We appreciate the assistance of Chris Parker who daily scanned the plants and Curtis Hubbard who maintained the plants in the greenhouse.

1. Establish TSSM Colonies on Pinto Beans
<ol>
	<li>Plant pinto beans, Phaseolus vulgaris L., in plastic trays (56 x 28 x 5 cm3) containing potting soil in the greenhouse as shown in Figure 1.</li>
	<li>Label the trays with marking sticks according to treatment and replication.</li>
	<li>Set and maintain greenhouse temperature to 90 &#176;F and 70% Relative Humidity.</li>
	<li>Grow beans to 1-2 trifoliate leaf stage10 as shown in Figure 2.</li>
	<li>Collect spider mites from cotton plants infested naturally with mites by removing infested leaves.</li>
	<li>Place spider mite infested cotton leaves on pinto beans as often as necessary until all plants in the trays are infested with numerous TSSMs.</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/54314/54314fig1.jpg" /> 
Figure 1: Planting pinto beans in plastic trays. Pinto beans seeds were planted in plastic trays (56 x 28 x 5 cm3) in the greenhouse and were watered daily. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54314/54314fig2.jpg" /> 
Figure 2: Pinto beans with trifoliate leaves. The first true leaf that is formed after the cotyledons emerge from the soil is the simple or unifoliate leaf. Subsequent leaves are the trifoliate leaves with denticulate tips. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
2. Transfer TSSM to Cotton Plants
<ol>
	<li>Grow Non-Bt (not genetically modified) cotton plants to 4-5 true leaf stage in plastic trays (56 x 28 x 5 cm) in the greenhouse as specified in step 1.3 and shown in Figure 3.</li>
	<li>Transfer spider mite colonies from pinto beans onto young cotton plants at 4-5 true leaf stage.
	<ol>
		<li>Transfer 3 masses of spider mites for lightly infested plants. Note: At very high infestation levels, spider mites form masses or bolls11 and are found hanging on leaf tips as seen in Figure 4.
		<ol>
			<li>Place a pan under pinto bean leaf tip containing TSSM masses.</li>
			<li>Cut pinto bean leaf tips with scissors, allowing TSSM masses to fall into the pan as shown in Figures 5 and 6.</li>
			<li>Turn pan upside down over cotton plants and tap TSSM masses onto cotton plants grown in plastic trays as shown in Figure 7. Note: Each tray contained ~100 cotton plants.</li>
			<li>Randomly spread 3 masses of TSSM onto cotton plants.</li>
		</ol>
		</li>
		<li>Transfer 20 masses for medially infested plants.
		<ol>
			<li>Place a pan under pinto bean leaf tip containing TSSM masses.</li>
			<li>Cut pinto bean leaf tips with scissors, allowing them to fall into the pan.</li>
			<li>Collect 20 masses in the pan.</li>
			<li>Turn pan upside down over cotton plants and tap out TSSM masses onto ~100 cotton plants raised in the greenhouse.</li>
		</ol>
		</li>
		<li>Transfer 40 masses for heavily infested plants.
		<ol>
			<li>Place a pan under pinto bean leaf tip containing TSSM masses.</li>
			<li>Cut pinto bean leaf tips with scissors, allowing them to fall into the pan.</li>
			<li>Collect 40 masses in the pan.</li>
			<li>Turn pan upside down over cotton plants, tap out TSSM masses onto ~100 cotton plants and spread them randomly.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
<img alt="Figure 3" src="/files/ftp_upload/54314/54314fig3.jpg" /> 
Figure 3. Cotton plants with 4-5 true leaf stage. The cotyledons emerge from the soil as leaf-like structures oriented opposite to each other on the seedling stem. The apical meristem emerges through the cotyledons and form the first true leaves. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54314/54314fig4.jpg" /> 
Figure 4. TSSM masses hanging on a trifoliate bean leaf. TSSM lives in colonies and when populations reach high density, they form masses or boll-like structures and congregate at the leaf tips for dispersal. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54314/54314fig5.jpg" /> 
Figure 5. Cutting pinto bean leaf tips containing a TSSM mass with scissors. Trifoliate bean leaf tips containing TSSM masses were removed with scissors for infesting cotton plants. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/54314/54314fig6.jpg" /> 
Figure 6. TSSM masses on bean leaf tips placed inside the pan. When sufficient number of trifoliate bean leaf tips with TSSM were found in the test plants, they were removed and placed inside the pan. These samples were used to infest treatment categories: light, medium and heavy which received 3, 20 and 40 masses of TSSM, respectively. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" src="/files/ftp_upload/54314/54314fig7.jpg" /> 
Figure 7. Turning pan upside down. The pans containing trifoliate bean leaf tips with TSSM were turned upside down on cotton canopy to infest the test plants. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
3. Scan TSSM Infested Cotton Plants with the Multispectral Optical Sensor
<ol>
	<li>Horizontally mount the optical sensor onto the greenhouse frame approximately 7 ft above the floor as shown in Figure 8. Set the distance between the scanner and the plant canopy at 36&#34;. Use a carpenter&#39;s level to ensure that the sensor is horizontally level.</li>
	<li>Place uninfested trays of cotton plants on a wheeled push cart.</li>
	<li>Activate the sensor switch and slowly push the cart under the sensor until the tray completely passes the sensor head as shown in Figure 8. Turn off switch. Retract the cart.</li>
	<li>Repeat Step 3.3 three times, for a total of 3 replications.</li>
	<li>Repeat this procedure for all trays of cotton.</li>
	<li>Repeat scanning on Day 1, Day 5, Day 6, Day 7, Day 9, Day 10, Day 12, Day 13 and Day 14 after treatment (DAT). The scanning provided the NDVI (Normalized Difference Vegetation Index) values12. Transmit the NDVI values to and store on a pocket PC which then can be downloaded to a computer in text format. 
	NOTE: NDVI was calculated from the following equation: NDVI = (NIR - RED)/(NIR + RED), where RED and NIR are the spectral reflectance values (0-255) in the red and near-infrared spectrums at 660 and 770 nm, respectively.</li>
</ol>
<img alt="Figure 8" src="/files/ftp_upload/54314/54314fig8.jpg" /> 
Figure 8. A multispectral optical sensor used to quantitatively measure the health of cotton plants infested with varying density levels of TSSM. The wheeled push cart with the test plants were slowly traversed under the sensor head to obtain spectral reflectance values. a is the sensor head; b is pocket PC; c is battery compartment and input/output ports; d is RS-232 serial data cable and e is the craft paper to provide uniform background. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
4. Data Analyses
<ol>
	<li>Obtain the maximum NDVI values using the Proc Means procedure13. Calculate the percent reduction in NDVI values for each day of observation using Day 0 as a reference value. Analyze the data using the repeated measures PROC GLM procedure13. 
	NOTE: Means were separated using the Duncan&#39;s Multiple Range Test at P = 0.05. Means with the same lower case letters were not significantly different.</li>
	<li>Perform graphical illustrations of the data14 as shown in Figure 9.</li>
</ol>
<img alt="Figure 9" src="/files/ftp_upload/54314/54314fig9.jpg" /> 
Figure 9. Percent reduction or change in NDVI relative to days after treatment. JMP software was used to graphically illustrate the functional relationship between percent change in NDVI relative to days of sampling (DAT). <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54314/54314fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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The authors have nothing to disclose.

Conventionally, insecticide efficacy tests conducted in the field include several treatments of the chemical applied at different rates and compared to an untreated check. Acaricides with varying toxicity profiles against instar and adult stages of TSSM are assessed to determine whether the damage caused by them could be reduced by the chemical treatment. TSSM samples are collected and brought to the laboratory where they are examined under the microscope and the varying stages of TSSM are counted and recorded. It is critically important to take adequate samples of the host plant to determine the damage in each treatment and differentiate them with statistically acceptable precision. The number of samples that are required to differentiate the treatments from each other depends upon the distribution profile of the organism. Highly patchy distribution of the TSSM leads to a considerable amount of variation between sample areas, and many plants must be sampled in order to ensure reproducibility of the population estimates. However, budget, manpower, time and statistical precision are important factors that impinge upon sampling techniques. It behooves the researcher to allocate the available resources optimally to conduct sampling with the least cost but with most precision.
Entomologists in lieu of counting TSSM stages visually score the damage based upon a scale of no damage to varying levels of damage. For instance, some researchers proposed binomial sampling, where only the proportion of infested leaves was scored rather than the number of spider mites per leaf9,19. Others estimated damage by TSSM on cotton based on a leaf reddening index scale, which varied from stippling and reddening to extensive reddening of vegetation canopy19. These methods are arbitrary, anecdotal and biased by individual perceptions of the degree of damage. A more robust and quantitative assessment of the damage caused by TSSM is required to evaluate and separate the treatments with statistical precision.
The ground-based multispectral optical sensor appears to be an improved sampling tool to quantitatively determine the damage inflicted by TSSM and to separate the treatments more precisely than the visual damage scoring system adopted by many researchers. However, researchers have reported that the data intensive hyperspectral remote sensing provided numerous spectral signatures to identify and detect crop stresses and canopy characteristics compared to multispectral remote sensing which is less data intensive with two wave lengths20,21. Using a hyperspectral spectrometer, Reisig and Godfrey found that the NIR reflectance wavelength &#8776;850 nm as an informative spectrum in distinguishing arthropod-infested from uninfested cotton22. In this study, we have shown that the multispectral reflectance values (NIR value being &#8776;770 nm) with just two spectral bands were able to identify and characterize cotton plants infested with varying densities of TSSM. Also, we have reported earlier that the multispectral optical sensor not only effectively separated cotton plants infested with widely varying density categories of TSSM, but also showed that spiromesifen was more effective than abamectin in controlling TSSM in early season cotton in the greenhouse at one-half rate of the lowest label rate23.
The multispectral optical sensor could be mounted on a mobile research platform and the reflectance values could be obtained from the treated areas of the vegetation canopies without human subjectivity. Acaricidal efficacy data can thus be obtained without much human labor. The NDVI data can be easily uploaded to the computer and analyzed using commercial statistical software. A GPS receiver also can be mounted onto the mobile platform to collect the GPS coordinates in order to generate a damage map of the field. Using multispectral reflectance signatures from the plant canopy, the multispectral optical sensor provides a rapid and cost effective means of identifying and quantifying plant stress. Moreover, a much larger area of the field can be covered in less time with higher spatial resolution of plant canopy compared to conventional field scouting. It is important to remember that the threshold damage level for TSSM on cotton is variable from region to region in the United States. For example, TSSM damage would be higher in an arid environment such as in California compared to the Midsouth region where rainfall and high humidity often prevail24. Therefore, yield loss due to TSSM damage will be variable and so is the damage threshold. However, reports from Mississippi, Arkansas and Tennessee reveal that the threshold level for TSSM on cotton appears to be when 30 to 50% of the plants are infested and populations are actively increasing5. Furthermore, field grown plants are exposed to multiple stresses including water stresses and feeding of arthropod herbivores and the interactions between these activities can substantially reduce plant productivity and are likely to influence damage threshold. The TSSM can reduce stomatal conductance, photosynthesis and transpiration rate in cotton25. Plants grown in the greenhouse are influenced by UV light radiation and it does significantly influence stomatal function, photosynthesis and canopy morphology26,27 and could probably have an additive effect on plant stress. However, TSSM is capable of avoiding UV radiation by having access to habitat protected from solar radiation on the lower surface of the plant canopy28,29,30, where it resides.
The height of the optical sensor above the target canopy and the orientation of the sensor relative to the target are important factors that affected significantly the reflectance values obtained by the multispectral optical sensor31. For instance, when the mobile research platform traverses through a row crop field such as when cotton canopy is open, the sensor is likely to produce different results depending upon the orientation of the sensor, either parallel to or perpendicular to the row. It is also likely that soil and other background materials may greatly influence the sensor readings, especially when the sensor is oriented perpendicular to the row. In order to obtain maximum response from the sensor, the sensor head should be oriented in-line with and directly above the rows. Although orienting the light beam perpendicular to the rows is more likely to pick up background soil reflectance, this may be acceptable, however, when cotton canopy is closed with lush vegetation. In addition, operators should follow manufacturer&#39;s recommendations on an operating height range of 81-122 cm and orienting the sensor head in-line with the target to obtain maximum signal response. It is important to charge the sensor battery before use or it should be kept plugged in to avoid troubleshooting. Low battery level is likely to produce erroneous readings.

Two-spotted spider mite, Tetranychus urticae (Koch) is a polyphagous and cosmopolitan pest of many field and horticultural plants1,2. It lives inside webbings in colonies on the bottom surface of the plant3,4. It has evolved from being a late season to an early season pest in the mid-southern United States over the last decade5. TSSM was the 5th most damaging pest of cotton and caused an estimated loss of 57,441 bales of cotton and 0.167% reduction in yield in the United States in 20116,7. Its short life cycle, high fecundity and haploid-diploid sex determination combined with the ability to digest and detoxify xenobiotics have exacerbated the development of resistance to pesticides8. Presently, acaricides remain as the only dependable control mechanism for the suppression of T. urticae. Therefore, field entomologists constantly evaluate currently available and newly developed acaricides for efficacy.
The estimation of damage by the spider mites is usually conducted by scoring the damage on a subjective scale because of the difficulty encountered in manually counting the mites. Some conducted binomial sampling, where only the proportion of infested leaves was scored rather than the number of spider mites per leaf9. A leaf reddening index scale, which varied from stippling and reddening to extensive reddening of the vegetation, was used as a criterion in estimating damage. The spatial distribution pattern of T. urticae on cotton conformed to a clumped distribution pattern9. Mites are distributed on cotton foliage from sparse to heavily clustered and remain so under field condition. Such distribution pattern coupled with its small size, mobility and prolific reproduction makes enumeration of TSSM difficult. Reliable alternative techniques are needed for the assessment of mite density in order to quantitatively evaluate efficacy of acaricides against TSSM.
The objective of this study was to separate cotton plants damaged by varying densities of TSSM by using an optical multispectral sensor. Our intent was to determine if the ground-based optical sensor could classify and separate healthy cotton plants from those damaged by the spider mites.

<table border="0" cellpadding="0" cellspacing="0" width="698">
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		<tr height="41">
			<td height="41" style="height:41px;width:216px;">GreenSeeker&#160;</td>
			<td style="width:128px;">Trimble Ag. Division</td>
			<td style="width:119px;">Model 505</td>
			<td style="width:235px;">Red NDVI sensor</td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:216px;"></td>
			<td style="width:128px;">Westminster, CO</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:216px;">Pinto beans</td>
			<td style="width:128px;">Producer&#39;s Co-op., Bryan, TX</td>
			<td style="width:119px;">Not applicable</td>
			<td>Free choice item</td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;width:216px;">Deltapine cotton seeds</td>
			<td style="width:128px;">Brazos Bottom Crop Care, Caldwell, TX77836</td>
			<td style="width:119px;">Not applicable</td>
			<td>436 RR; NonBt &#38; RoundUp&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;"></td>
			<td style="width:128px;"></td>
			<td style="width:119px;"></td>
			<td>Ready</td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:216px;">Plastic trays&#160;</td>
			<td style="width:128px;">BWI, Schulenberg, TX</td>
			<td style="width:119px;">FG1020NL7</td>
			<td>56 x 28 cm</td>
		</tr>
		<tr height="61">
			<td height="61" style="height:61px;width:216px;">Label sticks</td>
			<td style="width:128px;">Gempler&#39;s, Janesville, WI 53547</td>
			<td style="width:119px;">Item # 151276</td>
			<td>Durable spike-style pot markers</td>
		</tr>
		<tr height="61">
			<td height="61" style="height:61px;width:216px;">4-wheel Garden push cart</td>
			<td style="width:128px;">Farm Tek, Dyersville, IA 52040</td>
			<td style="width:119px;">Item # 108676</td>
			<td>61 x 122 cm</td>
		</tr>
	</tbody>
</table>

remote sensing evaluation of two-spotted spider mite damage on greenhouse cotton

The objective of this study was to evaluate a ground-based multispectral optical sensor as a remote sensing tool to assess foliar damage caused by the two-spotted spider mite (TSSM), Tetranychus urticae Koch, on greenhouse grown cotton. TSSM is a polyphagous pest which occurs on a variety of field and horticultural crops. It often becomes an early season pest of cotton in damaging proportions as opposed to being a late season innocuous pest in the mid-southern United States. Evaluation of acaricides is important for maintaining the efficacy of and preventing resistance to the currently available arsenal of chemicals and newly developed control agents. Enumeration of spider mites for efficacy evaluations is laborious and time consuming. Therefore, subjective visual damage rating is commonly used to assess density of spider mites. The NDVI (Normalized Difference Vegetation Index) is the most widely used statistic to describe the spectral reflectance characteristics of vegetation canopy to assess plant stress and health consequent to spider mite infestations. Results demonstrated that a multispectral optical sensor is an effective tool in distinguishing varying levels of infestation caused by T. urticae on early season cotton. This remote sensing technique may be used in lieu of a visual rating to evaluate insecticide treatments.

The sensor emits red and infrared light and this light in turn gets reflected back from the plant canopy. The reflected light serves as a quantitative measurement of the visible and the near-infrared bands of the electromagnetic spectrum and is numerically recorded as NDVI (Normalized Difference Vegetation Index) reading. The NDVI values vary from 0 to 0.99. The higher the NDVI reading the healthier the plant canopy. Healthy vegetation absorbs visible light and reflects the near-infrared light and unhealthy vegetation reflects more visible light and less near-infrared light. NDVI serves as a surrogate to photosynthetic activity and this spectral property is highly correlated to photosynthetically active radiation15,16,17,18. Very low values of NDVI (0.1 and below) corresponds to barren areas of rock or sand, while moderate values (0.2 to 0.3) represent shrub and grassland and high values (0.6 to 0.8) indicate temperate and tropical vegetation. The reflectance measurements were obtained under daytime lighting in the red and near-infrared regions of the spectra.
NDVI was calculated from the following equation: NDVI = (NIR - RED)/(NIR + RED), where RED and NIR are the spectral reflectance values (0-255) in the red and near-infrared spectrums at 660 and 770 nm, respectively. The sensor records reflectance values every 100 msec. The maximum NDVI readings culled from an array of NDVI values taken each time by the sensor were used in the analyses to minimize background reflectance and to provide consistently repeatable numerical values.
The analysis of variance of the data revealed that significant differences in percent reduction in NDVI were observed between lightly, medially and heavily infested cotton plants compared to the untreated control (F = 436.4; P &#60;0.0001; df = 3, 32). The NDVI values which described plant vigor during the test period varied significantly between days of observation (F = 1398.2; P &#60;0.0001; df = 8, 256). Also, the percent reduction in NDVI values were inversely correlated to the treatments during the observation period (DAT), but seldom tended to deviate from this pattern and interacting significantly with DAT (F = 201.5; P &#60;0.0001; df = 24, 256). The MANOVA test criteria for no DAT effect was significant as well (Wilk&#39;s &#955; = 0.00913; F = 339.0; P &#60;0.0001; df = 8, 25). Similarly, the interaction between DAT and treatment was significant (Wilk&#39;s &#955; = 0.00101; F = 29.8; P &#60;0.0001; df = 24, 73).
Figure 9 shows percent change in plant vigor as demonstrated by NDVI values during the observation period. A positive percent change in NDVI value indicates healthy growing plants, while a negative value indicates that the vigor of the plant has decreased since the first measurement (i.e. Day 0) was made. The non-infested control plants showed increased vegetative growth throughout the course of the study, while the TSSM-infested plants showed degradation in health over time. Mean separation of the treatments shown in Table 1 reveals that no definable difference in percent reduction in NDVI between treatment categories (light, medium and heavy) and the control was observed until Day 5 when infestation classes significantly deviated from the control and remained overwhelmingly so thereafter. This data demonstrates that the optical sensor can be effectively used in lieu of labor-intensive manual sampling to assess treatment efficacy against acaricides on cotton.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="10">Days After Treatment (DAT)</td>
		</tr>
		<tr>
			<td>Infestation Category</td>
			<td>1</td>
			<td>5</td>
			<td>6</td>
			<td>7</td>
			<td>9</td>
			<td>10</td>
			<td>12</td>
			<td>13</td>
			<td>14</td>
		</tr>
		<tr>
			<td>Control</td>
			<td>1.18 &#177;0.33a</td>
			<td>2.70 &#177;0.40a</td>
			<td>4.0 &#177;0.36a</td>
			<td>3.94 &#177;0.37a</td>
			<td>3.68 &#177;0.53a</td>
			<td>2.57 &#177;0.42a</td>
			<td>2.96 &#177;0.47a</td>
			<td>3.48 &#177;0.38a</td>
			<td>3.08 &#177;0.22a</td>
		</tr>
		<tr>
			<td>Light</td>
			<td>-0.13 &#177;0.13b</td>
			<td>-0.71 &#177;0.29b</td>
			<td>-0.65 &#177;0.28b</td>
			<td>-2.02 &#177;0.47b</td>
			<td>-5.68 &#177;0.72b</td>
			<td>-11.17 &#177;0.94b</td>
			<td>-15.73 &#177;1.76b</td>
			<td>-19.54 &#177;1.68b</td>
			<td>-24.9 &#177;1.90b</td>
		</tr>
		<tr>
			<td>Medium</td>
			<td>-1.83 &#177;0.42c</td>
			<td>-7.06 &#177;0.63c</td>
			<td>-9.61 &#177;0.53c</td>
			<td>-10.39 &#177;0.57c</td>
			<td>-17.06 &#177;0.80c</td>
			<td>-26.92 &#177;0.72c</td>
			<td>-33.84 &#177;0.96c</td>
			<td>-37.05 &#177;1.14c</td>
			<td>-41.74 &#177;0.73c</td>
		</tr>
		<tr>
			<td>Heavy</td>
			<td>-0.97 &#177;0.58bc</td>
			<td>-11.76 &#177;0.29d</td>
			<td>-13.83 &#177;0.86d</td>
			<td>-15.20 &#177;0.63d</td>
			<td>-25.0 &#177;1.0d</td>
			<td>-34.63 &#177;0.54d</td>
			<td>-39.07 &#177;0.94d</td>
			<td>-42.68 &#177;0.62d</td>
			<td>-46.71 &#177;0.63</td>
		</tr>
	</tbody>
</table>
Table 1: Percent reduction in Max NDVI after cotton plants were infested with varying number of clusters or masses of TSSM. Cotton plants grown in plastic trays in the greenhouse were infested with three categories of spider mite density. Category Light received 3 masses or clusters of TSSM per tray, Category Medium received 20 masses per tray and Category Heavy received 40 masses per tray. Means were separated from control according to Duncan&#39;s Multiple Range Test (P = 0.05). Means followed by the same lower case letter were not significantly different at the 5% level of probability.

Watch this Scientific Journal Video about Remote Sensing Evaluation of Two-spotted Spider Mite Damage on Greenhouse Cotton at JoVE.com

Remote Sensing Evaluation of Two-spotted Spider Mite Damage on Greenhouse Cotton

This manuscript describes a multispectral optical sensor that effectively detected damage to early season cotton artificially infested with varying densities of the two-spotted spider mite populations.

The objective of this study was to evaluate a ground-based multispectral optical sensor as a remote sensing tool to assess foliar damage caused by the ...

remote-sensing-evaluation-two-spotted-spider-mite-damage-on

Nanyang Technological University

Research

JoVE Journal

Environment

8.5K Views.  USDA-ARS, SPARC-AATRU. This manuscript describes a multispectral optical sensor that effectively detected damage to early season cotton artificially infested with varying densities of the two-spotted spider mite populations.

Video: Remote Sensing Evaluation of Two-spotted Spider Mite Damage on Greenhouse Cotton

Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production

Lignocellulosic biomass is one of the most abundant yet underutilized renewable energy resources. Both anaerobic digestion (AD) and hydrothermal carbonization (HTC) are promising technologies for bioenergy production from biomass in terms of biogas and HTC biochar, respectively. In this study, the combination of AD and HTC is proposed to increase overall bioenergy production. Wheat straw was anaerobically digested in a novel upflow anaerobic solid state reactor (UASS) in both mesophilic (37 &#176;C) and thermophilic (55 &#176;C) conditions. Wet digested from thermophilic AD was hydrothermally carbonized at 230 &#176;C for 6 hr for HTC biochar production. At thermophilic temperature, the UASS system yields an average of 165 LCH4/kgVS&#160;(VS: volatile solids) and 121 L CH4/kgVS&#160;at mesophilic AD over the continuous operation of 200 days. Meanwhile, 43.4 g of HTC biochar with 29.6 MJ/kgdry_biochar was obtained from HTC of 1 kg digestate (dry basis) from mesophilic AD. The combination of AD and HTC, in this particular set of experiment yield 13.2 MJ of energy per 1 kg of dry wheat straw, which is at least 20% higher than HTC alone and 60.2% higher than AD only.

A novel Upflow Anaerobic Solid State (UASS) reactor was used for biogas production from fibrous feedstock. Digestate from UASS reactor was hydrothermally carbonized into HTC biochar in a pressurized batch reactor. The integration of the two bioenergy concepts was applied in this study to increase overall bioenergy production.

Lignocellulosic biomass is one of the most abundant yet underutilized renewable energy resources. Both anaerobic digestion (AD) and hydrothermal ...

Application of Two-spotted Spider Mite Tetranychus urticae for Plant-pest Interaction Studies

The two-spotted spider mite, Tetranychus urticae, is a ubiquitous polyphagous arthropod herbivore that feeds on a remarkably broad array of species, with more than 150 of economic value. It is a major pest of greenhouse crops, especially in Solanaceae and Cucurbitaceae (e.g., tomatoes, eggplants, peppers, cucumbers, zucchini) and greenhouse ornamentals (e.g., roses, chrysanthemum, carnations), annual field crops (such as maize, cotton, soybean, and sugar beet), and in perennial cultures (alfalfa, strawberries, grapes, citruses, and plums)1,2. In addition to the extreme polyphagy that makes it an important agricultural pest, T. urticae has a tendency to develop resistance to a wide array of insecticides and acaricides that are used for its control3-7.
T. urticae is an excellent experimental organism, as it has a rapid life cycle (7 days at 27 &#176;C) and can be easily maintained at high density in the laboratory. Methods to assay gene expression (including in situ hybridization and antibody staining) and to inactivate expression of spider mite endogenous genes using RNA interference have been developed8-10. Recently, the whole genome sequence of T. urticae has been reported, creating an opportunity to develop this pest herbivore as a model organism with equivalent genomic resources that already exist in some of its host plants (Arabidopsis thaliana and the&#160;tomato Solanum lycopersicum)11. Together, these&#160;model organisms could provide insights into molecular bases of plant-pest interactions.
Here, an efficient method for quick and easy collection of a large number of adult female mites, their application on an experimental plant host, and the assessment of the plant damage due to spider mite feeding are described. The presented protocol enables fast and efficient collection of hundreds of individuals at any developmental stage (eggs, larvae, nymphs, adult males, and females) that can be used for subsequent experimental application.

Application of Two-spotted Spider Mite Tetranychus urticae for Plant-pest Interaction Studies

Protocols for efficient preparation of homogenous samples of spider mites, infestation of experimental plants, and assessment of plant damage, as required for studies of plant-pest interaction were developed.

The two-spotted spider mite, Tetranychus urticae, is a ubiquitous polyphagous arthropod herbivore that feeds on a remarkably broad array of species, with ...

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals is often not well understood. Here we demonstrate an integrated field lysimetry and porewater sampling method for evaluating the mobility of chemicals applied to soils and established vegetation. Lysimeters, open columns made of metal or plastic, are driven into bareground or vegetated soils. Porewater samplers, which are commercially available and use vacuum to collect percolating soil water, are installed at predetermined depths within the lysimeters. At prearranged times following chemical application to experimental plots, porewater is collected, and lysimeters, containing soil and vegetation, are exhumed. By analyzing chemical concentrations in the lysimeter soil, vegetation, and porewater, downward leaching rates, soil retention capacities, and plant uptake for the chemical of interest may be quantified. Because field lysimetry and porewater sampling are conducted under natural environmental conditions and with minimal soil disturbance, derived results project real-case scenarios and provide valuable information for chemical management. As chemicals are increasingly applied to land worldwide, the described techniques may be utilized to determine whether applied chemicals pose adverse effects to human health or the environment.

Field lysimetry and porewater sampling allow researchers to evaluate the fate of chemicals applied to soils and established vegetation. The goal of this protocol is to demonstrate how to install required instrumentation and collect samples for chemical analysis during integrated field lysimetry and porewater sampling experiments.

Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals ...

Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.

This article showcases the static chamber-based method for measurement of greenhouse gas flux from soil systems. With relatively modest infrastructure investments, measurements may be obtained from multiple treatments/locations and over timeframes ranging from hours to years.

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the ...

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

We demonstrate the utility of remotely sensed data and the newly developed Software for Assisted Habitat Modeling (SAHM) in predicting invasive species occurrence on the landscape. An ensemble of predictive models produced highly accurate maps of tamarisk (Tamarix spp.) invasion in Southeastern Colorado, USA when assessed with subsequent field validations.

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite ...

Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System

Life tables provide a means of measuring the schedules of birth and death from populations over time. They also can be used to quantify the sources and rates of mortality in populations, which has a variety of applications in ecology, including agricultural ecosystems. Horizontal, or cohort-based, life tables provide for the most direct and accurate method of quantifying vital population rates because they follow a group of individuals in a population from birth to death. Here, protocols are presented for conducting and analyzing cohort-based life tables in the field that takes advantage of the sessile nature of the immature life stages of a global insect pest, Bemisia tabaci. Individual insects are located on the underside of cotton leaves and are marked by drawing a small circle around the insect with a non-toxic pen. This insect can then be observed repeatedly over time with the aid of hand lenses to measure development from one stage to the next and to identify stage-specific causes of death associated with natural and introduced mortality forces. Analyses explain how to correctly measure multiple mortality forces that act contemporaneously within each stage and how to use such data to provide meaningful population dynamic metrics. The method does not directly account for adult survival and reproduction, which limits inference to dynamics of immature stages. An example is presented that focused on measuring the impact of bottom-up (plant quality) and top-down (natural enemies) effects on the mortality dynamics of B. tabaci in the cotton system.

Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System

Life tables allow quantification of the sources and rates of mortality in insect populations and contribute to understanding, predicting and manipulating population dynamics in agroecosystems. Methods for conducting and analyzing cohort-based life tables in the field for an insect with sessile immature life stages are presented.

Life tables provide a means of measuring the schedules of birth and death from populations over time. They also can be used to quantify the sources and ...

Preparation of DMMTAV and DMDTAV Using DMAV for Environmental Applications: Synthesis, Purification, and Confirmation

Dimethylated thioarsenicals such as dimethylmonothioarsinic acid (DMMTAV) and dimethyldithioarsinic acid (DMDTAV), which are produced by the metabolic pathway of dimethylarsinic acid (DMAV) thiolation, have been recently found in the environment as well as human organs. DMMTAV and DMDTAV can be quantified to determine the ecological effects of dimethylated thioarsenicals and their stability in environmental media. The synthesis method for these compounds is unstandardized, making replicating previous studies challenging. Furthermore, there is a lack of information about storage techniques, including storage of compounds without species transformation. Moreover, because only limited information about synthesis methods is available, there may be experimental difficulties in synthesizing standard chemicals and performing quantitative analysis. The protocol presented herein provides a practically modified synthesis method for the dimethylated thioarsenicals, DMMTAV and DMDTAV, and will help in the quantification of species separation analysis using high performance liquid chromatography in conjunction with inductively coupled plasma mass spectrometry (HPLC-ICP-MS). The experimental steps of this procedure were modified by focusing on the preparation of chemical reagents, filtration methods, and storage.

Preparation of DMMTAV and DMDTAV Using DMAV for Environmental Applications: Synthesis, Purification, and Confirmation

This article presents modified experimental protocols for dimethylmonothioarsinic acid (DMMTAV) and dimethyldithioarsinic acid (DMDTAV) synthesis, inducing dimethylarsinic acid (DMAV) thiolation through mixing of DMAV, Na2S, and H2SO4. The modified protocol provides an experimental guideline, thereby overcoming limitations of the synthesis steps that could have caused experimental failures in quantitative analysis.

Dimethylated thioarsenicals such as dimethylmonothioarsinic acid (DMMTAV) and dimethyldithioarsinic acid (DMDTAV), which are produced by the metabolic ...

Evaluating Dryocosmus Kuriphilus-induced Damage on Castanea Sativa

Dryocosmus kuriphilus Yasumatsu has become a major pest for Castaneasativa since its arrival in Europe. Its galling activity results in the formation of different gall types and prevents the development of normal shoots. Repeated and uncontrolled attacks cause, besides the production of galls and the attendant gall-related reduction in leaf area, progressive corruption of the branch architecture, including the death of branch parts, and an increase in dormant bud activation. Thus far, there have been few attempts to quantify branch architecture damage. Further, the different methods for assessing infestation degree (MAID) that have been developed focus only on the galls' presence and abundance.
Using the leaf area to sapwood area relationship as a green biomass indicator, we developed in a previous study a damage composite index (DCI) that takes into account the most important branch architectural features, allowing for realistic damage assessment during the entire epidemic process. 
The aim of this study is to present this novel method and highlight differences in the damage description with respect to other broadly used indices. Results show how the DCI depicts branch damage better, especially during the epidemic peak, compared to MAID, which tend to underestimate it. We conclude by suggesting how to properly evaluate the overall impact of the pest by means of our composite damage index, the infestation degree using classic methods, and crown transparency evaluations.

Evaluating Dryocosmus Kuriphilus-induced Damage on Castanea Sativa

It is common practice to assess the damage caused by Dryocosmus kuriphilus by considering the abundance of galls alone rather than by also taking related branch corruption into consideration. We propose a composite damage index that takes into account the most important branch features, thus enabling more realistic damage assessment.

Dryocosmus kuriphilus Yasumatsu has become a major pest for Castaneasativa since its arrival in Europe. Its galling activity results in the formation of ...

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it regulates the gravity-driven soil movement induced by runoff and tillage activities. The recent application of Light Detection and Ranging (LiDAR) data holds promise for generating high spatial resolution topographic metrics that can be used to investigate soil property variability. In this study, fifteen topographic metrics derived from LiDAR data were used to investigate topographic impacts on redistribution of soil and spatial distribution of soil organic carbon (SOC). Specifically, we explored the use of topographic principal components (TPCs) for characterizing topography metrics and stepwise principal component regression (SPCR) to develop topography-based soil erosion and SOC models at site and watershed scales. Performance of SPCR models was evaluated against stepwise ordinary least square regression (SOLSR) models. Results showed that SPCR models outperformed SOLSR models in predicting soil redistribution rates and SOC density at different spatial scales. Use of TPCs removes potential collinearity between individual input variables, and dimensionality reduction by principal component analysis (PCA) diminishes the risk of overfitting the prediction models. This study proposes a new approach for modeling soil redistribution across various spatial scales. For one application, access to private lands is often limited, and the need to extrapolate findings from representative study sites to larger settings that include private lands can be important.

Landscape processes are critical components of soil formation and play important roles in determining soil properties and spatial structure in landscapes. We propose a new approach using stepwise principal component regression to predict soil redistribution and soil organic carbon across various spatial scales.

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it ...

Studying Neurobehavioral Effects of Environmental Pollutants on Zebrafish Larvae

Recent years more and more environmental pollutants have been proved neurotoxic, especially at the early development stages of organisms. Zebrafish larvae are a preeminent model for the neurobehavioral study of environmental pollutants. Here, a detailed experimental protocol is provided for the evaluation of the neurotoxicity of environmental pollutants using zebrafish larvae, including the collection of the embryos, the exposure process, neurobehavioral indicators, the test process, and data analysis. Also, the culture environment, exposure process, and experimental conditions are discussed to ensure the success of the assay. The protocol has been used in the development of psychopathic drugs, research on environmental neurotoxic pollutants, and can be optimized to make corresponding studies or be helpful for mechanistic studies. The protocol demonstrates a clear operation process for studying neurobehavioral effects on zebrafish larvae and can reveal the effects of various neurotoxic substances or pollutants.

A detailed experimental protocol is presented in this paper for the evaluation of neurobehavioral toxicity of environmental pollutants using a zebrafish larvae model, including the exposure process and tests for neurobehavioral indicators.

Recent years more and more environmental pollutants have been proved neurotoxic, especially at the early development stages of organisms. Zebrafish larvae ...

Remote Sensing Evaluation of Two-spotted Spider Mite Damage on Greenhouse Cotton

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Chapters in this video

Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production

Application of Two-spotted Spider Mite Tetranychus urticae for Plant-pest Interaction Studies

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System

Preparation of DMMTA^V and DMDTA^V Using DMA^V for Environmental Applications: Synthesis, Purification, and Confirmation

Evaluating Dryocosmus Kuriphilus-induced Damage on Castanea Sativa

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Studying Neurobehavioral Effects of Environmental Pollutants on Zebrafish Larvae