High add valued application of turpentine in crop production through structural modification and qsar analysis

Article abstract of DOI:10.3390/molecules23020356

Turpentine is a volatile component of resin, which is an abundant forest resource in Southern China. As one of the most important components, the integrated application of-pinene has been studied. The broad-spectrum evaluation of -pinene and its analogues has, therefore, been necessary. In an attempt to expand the scope of agro-activity trials, the preparation and the evaluation of the herbicidal activity of a series of -pinene analogues against three agricultural herbs were carried out. In accordance with the overall herbicidal activity, it is noteworthy that compounds 6k, 6l, and 6m demonstrated extreme activity with IC50 values of 0.065, 0.065, and 0.052 mol active ingredients/hectare against E. crus-galli. The preliminary structure-activity relationship (SAR) was analyzed and the compounds with the appropriate volatility and substituent type that had beneficial herbicidal activity were analyzed. Simultaneously, the quantitative structure-activity relationship (QSAR) model was built and the most important structural features were indicated, which was, to a certain extent, in line with the SAR study. The study aimed to study the application of the forest resource turpentine in agriculture as a potential and alternative approach for comprehensive utilization.

Full text of DOI:10.3390/molecules23020356

molecules
Article
High Add Valued Application of Turpentine in Crop
Production through Structural Modification and
QSAR Analysis
Yanqing Gao 1,†, Jingjing Li 2,†, Jian Li 2,*, Zhanqian Song 3, Shibin Shang 3 and Xiaoping Rao 3
1
Research & Development Center of Biorational Pesticide, College of Plant Protection,
Northwest A&F University, Yangling 712100, Shaanxi, China; gaoyanqinggc@nwsuaf.edu.cn
Shaanxi Province Key Laboratory of Economic Plant Resources Development and Utilization,
2
College of Forestry, Northwest A&F University, Yangling 712100, Shaanxi, China; Lijingjing0355@163.com
Institute of Chemical Industry of Forest Products, Chinese Academy of Forestry, Nanjing 210042, Jiangsu,
3
China; lhssxly@hotmail.com (Z.S.); shangsb@hotmail.com (S.S.); rxping2001@163.com (X.R.)
*
Correspondence: ericlee99@nwsuaf.edu.cn; Tel.: +86-029-87082230
†
These authors contributed equally to this paper and share co-first authorship.
Received: 12 January 2018; Accepted: 6 February 2018; Published: 8 February 2018
Abstract: Turpentine is a volatile component of resin, which is an abundant forest resource in
Southern China. As one of the most important components, the integrated application of
has been studied. The broad-spectrum evaluation of -pinene and its analogues has, therefore, been
necessary. In an attempt to expand the scope of agro-activity trials, the preparation and the evaluation
of the herbicidal activity of a series of -pinene analogues against three agricultural herbs were
carried out. In accordance with the overall herbicidal activity, it is noteworthy that compounds 6k
β-pinene
β
β
,
6l, and 6m demonstrated extreme activity with IC50 values of 0.065, 0.065, and 0.052 mol active
ingredients/hectare against E. crus-galli. The preliminary structure–activity relationship (SAR)
was analyzed and the compounds with the appropriate volatility and substituent type that had
beneficial herbicidal activity were analyzed. Simultaneously, the quantitative structure–activity
relationship (QSAR) model was built and the most important structural features were indicated,
which was, to a certain extent, in line with the SAR study. The study aimed to study the
application of the forest resource turpentine in agriculture as a potential and alternative approach for
comprehensive utilization.
Keywords: turpentine; herbicidal activity; SAR; QSAR
1. Introduction
Weeds are considered worldwide as an infestation for crops. Some weed species interfere with
the production of grain and vegetables and severely reduce the yield and quality [
Echinochloa crus-galli is one of the world’s worst weeds because it can seize the available soil nitrogen
from the crop [ ]. Effective and integrated control of these noxious weeds is essential for modern
agriculture [ ]. However, the wide use of single-type herbicides causes the serious occurrence of
resistance weeds and a series of environmental issues [ ]. Therefore, developing more effective and
low toxic herbicides has become a priority for agriculture producers, researchers, and extension
personnel [ 10]. As an important alternative to replacing traditional herbicides, forest resources have
1]. Among them,
2
3
4
5–
attracted increasing attention from researchers due to their unique qualities, such as being widely
distributed, environmentally friendly, and diverse in chemical composition [11]. The acrylopimaric
acid-based botanical herbicides have been synthesized from forest resource rosin [
3]. The natural
herbicide activity of Satureja hortensis L., an essential oil against two important weed species, has been
Molecules 2018, 23, 356; doi:10.3390/molecules23020356
www.mdpi.com/journal/molecules

Molecules 2018, 23, 356
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reported [12]. Mansonone E has potential as a new natural pesticide for agricultural plant pathogen
management [13]. Therefore, taking advantage of forest resources for agriculture through chemical
structural modification is a viable solution for the production of new herbicides.
Resin, an abundant forest resource, is obtained from pines, which use it to resist external insect
bites and other damage. In the growth of plants, resin components (including pinene) play many
special roles, such as plant defense, plant interspecific phytochemical roles, attracting insects for
pollination, and so on. Just as plant secondary metabolites, resin is agriculturally active and the
high value-added application of resin is meaningful. In the complex chemical components of resin,
turpentine, a monoterpene mixture of volatile oil, has excellent performance and potential for use
in many fields. Turpentine has a high content of
However, studies on the biological activity of -pinene derivatives are not rich. Therefore, further
development of derivatives with bioactive properties using -pinene as a starting material is gradually
becoming a trend in turpentine processing and utilization. For instance, -pinene and its analogues
have agricultural activities, such as antifeedant, repellent, and antimicrobial properties [14 16].
β-pinene and the cost to isolate β-pinene is low.
β
β
β
–
The preparation of most compounds has been reported by us. Based on previous research, the reaction
process has been improved. In order to further study the impact of heteroatoms on the activity,
other novel heterocyclic compounds (6k
-pinene and its analogues is worthy of study in order to develop some ecofriendly herbicides that
can be applied in the control of noxious weeds.
–6n) have been synthesized [17,18]. The herbicidal activity of
β
In a program to design and synthesize herbicidal active substances via derivation of volatile
-pinene, there are many factors that need to be considered. First, the primary factor is the effective
β
contact between the herbicide and the treated soil [19]. In order to improve the permeability
(the penetration of the molecule through the plant epidermis, which is influenced by amphipathic
characteristics, and better the biphasic solubility) and reduce volatilization, ester and amino groups
were introduced into
mickle candidates for the weed control. QSAR, an efficient means to screen biological activity and
mechanisms of action, was carried out through quantification software packages [20 22]. After the
β-pinene. Second, new technology is needed to screen potential herbicides from
–
essential structural features for the activity have been defined, a study on the mechanisms of action
should be targeted. The objective of this study was to continue expanding the application of
volatile β-pinene in a high value-added field and to develop its broad-spectrum biological activity
in agriculture.
2. Results and Discussion
2.1. Synthesis of Derivatives of β-Pinene
The synthesis of two series of turpentine-based ester derivatives are shown in Schemes 1 and 2.
The preparation of most of these compounds has been reported by us and, based on previous research,
the reaction process has been improved. In order to further study the impact of heteroatoms on the
activity, other novel heterocyclic compounds (6k–6n) were synthesized. The dehydrocumic acid was
prepared from -pinene through reactions of alkaline oxidation, dehydration, and isomerization,
β
respectively. For the purpose of improving the reactivity of carboxylic acid, the dehydrocumic acid
was activated by thionyl chloride into acid chloride. In the synthesis process of oxime esters, some
of the intermediate oxime compounds have been prepared by us. In order to obtain a high yield,
the synthesis process was optimized by regulating the reaction temperature and the reaction solvent
and alkali. The optimal reaction conditions were ethanol as the reaction solvent, sodium carbonate as
the base, and 25 ◦C as the reaction temperature. The structures of the title compounds have been well
characterized by IR, 1H-NMR, MS, and elemental analysis.

Molecules 2018, 23, 356
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Scheme 1. Structure and chemical synthesis of the compounds 5a–5l.
Scheme 2. Structure and chemical synthesis of the compounds 6a–6n.
2.2. Herbicidal Activity and Structure–Activity Relationships (SARs)
In Supplementary Materials (Table S1), the herbicidal activities of compounds 5a–5l and 6a–6n
against E. crus-galli, Amaranthus retroflexus, and Brassica campestris L. var. amplexicaulis Makino were
screened primarily at 200 g active ingredients/hectare. It is shown that all of the ester and oxime
eater derivatives of
two herbs. From Table 1, the research on the herbicidal activity against E. crus-galli was done and the
analogues displayed good herbicidal activity, which was more significant compared with compound
It is noteworthy that compounds 6k 6l, and 6m demonstrated extreme activity with IC50 values
of 0.065, 0.065, and 0.052 mol active ingredients/hectare against E. crus-galli, which were similar
to that for sulfentrazone, a commercialized agriculture herbicide. For different types of -pinene
analogues, the level of herbicidal activity was oxime esters (6a 6n) > monoesters (5a 5l). Nevertheless,
β-pinene had good inhibition rates against E. crus-galli compared with another
3.
,
β
–
–
the environmental toxicology research on the newly synthesized compounds was very necessary.
On the one hand, in order to avoid pesticide residues of herbicides in the soil, water, and air,

Molecules 2018, 23, 356
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the chemical stability and products of metabolism of the candidates must be experimentally tested
under the influence of prolonged exposure to ambient temperature, sunlight, microflora or selected
microorganisms, and plants. On the other hand, the impact of herbicides on non-target organisms
such as bird, fish, and bees should also be assessed. Research in this area will be carried out in the
follow-up work.
Table 1. Herbicidal activity of compounds against E. crus-galli in a seed germination method.
Herbicidal Activity at a
Concentration of
IC50
(g Active Ingredients/Hectare)
log
IC50
R2
Compd.
y = a + bx
g Active
mol Active
200
100
50
25
12.5 Ingredients/ Ingredients/
Hectare
Hectare
3
5a
5b
5c
5d
5e
5f
5g
5h
5i
80
100
100
100
100
96
90
100
91
92
88
75
80
100
100
95
93
85
100
90
88
98
93
68
91
90
90
90
80
78
90
78
81
76
60
60
96
96
84
81
74
95
76
73
85
79
98
97
95
95
80
55
72
71
70
70
68
64
69
65
64
60
49
48
77
76
65
64
59
74
61
60
69
63
78
79
77
75
69
45
57
56
55
54
50
50
53
49
50
50
42
41
61
61
58
55
50
60
54
54
57
55
60
63
60
61
55
32
42
41
41
40
39
39
40
40
38
40
35
35
40
43
37
40
41
40
40
41
40
42
45
44
46
40
39
49.880
19.886
21.204
22.024
23.099
25.505
25.679
23.908
25.335
26.605
27.573
64.910
63.125
18.905
17.510
21.708
21.115
26.975
19.723
23.711
23.411
20.229
20.196
17.182
16.004
15.714
19.077
15.743
0.300
0.110
0.109
0.106
0.111
0.115
0.116
0.108
0.114
0.113
0.103
0.309
0.249
0.069
0.061
0.068
0.071
0.076
0.073
0.107
0.100
0.075
0.071
0.065
0.065
0.052
0.070
0.041
y = −0.643 + 0.011x 0.962 −0.523
y = −0.617 + 0.031x 0.991 −0.959
y = −0.643 + 0.030x 0.989 −0.963
y = −0.667 + 0.030x 0.993 −0.975
y = −0.712 + 0.031x 0.993 −0.955
y = −0.498 + 0.020x 0.983 −0.939
y = −0.373 + 0.015x 0.949 −0.936
y = −0.736 + 0.031x 0.996 −0.967
y = −0.383 + 0.015x 0.959 −0.943
y = −0.442 + 0.017x 0.951 −0.947
y = −0.360 + 0.013x 0.959 −0.987
y = −0.570 + 0.009x 0.972 −0.510
y = −0.656 + 0.010x 0.994 −0.604
y = −0.768 + 0.041x 0.990 −1.161
y = −0.674 + 0.038x 0.994 −1.215
y = −0.416 + 0.019x 0.954 −1.167
y = −0.345 + 0.016x 0.965 −1.149
y = −0.305 + 0.011x 0.950 −1.119
y = −0.738 + 0.037x 0.989 −1.137
y = −0.323 + 0.014x 0.967 −0.971
y = −0.282 + 0.012x 0.969 −1.000
y = −0.460 + 0.023x 0.990 −1.125
y = −0.314 + 0.016x 0.982 −1.149
y = −0.741 + 0.043x 0.993 −1.187
y = −0.665 + 0.042x 0.995 −1.187
y = −0.564 + 0.036x 0.998 −1.284
y = −0.719 + 0.038x 0.987 −1.155
y = −0.820 + 0.052x 0.999 −1.387
5j
5k
5l
6a
6b
6c
6d
6e
6f
6g
6h
6i
6j
6k
6l
6m
6n
100
100
100
100
Sulfentrazone 100
Values in columns followed by similar letters were not significantly different according to Fisher’s protected; LSD
test (P = 0.05).
In the process of herbicides playing a role, there are many factors that restrict the interaction with
the herbs. For instance, the suitable volatility and electrostatic interaction may be mainly affected [
In order to improve the volatility, the structure of the carboxylic acid (compound ) was modified with a
hydroxyl group to obtain ester analogues. From the activity data shown in Table 1, the shorter branched
chained compounds were intrinsically more toxic, for the monoesters compounds (5a 5l), and the
activity sequence was 5a 5b 5c 5d 5g 5i 5j 5k 5l. In light of the point of
5e ≈ 5f ≈ 5h
view of Li et al. and Fan et al. aliphatic compounds are more volatile than aromatic compounds, and the
volatility decreases with an increase in the molecular weight of the compounds [ 24]. Therefore, with
1,23].
3
–
>
>
>
>
>
>
>
>
>
8
,
regard to the same series of derivatives, along with the branched chain length increasing, the herbicidal
activity showed a downward trend, and a similar trend was observed with oxime esters compounds
(6a–6n). The electrostatic interaction of compounds is another important factor for herbicidal activity,
and the type and position of the substituent has a great impact on the electrostatic effect of the
compound. From investigations of the relationship of charge density and drug activity, the heteroatoms
N, O, and S can play electron-withdrawing or electron-donating actions. Therefore, heterocyclic
substituents such as thiophene, furan, and pyrrole were introduced to the derivatives. Based on the
activity results, the rough order of herbicidal activity was aromatic substituted compounds was higher

Molecules 2018, 23, 356
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than aliphatic substituted compounds, and specifically heterocyclic substituted compounds (6a, 6b, 6f,
6k, 6l, 6m and 6n) was higher than benzene substituted compounds (6c, 6d, 6i and 6j). As a preliminary
conclusion, during the molecules playing an effect on E. crus-galli, the ring of thiophene and furan
accepts the electron, which forms an electron transfer process with a protein or enzyme to achieve
the herbicidal effect. To sum up, the volatility and substituent type are two important compound
properties influencing the herbicidal activity.
2.3. QSAR Study on Herbicidal Activity Against E. crus-galli
There were six groups of descriptors that reflected all of the features of the compounds, such
as molecular composition, connectivity, 3D-coordinates, charge distribution, and quantum chemical
data. Through calculation and selection, several significant molecular descriptors were determined
during the model development process. The most important descriptors in this work were the
quantum-chemical descriptors. In an attempt to establish a relationship between activity and molecular
descriptors through several regression approaches, the heuristic regression was chosen to obtain a
QSAR model with satisfactory values of R2, F, and S2. Through the “breaking point” rule and the
number of molecular descriptors being no more than one-third of the sample number plus one,
the descriptor number was determined. The “breaking point” rule results are shown in Figure 1.
Finally, the four-descriptor QSAR model was determined as the best model and is shown in Table 2.
The four significant descriptors and their values are listed in the Supplementary Materials (Table S2).
Figure 1. The “breaking point” rule results. The black code indicates a statistically notable improvement
in the correlation coefficient, and the red code indicates it was not improving obviously.
Table 2. The best four-descriptor model.
Descriptor No.
X
±∆X
t-Test
Descriptor
−1
−4
−1
−2
−1
0
1
2
3
4
−4.5445
−2.5592 × 10
2.8334
7.7801 × 10
−3.4698 × 10
b
−6.1926
−11.0701
7.3116
7.0850
−2.2609
c
Intercept
7.3386 × 10
2.3118 × 10
3.8752 × 10
1.0981 × 10
1.5347 × 10
a
−3
−1
∆Hf b
Pµµ
µ c
−2
◦ d
qmax
a
d
Final heat of formation of atoms. Max atomic orbital electronic population. Tot dipole of the molecule. Max
net atomic charge for a O atom.
The final four-descriptor QSAR model contained the sample number N = 26, and had the following
statistical characteristics: R2 = 0.9428, F = 86.49, S2 = 0.0014. The experimental and predicted log
IC50 values are shown in Table 3, which were also compared in Figure 2. The following equation

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(Equation (1)) describes the four-descriptor QSAR model. In the model, a positive sign (+) indicates
that the descriptor value had a positive correlation with log IC50, and that the log IC50 value was higher
as the descriptor value was larger. In contrast, a negative sign (−) indicates a negative correlation.
◦
log IC50 = − 4.5445 − 0.0026 × ∆Hf + 2.8334 × Pµµ + 0.0778 × µ − 0.3470 × qmax
N = 26, R2 = 0.9428, F = 86.49, S2 = 0.0014
(1)
Figure 2. The comparison between experimental log IC50 and predicted log IC50
.
Table 3. The difference between the experimental log IC50 and predicted log IC50
.
No.
Compd.
Calc. Log IC50
Exp. Log IC50
Difference
1
2
3
4
5
6
7
8
5a
5b
5c
5d
5e
5f
5g
5h
5i
−0.884
−0.907
−0.926
−0.964
−0.942
−0.952
−0.975
−0.979
−0.949
−0.990
−0.534
−0.628
−1.163
−1.220
−1.023
−1.079
−1.102
−1.067
−1.011
−1.027
−1.183
−1.225
−1.152
−1.109
−1.338
−1.162
−0.959
−0.963
−0.975
−0.955
−0.939
−0.936
−0.967
−0.943
−0.947
−0.987
−0.510
−0.604
−1.161
−1.215
−1.167
−1.149
−1.119
−1.137
−0.971
−1.000
−1.125
−1.149
−1.187
−1.187
−1.284
−1.155
0.075
0.056
0.049
−0.009
−0.003
−0.016
−0.008
−0.036
−0.002
0.003
−0.024
−0.024
−0.002
−0.005
0.044
0.070
0.017
0.070
−0.040
−0.027
−0.058
−0.076
0.035
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
5j
5k
5l
6a
6b
6c
6d
6e
6f
6g
6h
6i
6j
6k
6l
6m
6n
0.078
−0.054
−0.007

Molecules 2018, 23, 356
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The validation of the established QSAR model was carried out by two validation methods.
The internal validation method was described as the compounds , etc. were assigned to group A;
compounds , etc. were assigned to group B. The other compounds belonged to subset C.
1, 4, 7
2, 5, 8
The training set was two of these three groups, and the test set was the other group. The values of
the corresponding test sets were predicted by the obtained correlation equation from the training
set using the identical descriptors. The results of the internal validation are listed in Supplementary
Materials (Table S3). The difference between RTraining2 and RTest2 for the three sets was tiny enough
to be ignored, and the average values of RTraining2 and RTest2 were essentially identical to the overall
R2 value, which meant the approving predictive power of the obtained model. In the “leave-one-out”
method, the compounds 1, 5, 9, etc. were the external test set and the others were the training set.
The R2 value of the training set and test set were close and the QSAR developed in this study had
good predictability.
With regard to the descriptors related to the QSAR model, the first important descriptor was the
heat of formation of the molecule (∆Hf), which gives the energy of the molecule in the thermodynamic
standard scale (elements in ideal gas state at 298.15 K and 101.325 Pa). It measures the change of
enthalpy during the formation of 1 mol of the compound from its constituent elements with all
substances in their standard states. This quantum-chemical descriptor indicates the level of reactivity
of the molecule and can find the standard enthalpy change of any reaction [21]. The value of
signifies the difficulty and heat change of the chemical reaction. A large absolute value Hf implies
a prone reaction and a negative value Hf means an exothermic reaction. The converse is also true.
From Equation (1), the ∆Hf value had a negative effect on log IC50 values.
∆Hf
∆
∆
The second important descriptor is the max atomic orbital electronic population (Pµµ), and it is
a simplified index to describe the nucleophilicity of a molecule. According to the molecular orbital
theory and frontier orbital theory, the highest occupied molecular orbital (HOMO) and the lowest
unoccupied orbital (LUMO) are influential on the activity of the molecule [21]. When a molecule
reacts with a target molecule, it occurs near the molecular front-orbital; therefore, the frontier orbital
energy can greatly affect the herbicidal activity of a molecule. The suitable values of HOMO and
LUMO are beneficial for the pesticide activity. From Figure 3, the frontier molecular orbitals (FMOs) of
compounds 6k, 6l, and 6m are shown, which indicate the highest occupied molecular orbital (HOMO)
and the lowest unoccupied molecular orbital (LUMO). The HOMO and LUMO of the molecule mainly
distribute in heterocyclic and benzene rings, which means that these active groups accept or provide
electrons during the interaction with the receptor.
Figure 3. The HOMO and LUMO energy maps for compounds 6k, 6l and 6m.

Molecules 2018, 23, 356
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The third most important descriptor in the model is the tot dipole of the molecule, which measures
the separation of positive and negative electrical charges within a molecule, that is, a measure of the
overall polarity of the molecule [23
magnitude of the dipole moment. In Figure 4, the molecular electrostatic potential and contour maps
of compounds 6k 6l and 6m are illustrated. The electron withdrawing substitute of O and S atoms,
,25,26]. The electric field strength of the dipole is proportional to the
,
demonstrated by the green parts, represents the positive molecular orbitals. The electron donating
substitute of N atoms shown in red, represents the negative molecular orbitals. From Equation (1),
the µ value has a positive influence on the herbicidal activity.
Figure 4. The molecular electrostatic potential and contour maps of compounds 6k, 6l and 6m.
The last important descriptor in the model is the max net atomic charge for an O atom. This
electrostatic descriptor reflects the characteristics of the charge distribution of the molecule and is
related to the strength of the intermolecular bonding interactions and characterizes the stability of the
molecules, their conformational flexibility, and the other valency-related properties [24,25]. Figure 5
shows the optimized geometries and charge distribution of compounds 6k, 6l and 6m.
Figure 5. The optimized geometries and charge distribution of compounds 6k, 6l and 6m.

Molecules 2018, 23, 356
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3. Materials and Methods
3.1. Synthesis and Characterizations
β
-pinene (
a commercial source. All the other chemicals used in the synthesis were of reagent grade and the
purity was chemically pure ( 99.5%). A Nicolet IS 10 spectrophotometer (Thermo Nicolet Co., Ltd.,
1) was obtained from Jiangxi Jishui Hongda Natural Spices Ltd. (Jishui, China) of
≥
Madison, WI, USA) was used for the Fourier transform infrared (FT-IR) spectra. A Bruker AV-300
nuclear magnetic resonance spectrometer (Bruker Co., Ltd., Karlsruhe, Germany) was used to measure
the 1H-NMR spectra. An Agilent-5973 spectrophotometer was (Agilent Technologies Inc., Santa Clara,
CA, USA) utilized for the MS spectra. A Bruker Q-TOF mass spectrometer (Bruker Bruker Co., Ltd.,
Karlsruhe, Germany) equipped with an electro spray ionization source was applied for ESI mass
spectral data. Thin-layer chromatography (TLC) was employed to monitor the progress of reactions
and determine the reaction’s end, which was carried out on Merck silica gel 60 GF254 plates (Qingdao
Bangkai Hi-Tech Materials Co., Ltd., Qingdao, China) with eluent of petroleum ether/ethylacetate
(v/v = 8:1). The preparation and the structures of title compounds are shown in Schemes 1 and 2.
3.1.1. Synthesis of 4-Isopropylcyclohexa-1,3-dienecarboxylic acid (Dehydrocumic acid, 3)
β
-pinene was used as the raw material. Through alkaline oxidation, dehydration, and isomerism,
the nopinic acid ( ) and dehydrocumic acid ( ) were prepared according to the method described
previously [24]. During this process, the colorless crystal of was obtained by recrystallization
with organic solvent (such as ethanol or toluene) [25]. After dehydration and isomerization with
concentrated sulfuric acid, the hydroxyl of the carboxylic acid was eliminated and the crude product
was obtained, which was used in the subsequent reaction after purification by recrystallization. Crystal
Data for C10H16O3 (compound , M = 184.23 g/mol): monoclinic, a = 26.796 (5) Å, b = 6.6560 (13) Å,
c = 12.250 (3) Å, = 112.23 (3)
, V = 2022.5 (9) Å3, Z = 8, = 0.009 mm−1, T = 293 K, R [F2 > 2σ (F2)] = 0.056
wR (F2) = 0.153, S = 1.00, λ = 0.71073 Å, F000 = 800.
2
3
2
3
2
β
º
µ
,
3.1.2. Synthesis of 4-Isopropylcyclohexa-1, 3-dienecarboxylates (Compounds 5a–5l)
From the lead compound , the 12 resulting compounds 5a 5l were obtained by an esterification
3
–
reaction between dehydrocumic acid chloride and the corresponding alcohols [26].
3.1.3. Synthesis of Oximyl 4-Isopropylcyclohexa-1,3-dienecarboxylates (Compounds 6a–6n)
From the lead compound 3, the 14 resulting compounds 6a–6n were obtained by an esterification
reaction between dehydrocumic acid chloride and the corresponding oximes [8].
3.2. Herbicidal Activity Assay of β-Pinene Analogues
β
-pinene analogues were evaluated for herbicidal activity of the representative monocotyledonous
weed E. crus-galli and the dicotyledonous weeds A. retroflexus and B. campestris L. The herbs were
grown in a greenhouse and the test method was the conventional plate method (in vitro) [25 27]. In the
–
evaluation, all of the test compounds were dissolved in mixed solution of DMF and distilled water
(v/v = 8:1). The inhibition percentage of seed germination was the mean value obtained through three
independent experiments and the standard deviation (SD) values were limited within
±
5%. On the
basis of the series inhibition percentage, the IC50 results were calculated by the SPSS statistics program
version 17.0 (SPSS Inc., Chicago, IL, USA). For stringency, the commercial herbicide sulfentrazone
(Shanghai Aladdin Bio-Chem Technology Co., Ltd., Shanghai, China) was chosen as the positive
control, and a pure solution without test compound was tested as the negative control.
The initial concentration was set at 200 g active ingredients/hectare and the lower required
concentrations were diluted with water (100, 50, 25 and 12.5 g active ingredients/hectare). For better
dispersion all the solutions were prepared with Tween (final concentration 0.1%) as surfactant. In petri

Molecules 2018, 23, 356
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dishes of 9 cm diameter, 2 pieces of filter paper were placed and 2 mL test compound solution with
certain concentrations was sprayed evenly. For the accuracy of the results, the negative control was the
same amount of DMF mixed with Tween-80 and water. Ten just-sprouting seeds of each weed species
including E. crus-galli, A. retroflexus and B. campestris L. were grown in the test plate and allowed to
germinate for 72 h at 28
±
1 ◦C. Finally, the average values of the height of the ground portion of the
above mentioned seedlings growing in each plate were calculated. For reproducibility and credibility,
all of the tests at each concentration were repeated three times. The inhibition percentage (IP) was
used to describe the control efficiency of the compounds and was calculated according to Equation (2):
IP (%) = [(H0 − H1)]/H0 × 100
(2)
where H0 is the height of control test and H1 is the height of treated test. Through regression analysis
using SPSS Statistics 17.0, the IC50 values were calculated by the inhibition percentage of E. crus-galli at
five concentrations for each test compound [28].
3.3. Building and Verification of the Quantitative Structure–Activity Relationship (QSAR) Model
The QSAR model was built and validated in accordance with the common procedure. Briefly,
optimization of the most stable configuration was obtained with a Gaussian 03W package of programs
(Gaussian Inc., Wallingford, CT, USA,), and all the molecular descriptors were calculated by CODESSA
2.7.15 (The copyright of this version is held by the Center of Heterocyclic Chemistry, University of
Florida.) [29]. The “breaking point” rule for determining the number of the descriptors is described in
Figure 1. The best multilinear regression showed a significant increase in R2 when the number of the
descriptors was less than or equal to 4. However, there was negligible change in R2 when the number
of descriptors increased from 4 to 5. Descriptors with high t values were accepted and those with low t
values were rejected. A “breaking point” indicates that the improvement of the regression model has
become non-significant (R2 < 0.02-0.04). For the determination of the most significant structural features
of herbicidal activity against E. crus-galli, the heuristic analysis was to build the QSAR model. During
the model development process, the related statistical parameters (R2, S2 and F) were determined to
assess the predictability of a given model. In this study, a model displaying good predictability between
the compounds’ structures and the log IC50 values was developed. To ensure high quality of the final
QSAR results, two verification methods, internal validation, and the “leave-one-out” cross-validation
were used for determination [30].
4. Conclusions
In order to expand the efficient application of the forest resource
β-pinene to agriculture, two
series of -pinene analogues—ester and oxime esters—were prepared with suitable volatility and
β
a substituent type through structural modification. The herbicidal activity against E. crus-galli,
A. retroflexus and B. campestris L. was evaluated. Among them, the activity against E. crus-galli was more
ideal; therefore, a study on the structure–activity relationship (SAR) against E. crus-galli was focused on.
The preliminary conclusion is that compounds with esterification modification and a short chain length
are beneficial for herbicidal activity. In addition, the heteroatoms N, O and S can play an active role.
Simultaneously, the quantitative structure–activity relationship (QSAR) model (R2 = 0.9428, F = 86.49,
S2 = 0.0014) was built and indicates that the most important structural feature is the heat of formation
of the molecule (
the better application of volatile
∆
Hf). In view of these results, for the further exploitation of ecofriendly herbicides and
-pinene, short chain esters, and heterocyclic-substituted derivatives
β
could be the direction of the future development of new structures. It is noteworthy that environmental
toxicology should be focused on in future work.
Supplementary Materials: The following are available online. IR, 1H-NMR, MS and elemental analysis data for
the target compounds. The herbicidal activity and structure descriptors of the title compounds are also available
as supplementary information.

Molecules 2018, 23, 356
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Acknowledgments: The Excellent Young Teacher Training Program of the College of Forestry, Northwest A&F
University (Project No. Z111021604) provided financial support for this research.
Author Contributions: Jian Li designed the experiments and research; Yanqing Gao and Jingjing Li performed
experiments and contributed to the writing of the manuscript; Zhanqian Song, Shibin Shang and Xiaoping Rao
analyzed the data. All authors read and approved the final manuscript.
Conflicts of Interest: The authors declare no conflict of interest.
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2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
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