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Risk Evaluation of Main Pests and Integrated Management in Chinese Wolfberry Lycium barbarum L.

Byline: Junhe Liu Abid Ali Mingfu Yu Fengyun Zhu and Dawit Kidane

Abstract

Chinese wolfberry Lycium barbarum L. (Solanales: Solanaceae) is an ancient herbal medicine and has been used for years in China. However insect pests associated with this plant had not yet been well studied. The present study characterized the main pests associated with this plant. The method of risk assessment indices and the method of experience formulae were used to analyze the risk of pests under different management systems. The result demonstrates most frequent incidental and general insect pest in abandoned organic and conventional fields. Analyses using CANCORR showed that the dynamics of pest populations were similar in all fields under different management system. Moreover the matrices of correlation coefficients showed that dynamics of pests were significantly correlated.

The correlation coefficients in dichotomous pattern viz. the abandoned field and the conventional field the abandoned field and the organic field the conventional field and the organic field were 0.8504 0.8447 and 0.8564 respectively. Dynamics of the populations showed that the frequent disaster pests had two population establishment stages and one exponential growth stage in a year. The optimal controlling stages were from late part of the infancy period to early part of outbreak I period middle of outbreak I period and from late part of dormancy period to early of outbreak II period. These were the key periods to control pest outbreak. The implications of these results are discussed.

Keywords: Chinese wolfberry field; control strategies; disaster pests; optimal separations; risk assessment.

INTRODUCTION

Lycium barbarum L. (Solanales: Solanacae) is a famous Chinese herbal medicine and a healthy food. In 2007 Ningxia cultivation area of L. barbarum was 12006 mha (million hectares) Inner Mongolia 29681 mha Xinjiang 9671 mha. L. barbarum accounts for about 30% of cultivated area in China 50% of the country's output and 62% of the export volume. L. barbarum industry has become the main industry of Ningxia. L. barbarum products have become important brand names in China. With the continuous development of L. barbarum industry the pests also become increasingly serious. The outbreak of insect pests seriously reduces the yield and quality of Chinese wolfberry bringing huge economic losses to farmers. The risk assessment of harmful organisms was developed in the late 1970s.

More studies were concentrated on the risk and the structure of community characteristics (Li et al. 1998; Solomon and Sibley 2000; Liang et al. 2006) seasonal variations of zooplankton species (Yagci 2014) but most researches were on a single invasive species (Wang et al. 2003; Du et al. 2005; Chen et al. 2007; Yang et al. 2007) or ecosystem risk (Bai et al. 2002; Inamura et al. 2003; Lu et al. 2003; Ren et al. 2008). FAO/ISPM has stipulated the pest risk analysis (PRA) standard procedure in 2001.

There were a number of studies about prevention and control strategies especially in the structure of community characteristic and control of the natural enemies (Ge et al. 2002); but studies from sub-community aspect have been conducted in scanty. Based on 5 risk aspects of these pests including their distribution area degrees of harm the number and species of natural enemies the biological characteristics of pests and ecological characteristics for the first time this paper analyses the comprehensive degree of harm from all kinds of sub-community pests in Chinese wolfberry fields. We examined the characteristics of different pests proposed control measures revealed the mechanism of the pest and from this theory-based approach provided evidence for pest control and risk analysis.

MATERIALS AND METHODS

Sampling sites Conventional field Gardens of Yinchuan are located in 3834'- 36'N1068'-10'E the soil is alkaline mountain sierozem 10 year old tree better management better tree potential use pesticides 12 times a year mainly abamectin imidacloprid chemical pesticide chlorpyrifos etc.

Organic field

Ningxia Forestry Academy of Sciences organic Chinese wolfberry base (Organic Food Development and Certification Center-OFDC certification 3834'-36'N10611'-13'E the soil is alkaline mountain sierozem 7 years old better management better tree potential use pesticides 8 times a year mainly azadirachtin Li reed alkali rotenone and sulfur rubber suspension agent.

Abandoned field

Ningxia Forestry Academy of Sciences Chinese wolfberry experiments center 3827'- 28'N10612'-13'E the soil is ash brown 6 years old poor management the trees grew well pesticides. All trees species are L. barbarum variety (Ningqi 1st) spacing 1m x 3m from 2007 making a system census for different artificial interference conditions Chinese wolfberry fields every 10 days from April to November.

Survey methods

A board type 5 random sampling method (Gao and Pang 2006) was used according to the characteristics of Chinese wolfberry trees. Each tree was divided into 5 areas: east south west north and center. In each area one representative branch was chosen giving priority to branches that were longer than 40 cm. We used visual estimation and sweeping net to investigate insect species and individuals. The type and number of insects in the range were noted visually. The common types were recorded; the rare types add the labels. The collected larvae were kept in a bottle and fed until they developed into adults and identified. Insects were also collected using sweep nets (50 sweeps) under the trees. The collected insects were placed into the killing bottles and taken to the laboratory for proper identification. Moreover the type and number of insects were also recorded. Gall mites were also collected.

One representative branch in each direction was brought back to the laboratory and fruits were dissected for insect inspection then after all the arthropods were weighed.

Data sources

All of the original data were checked by statistical yearbook government departments and research institutions. Distribution of pests in Chinese wolfberry growing area (P1) and degree of attention (P24) (derived from the Ningxia Academy of Agricultural Sciences Institute of Chinese wolfberry). The potential economic damage (P21) spread diseases and caused serious reactions of crops (P23) and capacity of migration and proliferation (P42) derived from the Ningxia Academy of Agriculture and Forestry Research Institute of plant protection it's nearly 50 years of Chinese wolfberry material and research achievements.

Capacity of adaptability (P43) was collected from climate data of Ningxia Meteorological Bureau 1958-1990 statistical year book while hazard sites (P22) individuals of one host (P31) average weight (P32) and life (P33) of different pests generation of one year (P34) species (P51) and individuals (P52) of natural enemies in one host were derived from experimental investigation and laboratory test.

Analysis of risk sources

Risk sources involved in the community pest evaluation might be caused by an effect of the attributes of the pests and environmental factors. Attributes of the pests are decided by distribution biological characteristics ecological characteristics and degree of damage. Environmental factors are concerned with the property of soil vegetation situation and agricultural tillage conditions pesticide selection pressure competition between species predation parasitism and mutual benefits (Harvey and Clouston 1999; Landis 2003; Iiyama et al. 2005).

Analysis of historical data

Historical data were analyzed using the following indexes (P1) pest distribution range. This is the index of evaluating pest distribution representing the adaptability of pests; degree of harm (P2) is an index evaluating damage done by the pest; biological characteristics (P3); ecological characteristics (P4) P4 is the main index which determine the damage degree of pest insects; predation and parasitic effects (P5) this is affected by the species of natural enemies present and the size of their populations and can have a strong influence on the degree of pest damage. It can be used as an index of evaluating pest risk. Soil characteristics and vegetation conditions have an indirect effect on pests. Human interference in a farmland ecosystem is large and very unstable so it is not considered.

Use of pesticides is common and very hard to standardize so this is not considered; Interactions between species competition and mutual benefit relationships is changeable and does not play a major role on the harm of pests in agricultural ecosystems.

Qualitative analysis and evaluation index

This includes analysis of the risk source of agricultural damage determining judgment indicators of risk assessment and establishment of evaluation standards (Table I).

Quantitative indicators

Index method of pest risk

Using a large number of data analyses a pest risk assessment of comprehensive indicators system was established (Landis 2003; Su et al. 2005) (Fig.1) which was divided into two systems five aspects and fourteen indices. The indices were then quantified and at the same time these numbers were combined using the Analytical Hierarchical Process (AHP) method (Swanson 1998; Sydelko et al. 2001) to obtain the weighted scores. The scores from left to right were 0.079 0.103 0.059 0.062 0.034 0.104 0.052 0.088 0.042 0.091 0.079 0.057 0.051 and 0.099.

R=SPiA-P

Where R is consistency ratio P is index value and Pi is weight. Using the classification standard (Table II) the weighted pest risk index" evaluated the relative size of different pest risks in the community in order to calculate the degree of risk of community pests by sample surveys.

Empirical formula method

After the comprehensive system was used to assign values to each index considering that pest risk is closely related to individual number In1 weight W average life L generations of a year G migration ability M transmitted disease D distribution area S harm location P natural enemy species N and number In2" the empirical formula method was used to calculate risk value DP (Table III).

DP = In1A-WA-LA-GA-S A-MA-DA-P/ In2A-N

Pest sub-community analysis method

For optimal separation the main pest individual number in each investigation was used as the original data matrix (Gao 1998; Gao and Pang 2006). The different values were calculated from the various separation methods separated by time the smallest different value is the most similar segment within the community. Finally the optimal separation number and separation points were determined by the total variation.

Canonical correlation analysis

Taking Chinese wolfberry field pests sub- community as variables in the different management systems typical correlation analysis was done for abandoned field and conventional field abandoned field and organic field conventional field and organic field taking the correlation coefficient of each first pair of canonical variables.

All the data processing analysis and mapping were processed by Microsoft Office Excel 2003 Microsoft Office Word 2003 and SAS 8.2.

RESULTS

Risk analysis of main pests in different managements

Pest risk index method

In the abandoned field Aceria palida Keifer Aphis sp. Paratrioza sinica Yang and Li were the frequent disaster pests. Lema decempunctata Gebler Jaapiella sp. Nycteola asiatica and Phthorimaea sp. were the incidental disaster pests. Psilothrips indicus Bhatti Lygus sp. L. pratensis Epithrix sp. Aculops lycii Kuang Scotogramma trifolli (Rottemberg) Psylliodes obscurofaciata Chen and

Table I.- Judgment indicators and evaluation standard of pests sub-community's risk assessment.

Number###Judgment indicator###Evaluation standard

P1###Distribution of pests in Chinese###Distribution of pests accounted for the distribution of Chinese wolfberry

###wolfberry growing area###growing area. Beyond 80% P1=4; between 50%-80% P1=3; between

###20%-50% P1=2; under 20% P1=1

P21###The potential economic damage###Production losses caused by pests. Beyond 30% P21=4; between 10%-

###30% P21= 3; between 1%-10% P21=2; under 1% P21=1

P22###Hazard sites###Borers-fruit pests P22=4; flower-feeding and fruit-feeding pests P22=3 ;

###leaf-feeding pests P22=2; piercing sucking pests P22=1

P23###Spread diseases and caused serious###Spread disease and caused serious reactions of crops. Beyond 3 P23=4;

###reactions of crops###between 2-3; P23=3; only 1P23=2not spread disease P23=1

P24###Degree of attention###Area of treatment target in Chinese wolfberry growing area. Beyond 80%

###P24=4; between 50%-80% P24=3; between 20%-50% P24=2;under 20%

###P24=1

P31###Individuals of one host###Individuals of one host through 15 investigation. Beyond 10000 P31=4;

###between 1000-10000 P31=3; between 100-1000 P31=2; under 100

###P31=1

P32###Average weight of different pests###Average weight of different pests. Beyond 0.5g P32=4; between 0.5g-

###0.1g P32=3; between 0.05g-0.1g P32=2; under 0.05g P32=1

P33###Average life of different pests###Average life of different pests. Beyond 60d P33=4; between 40d-60d

###P33=3; between 20d-40d P33=2; under 20d P33=1

P34###Generation of one year###Generation of one year. Beyond 10 P34=4 between 5-10 P34=3; between

###2-5 P34=2; under 2 P34=1

P41###Time of hazard###Time of hazard. Beyond 140d P41=4 between 100d-140d P41=3;

###between 50d-100d P41=2under 50d P41=1

P42###Capacity of migration and###Strong long-distance migration capacity or proliferation in air P41=4;

###proliferation###Middle-distance migration P42=3; migration by attaching to flying insects

###or birds P42= 2 migration by crawling P42=1

P43###Capacity of adaptability###Region of appropriate growth and reproduction account for the distribution

###of Chinese wolfberry growing area. Beyond 80% P43=4 between 50-

###80% P43= 3; between 20%-50% P43=2 under 20% P43=1

P51###Species of natural enemies in one host###Species of natural enemies in one host. Under 5 P51=4 between 5-10

###P51=3 between 10-15 P51=2 beyond 15 P51=1.

P52###Individuals of natural enemies in one###Individuals of natural enemies in one host. Under 20 P52=4 between 50-

###host###100 P52=3 between 20-50 P52=2 beyond 100 P52= 1

Table II.- Classification standard of pest risk index.

Classification###Frequent###Incidental###General

standard###disaster###disaster###pests

###pests###pests

Pest risk###X1 2###1.8 X2 2###1.8

index

Experience###X1 1700###1000 X2###X31000

formula index###1700

Phthorimaea sp. were general pests. In the conventional field A. palida Aphis sp. P. sinica and P. indicus were the frequent disaster pests while Jaapiella sp. and Phthorimaea sp. were the incidental disaster pests and all were general pests. In the organic field the frequent disaster pests were same as in the abandoned field but P. indicus Jaapiella sp. and Phthorimaea sp. were the incidental disaster pests and others were general pests (Table III).

Table III.-###Risk assessment of pest - the method of risk assessment indices and experience formula.

###Abandoned field###Conventional field###Organic field

###Scientific name

###formula###indices###formula###indices###formula###Indices

Aceria palida Keifer###1944###2.18###1536###2.29###3072###2.29

Aphis sp.###2048###2.18###2048###2.18###2048###2.05

Paratrioza sinica Yang and Li###1024###2.06###1024###2.06###1024###2.19

Lema decempunctata Gebler###1728###1.86###432###1.40###432###1.4

Jaapiella sp.###648###1.84###648###1.84###648###1.84

Phthorimaea sp.###96###1.80###288###1.86###288###1.86

Neoceratitis asiatica Becker###576###1.80###96###1.45###96###1.45

Psilothrips indicus Bhatti###324###1.73###1296###2.03###1296###1.88

Lygus sp.###576###1.57###288###1.47###288###1.47

Lygus pratensis L.###384###1.59###288###1.49###576###1.74

Epithrix sp.###216###1.56###72###1.21###72###1.21

Aculops lycii Kuang###48###1.43###24###1.18###24###1.13

Scotogramma trifolli Rottemberg###192###1.03###96###0.85###192###0.86

Psylliodes obscurofaciata Chen###144###0.93###48###0.93###48###0.68

Phthorimaea sp.###96###0.82###288###1.12###288###1.09

Empirical formula method

In the abandoned field Aphis sp A. palida L. decempunctata were the frequent disaster pests while Phthorimaea sp. and P. sinica Jaapiella sp. were the incidental disaster pests and N. asiatica Lygus spp. Lygus pratensis (L.) P. indicus Epithrix sp. and A. lycii were the general pests. In the conventional field Aphis sp. A. palida P. indicus and P. sinica were the frequent disaster pests Jaapiella sp. and Phthorimaea sp. were the incidental disaster of pests the others were general pests. In the organic field A. palida Aphis sp. and P. indicus P. sinica were the frequent disaster pests Jaapiella sp. Phthorimaea sp. and P. indicus were the incidental disaster of pests the others were general pests (Table III).

Optimal separation of pest sub-community in different managements

The optimal separation method was used to deal with different management of Chinese wolfberry field pest sub-community separately to obtain the total variation of each section in each community (Table IV) and to analyze the determination of pest sub-communities in species composition and quantitative changes. After the 5 paragraph separation different management of Chinese wolfberry fields pest sub-community within the total variation gently declined pest community total variation was more than 9.11 before 5 paragraph separation after 5 paragraph separation pest community total variation was less than 4.9 different management of Chinese wolfberry fields pest sub-community change rules are basically the same so we can conclude that the optimal separation number is 5.

In the infancy stage (from March 28 to April 15) the weather gets warmer the soil is thawing Chinese wolfberry begins to sprout psyllids (jumping plant lice) climbing a tree to reproduce is the most representative characteristic of this stage other pests have not appeared. During the outbreak I period (from April 15 to July 18) the weather continues to warm the abandoned field marked by L. decempunctata appearing massively and reproducing organic field and conventional fields are marked by A. palida starting to climb the tree to feed. Following this L. pratensis Jaapiella sp. N. asiatica etc. a large number of pests climb the tree to feed this period is the key period of for Chinese wolfberry pest control. During the dormancy period (from July 18 to September 5) the weather is hot; it is rainy season marked by the greatly reduced Aphis sp. population the other pests population decrease in size.

This period does not need pesticide control except for A. palida that sometimes damage trees. The other pest population was too small to cause any harm. The outbreak II period (from September 5 to October 15) is marked by the Aphis sp. population size rises again L. pratensis and N. asiatica also begin to increase moving into the second prevention and cure key period.

Table IV.- Optimal separations of pests sub-communities in different management of Chinese wolfberry fields.

Stage###Abandoned###Conventional###Organic

numbers###field###field###field

2###73.58###50.49###59.89

3###60.35###41.41###49.12

4###51.34###35.22###41.79

5###42.35###27.74###34.28

6###37.25###22.24###30.13

7###33.35###19.57###27.96

8###28.25###16.24###24.13

9###26.35###14.57###21.96

10###23.62###11.01###18.92

11###20.35###9.76###15.26

12###17.51###7.13###13.13

13###14.96###6.69###11.24

14###12.36###5.54###9.51

15###9.32###4.78###7.21

16###6.35###3.04###5.98

17###3.62###2.08###2.94

18###1.62###1.11###1.31

19###0.85###0.77###0.92

20###0.35###0.24###0.28

21###0###0###0

The recession period (after October 15) is marked by decreasing the Aphis sp. population and vanishing of other kinds of pests. Aphis sp. produce eggs for surviving the winter A. palida crawl enter the branches to overwinter the arthropod community is in decline.

Control strategies and methods

Relevance of pest sub-community in different managements

Correlation matrices of pest sub-community in different management of Chinese wolfberry fields were analyzed. Abandoned field and conventional field abandoned field and organic field conventional field and organic field pest sub- community correlation coefficients were significant with 0.85 0.84 and 0.86 respectively. This indicated that the pest population dynamics of the pest sub-community in different Chinese wolfberry Determination of optimal control period According to the study of main pests in different Chinese wolfberry garden and the result of optimal separation A. palida Aphis sp. and P. sinica P. indicus are the most significant barriers to agricultural production. The Jaapiella sp. and Phthorimaea sp. may harm agricultural production of the Chinese wolfberry unexpectedly the rest insect pests would not cause significant harm at present.

The disaster pest population dynamic curves under different management of Chinese wolfberry gardens are consistent. Around April 20 the pests started to damage trees by the end of May to the early July the population expanded dramatically the individual number was grown exponentially this period lasted for a long time and caused the most harm. At the beginning of July population levels started to decline and in middle of July to the beginning of September did not cause damage. At the beginning of September the population levels of Aphis sp. began to rise again harming the autumn fruit harvest and at the beginning of October various pest populations drop quickly. On April 20 the gardens would be closed for prevention and cure and as Chinese wolfberry budding began a variety of pests started to damage the trees in succession which is the first building stage of Chinese wolfberry pests.

After June 5 the temperature continued to rise Aphis sp. P. indicus and A. palida propagated massively resulting in sharp increases in population size which was the exponential growth period of Chinese wolfberry pests. Around September 15 Chinese wolfberry went through the dormancy period Aphis sp. as the pest representative entered the Chinese wolfberry garden again populations quantity rose again in succession which was the second building group stage and population growth period of Chinese wolfberry pests.

As the weather conditions are different every year climate changes vary greatly. Therefore it is best to control and cure the pest at the two period of time both the pest grow exponentially early period and the first group build period the first period is the later stage of infancy period of Chinese wolfberry to early stage of the first group build period of pest the second period is the later stage of the dormancy period of Chinese wolfberry to early stage of the outbreak period of pest.

DISCUSSION

We created an insect comprehensive evaluation system for Chinese wolfberry and suggest the use of 2 sub-systems 5 aspects and 14 indicators to reflect the integrated damage force of various pests. The key of risk assessment is the analysis of the risk source (Berlin et al. 2000; Sydelko et al. 2001; Inamura et al. 2003) and this paper analyses the influence of pest damage from the biological properties and environmental conditions in the two sub-systems excluding the smaller effecting factors based on the five aspects of pest distribution areas the biological characteristics of pests ecological characteristics degree of harm the number and kinds of natural enemies and 14 indicators for evaluation. The results are almost the same with actual observation results in Chinese wolfberry gardens showing that the pest assessment system is applicable to Chinese wolfberry garden pest risk assessment but whether it can be applied to other field pest sub-communities remains to be determined.

The results of the pest risk index method and empirical formula method were in substantial agreement. The two pest classification standard for Chinese wolfberry garden pest sub-community calculation results may be inconsistent with pests sub-community graduation standard for other plants therefore an independent graduation standard for each field pests sub-community should be established when establishing a risk assessment.

Since the farmland ecosystem is a highly people-centered production system vegetation conditions are very simple we opine that pest control should suppress the establishment of disastrous pest populations and the key for effective control is to seize the most suitable control period. Pest's sub-community separated chronologically into 5 optimal separations: the infancy period the outbreak I period the dormancy period the outbreak II period and the recession period. As the weather conditions change every year climate can change greatly in a year therefore identifying the two building groups the early period and exponential growth early period is the best prevention and cure periods. Since yearly climate temperature may change greatly the timing of these periods may be advanced or delayed. So in reality we should depend on local conditions analyze and take timely effective measures.

ACKNOWLEDGEMENTS

We thank Dahan He and Rong Zhang (Ningxia University China) for critical comments on an earlier version of the manuscript thank to Dr Zihua Zhao (CAS China) for helping in data analysis and we also thank to D. M. Mager for English editing. We extend our thanks to the farmers who allowed us to use their fields for this series of experiments. Funding for this study was provided by Henan Province Science and Technology (Grant#132102110021 142300410007 and 142 102110028) and the Key Teacher Support Program of Henan University (Grant# 2012GGJS-219).

Conflict of interest declaration

The authors have declared that no conflicts of interest exist.

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