How much kaolin is too much?

Red and white kaolin on the class panes we use to measure transmittance.

One important question that growers have been asking is how much kaolin can be on a leaf before having negative consequences from too much shading. If you are considering applying another layer, and the original layer hasn’t been washed off, it is important to know how much kaolin can be on a leaf before it begins to have a negative effect. Because we have some idea of how individual leaves respond to different light levels.

To answer this question we measured transmittance with the equivalent of different rates of kaolin. You can see the response plot below. One important feature of the response is that increasing rates of kaolin beyond 50 lbs/acre doesn’t increase the degree of shade to the same extent that rate increases below that level do.

So how much shade is beneficial for citrus plants? We can start by looking at the the maximum amount of light that these rates allow to reach the leaf.

Citrus leaves saturate at approximately 700 umols/m2 s, which means that additional light does not increase photosynthesis. With red kaolin, at the highest expected sunlight intensity (about 2200 umols), 25 lbs/acre reaches the level of shading reduces the light intensity of the exterior leaves to the saturation level, but the white kaolin doesn’t reach the level of 25 lbs/acre of red until 100 lbs/acre of white, though 50 lbs per acre reaches close to saturation.

Given these differences in intensity, we still don’t know why plants covered with the red seems to grow slightly more than those treated with the white. However, levels of red greater than 25-30 lbs/acre risk excessive diminishing light levels to exterior leaves, which means that they may not be able to maximize photosynthesis.

There can be a lot of complexity in terms of how much light reaches further into the canopy, which is part of how kaolin increases whole plant photosynthesis. However, it would seem that the risk of overapplicaton of white kaolin is low. You should be careful, though with repeated applications of red kaolin, unless previous applications have been mostly washed off.

Effects of kaolin on Asian citrus psyllid

Kaolin films are showing promising results in management of Asian citrus psyllid.  I recently presented preliminary results from our trial of Surround kaolin clay product and a Surround that we have modified with a red dye in presentations to the Polk County OJ Break and to the Citrus Research and Development Foundation research lunch.  To see the complete presentation click here.   

kaolin in field 6 mo
Six-month old trees with white kaolin.

The results are promising: Over the course of the first year after planting we saw an 78% reduction in mean psyllid numbers per tree in the white kaolin treatment.  Thus far, this has also translated in lower infection rates, with a mean of 10% infection in the white kaolin versus 25% in the foliar insecticide treatment.  These results are early, so we should be cautious about jumping to conclusions.  However, other studies have produced similar results, and this means that growers should consider kaolin as a viable practice to incorporate into their management programs.

psyllid plot 1 year
Mean Asian citrus psyllid counts based on weekly counts over the first year after planting on trees treated with Red-dyed or non-dyed (White) kaolin or with foliar insecticide. Click here for full presentation.


Welcome Myrtho Pierre


Myrtho Pierre is the new biological scientist in the lab.  She is already taking charge of many of our specialized measurements.  Myrtho worked for years in horticultural production and consulting in Haiti, and she has been working “behind the scenes” here at CREC for 4 years (3.5 years longer than I have!).  She brings organization and friendliness to the lab, and she is already knee deep in greenhouse management and calibration of chlorophyll fluorescence and root respiration measurement.  I look forward to good things to come.

What is the right actinic light level for OJIP analysis?


We recently began trying to measure OJIP, more succinctly known as “the transient rise in chlorophyll fluorescence,” on citrus plants.  We immediately ran into values that did not make intrinsic sense, with large differences between Fo and O, and with traces that did not look like the characteristic sloped steps of OJIP analysis.  We are using the Opti-Sciences OS-30p+ to collect data. We called the company, and their technicians were very helpful.  They suggested that the modulated light power should be reduced. In order to do that we did not activate photosynthesis with our modulated (far-red light).  They also recommended that we optimize the actinic light level.  Because we could not find any published systematic approach to it we decided to try to go about it in a systematic way ourselves, and share the results with anybody who might be interested.  It is interesting to note, that I had worked with OJIP of papaya for 3 years, and never noticed such problems. Thus, optimization may need to be species- and/or conditions-based.



We were used two (2) varieties of citrus (Murcott and Ruby Red) under two light levels: full sun and the Citrus Under Protection environment (approximately 20% shade). Leaves were selected randomly at approximately 2 to 3 meters from the ground. In the same row we put dark acclimation clips on leaves using one (1) leaf per tree. After one (1) hour of dark acclimation, we collected data for 8 different actinic light level from the lowest to the highest level: 525, 875, 1000, 2500, 3000, 3500, 4500, and 6000 µmol m-2 s-1 using the OS-30p+ fluorometer using the JIP protocol (Opti-Sciences, Hudson NH).  This was performed only once.



The results were subjected to principal component analysis, including only raw data: tFm, Fo, O, J, K, I, P, S, using prcomp from R stats and the factoextra package for visualization.



The raw data were simplified because K, Fo, and S were very positively correlated (redundant).  Thus the final results include, tFm, O, J, I, and P.  The first 2 principal components account for approximately 86% of the variance, and the third PC adds another 10% (Scree plot).   tFm and O are negatively correlated on both the first and second PCs, and I and P add a different direction of effect.


Actinic light level is the primary contributor to the variance in PC1, and a significant main effect on PC2, with no interactions with other factors (Anovas below).  In theory This makes the actinic light part easy.



Ideally we would find an actinic light level that had confidence intervals that overlapped with zero in both directions, but no dice.  The means for 1000 µmol m-2 s-1 and 2500 µmol m-2 s-1 are closest to 0 and upon visual inspection, you would think that somewhere around 1800 µmol m-2 s-1 would be very close to zero (Figure below).


Another point to consider is that initial problem including large differences between Fo and O.  Light level also had a significant impact on this difference, but with an interaction with the other 2 factors.  While it is normal to have some difference between Fo and O, and because Fo is measured in the “dark” and O immediately after turning on the actinic light, you would expect delta O (Fo-O) to be slightly negative, but certainly, not 200 different (Fm being around 900), as with 6000 µmol m-2 s-1. However, at 1000 µmol m-2 s-1 the value of delta O overlaps above 0, which would make me think that perhaps this is not quite enough light, while at 2500 µmol m-2 s-1 the different varieties and locations are distinguishable, which should not necessarily be the case, as Fm and O are different estimates of the same characteristic.   Once again, neither 1000 nor 2500 µmol m-2 s-1 can be eliminated, while it appears that perhaps an intermediate light level could be more suited.


Still, delta O appears to respond toothed factors in addition to actinic light level (Analysis of variance results below).


Thus a delta O below 0 is not necessarily a mistake.  The only potential explanation for this that I have is that the rate of rise of the early part of the transient effects a higher O relative to Fo.  If this is true Vj should be negatively correlated to delta O.  I tested this with car.test in the basic R stats package, which uses a Pearson’s product-moment correlation and derives a p-value. The result was a correlation of -0.487, with 95% confidence interval of -0.567 to -0.399, and a p-value of <0.0001.  My conclusion is that delta O is affected by light level but also by photochemical structure of the leaf, primarily in absorption-trapping.

The overall conclusion, however, is that actinic light level affects the results of the OJIP test.  Although it is not entirely clear what the results should be, it seems that chlorophyll fluorometer companies could help us by including some actinic levels in the range of 1800 µmols m-2 sec-1.   I would welcome any comment and would like to see a more systematic approach to OJIP analysis in generally.  A discussion among those who use the test would likely lead to a more sound approach.