Week 7: The great debate

The controversy is between academic research and private industry (commercial products).  Should data from seed companies be made public or is the information strictly the companies property?  Research scientists and the private seed industry have agreements and terms which allow for the sharing and public use of vital information involving human and environmental health.

Who's in control though?  The EPA and FDA have certian standards that must be met in order to become commercially available to the public.  Although these two organizations regulate to some extent what goes on within the biotechnology of the product the seed companies in all reality can determine and alter the tests conducted.  The private seed industry has the majority of say on what can be published and what can't.  They decide and form agreements on the testing with the academic sector and if the public researchers do not comply with the conditions then no information can legally be conducted.

Researchers are going about this all wrong.  I believe that a stronger trust between the two should be formed rather than researches criticizing.  Researchers working with the private seed industry could correlate with each other in that the information formulated from research could benefit the companies in a good way and  at the same time the public could become aware of the technology at hand.  Using the information from the test trials and comparisons could aid in correcting or formulating better and newer products.

Growers should be informed and given disclaimers on the performance data.  This would give the producers a better understanding of what they growing.  Also the growers would be given the information on whether the seed was extensively compared to other top varieties and standards.  Although bio-technology is looked upon as a negative aspect in some cases without this technology (GM crops) food security would not be in the position it is currently in today.  Our global food source is very much dependent on bio-tech crops which involves the advancement of increased productivity for an ever growing world population.

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Entom 767

The max carrying capacity or the plateau from the functional response graph can be reached by several different factors. For example a limited food source which inhibits the ability of the insect to find a valuable source of energy will affect population density.  Also limited space within the insects natural climate can be factor towards survival and reproduction.

The insect density number is the variable that determines the level of the plateau on the graph.  Many different things can take place and disrupt the number of prey attacked by a predator.  Weather and field distribution play a big key in the attack rates.  Number of predators within a population can also correlate with the number of prey attacked.  Higher populations mean more encounters and lower populations might mean fewer interactions. 

During the trial the lady beetle I observed had 7 events (attacks).  I classified an event on the basis of attacking an aphid (start time) and recording the results up to the next attack (end time).  The times from event 1-event 7 are as follows:

1) 41 sec
2) 11 sec
3) 2 min
4) 25 sec
5) 39 sec
6) 4 min 36 sec
7) 1 min 46 sec

Between events 3-4 and 4-5 after the prey was consumed the predator (lady beetle) would groom its mouth parts and continue on.  The grooming seemed odd.  My best guess is that the lady beetle was cleaning its mouth parts for the next victim.  My lady beetle was very aggressive compared to my surrounding classmates.  Within the time of approximately 10 minutes my lady beetle had consumed 7 different aphids which show that possible bio-control with insects (natural enemies) could be beneficial and cost effective.  The standard error for the 7 events was 1.885.

Compared to the table in the handout the handling times are longer and more extensive than in the trials that I conducted.

My responsibility was to trace the search pattern of the lady beetle in search of prey.  The patterns for both predators were random and they spent the majority of their time along the straight edges of the case.  The second lady beetle found the aphid infested leaf about half way through the trial ( @ 3 minutes). 

I was not surprised that the second lady beetle found the leaf but rather surprised that the first lady beetle had a hard time coming up with the find.  Being confined to a small area with only two leafs visible in the center should have been simpler compared to field conditions.  It is possible that the lady beetle was not use to the unfamiliar habitat and was thrown off track.  Either way with high population numbers in a field situation I gained a better understanding with this experiment that bio-control with insects can be potentially useful in a management system.

In the analysis of behavioral sequences we observed 2 events.  Within both trials we calculated the time spent walking, grooming, resting, and feeding. 
Results determined from standard error:

walking (24.74)
resting (7.07)
feeding (31.81)
grooming (no time)

Lab Wk 3 Estimating Damage

Most of the damage seen on the different sample units were from chewing feeding types.  Earworm, grasshoppers and birds could have been related to the damage observed on the corn, soybeans, and sorghum.  From the initial feeding damages there was some formation of disease on the corn.  This is an indirect effect from the feeding/injury.  The sampling units used were leaf (soybean), ear (corn), and head (sorghum).  The soybean sample size included 50 different leaves.  The corn included 30 different ears as samples.  The sorghum samples consisted of 30 different heads.  The estimation method that I used was real basic.  The percentage of the ear/head/leaf that was infected or gone compared to the healthy intact section enabled me to roughly estimate a percentage.  Sampling is a relative measure since we were comparing and judging off of each individual leaf.  Absolute sampling would involve the actual percentage determined from calculations.  Different sizes of the samples could have affected my accuracy.  Using more uniform samples might correct this problem.

Comparing Results:

Sorghum (R2)
Wehking (highest in class)-0.8277
Trachsel-0.8019

Corn (R2)
Pfizenmaire (highest in class)-0.5327
Trachsel-0.0448

Soybean (R2)
Baird (Highest in class)-0.9173
Trachsel-0.847

-I was over estimating on my predicted damage compared to the observed damage.

Not accurately determining the damage in the field can imply one way or another that the situation is economical or not.  Having a false idea from those predictions could result in losses from controlling when not needed or not controlling when needed.

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The information from these graphs can be used in determining your comparison to the actual damage and then can help with making an economical decision.

Examining insects, for the most part, are hard to see without a microscope.  That is why taking samples and pictures in the field are extremely difficult compared to being in the lab.  Using the technology that is used in the lab out on a farm location is not readily available and can be expensive.  This picture above is a grasshopper (Orthoptera).  It has a hyognathus head orientation, chewing mouth parts and legs that are adapted for jumping.  Other orders that I found in the soybean and milo sample were Coleoptera, Neuroptera and Lepidoptera.  The majority of the insects had chewing mouth parts.  In the order Lepidoptera i found a moth with mouth parts capable of siphoning and in the order Neuroptera the lacewing had sucking mouth parts.