was the crop that I was most accurate with)- it was the only group that i had a R2 above .5. I think the hard part of estimating sorghum damage was that the size of the sorghum heads varied so much, what might have been 5% damage on one, could have been 25% damage on a smaller one. 

The Next was soybean leaves. My estimations for soybean damage were all over the place, not very accurate or precise at all. I think the difficulty here was that I tended to over estimate damage. I was looking for any little sign that would have counted towards damage.

Finally with corn I did the worst job estimating. My R2 value was only a .3 which is not very good. Again all of my points are scattered. I think the hardest part about estimating with the corn was that I didn't exactly know what damage could have been defined by. I just counted areas on the ear that were covered with a fungal disease or had obvious insect damage. I didn't think to count areas that were missing kernels all together from other problems other than insect damage. However, after reviewing the results from the rest of the class, it doesn't look like I did that bad at estimating the corn damage in comparison. 

When compared to the class I think I did average on estimating sorghum and corn, and below average estimating  soybean. I overestimated in corn, soybean, and sorghum. Based on R2 values and y intercepts, I think that Hedlund had the best estimations for corn, McCartney for soybeans, and then Patterson for sorghum. 


Looking back on the lab- it initially seemed easy, but there are many of things I would have done differently a second time around. For instance, I did not think to look for insect frass - this is a good indication of what may be causing the damage. Another thing I did not take very well into account was the size of each sampling unit. This can make it difficult to estimate damage- if you look at a large sorghum head, next to a small sorghum head. Regardless, I'm sure it takes time to become good at estimating damage. To accurately estimate damage, it would be nice to use the computer programs that were used to estimate the damage; but right now technology is not up to date enough to make this possible. For now, you have to hope that you have a good scout that is a much better damage estimator than I am!

Insect structures: what's in the bag?

Insect structures: what’s in the bag?
The purpose of this week’s lab was to be able to sort through samples from sorghum and soybean fields in the area and sort out the insects. We had to sort the insects by mouth parts because mouthparts are a main diagnostic key when identifying insect pest damage.

The first bag I sorted was sampled from soybean field in Manhattan, KS. In this bag I sorted out 27 insects; 88% of the insects had chewing mouth parts, 7% had piercing-sucking mouth parts, and 3% had siphoning mouth parts. The piecing-sucking insects were both stinkbugs, and the insect with siphoning mouth parts was a moth. The insects with chewing mouth parts were broken down into the following groups: 58% green beetle, 17% caterpillars, 17% green field crickets, and 8% green lacewing. The orders in the soybean field were: Lepidoptera, Hemiptera: Pentatomidae, Coleoptera, and Neuroptera: Chrysopidae, and Orthoptera: Gryllidae.

The second bag I sorted through was sampled from a sorghum field in Manhattan, KS. This bag had 20 insects; 90% had chewing mouth parts and 10% had piercing-sucking mouth parts. Again the piecing sucking insects were green stinkbugs. As for the insects with chewing mouth parts 78% of the insects were caterpillars, 11% were green beetles, 5% were green field crickets, and 5% were green lacewings. The orders in the soybean field were the same as the orders in the soybean field.

After the insects were sorted through I picked a green lacewing from the soybean field to look at under the Dino-Lite microscope. I picked this insect because I knew it was a beneficial insect; however, I have never taken the time to really look at it up close. Green lacewings belong to the order Neuroptera and family Chrysopidae. The larvae are typically predaceous and feed on aphids, while the adults may be predaceous, feed on pollen, or feed on honeydew. The eggs are laid on a thin stalk, with the the egg attached to the end. The larvae pupate in cocoons attached to the underside of leaves, and adults overwinter in the forest (Triplehorn and Johnson 2005). The picture below shows the green lacewing’s external anatomy. Green lacewings have a prognathous head orientation, with filiform (thread-like) antennae. These insects move around with their wings, and legs.

There were a couple of difficult parts in the lab for me. The first difficulty came when sorting. There were not enough forceps for the whole class so we had to use big green plastic ones. This made it difficult to grab the insects without smashing them. Another difficulty was with the microscope. It took a good picture, but I didn’t know I could get closer to it. For instance, I would have liked to zoom in so that I could have gotten a better view of the chewing mouth parts. This picture does not make it easy to distinguish individual mouth structures. The third difficulty was realizing that I didn’t know anything about insect larvae! I’m looking forward to being able to identify all the insect larvae that were in the bag.

Using this type of identification method in the field would be difficult. You would need to set up the computer and microscope, which depending on where you are may be an issue. Another difficulty of using this method in the field would be that it would be hard to observe the insect under the microscope if it was still alive. I would suggest bringing a kill jar out to the field with you so you don’t have to worry about the insect flying or crawling away.