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Bagworm is the most important insect defoliator of oil palm. The bagworm larvae scrape off the leaflets’ epidermis while the older larvae chew the leaflets and leaving multiple holes and causes the palm to lose its photosynthetic capability. A bagworm census should be carried out quickly to determine the extent of damage. However, the conventional practices are heavily dependent on in-situ data collection, which is destructive, less efficient, laborious, and costly. Recently, many studies have incorporated machine learning analysis such as artificial neural network (ANN) in agricultural fields especially in the development of pest prediction model. Therefore, this study was conducted to develop a weather-based bagworm prediction model using ANN-Feature Selection method. Bagworm censuses were done by identifying Metisa plana’s larval stage 1 (L1) to 7 (L7) from 13 random palms by cutting off frond number 17 biweekly and weather data was recorded by installing weather station in an oil palm plantation belongs to TH Plantation Berhad in Muadzam Shah, Pahang, Malaysia from July 2016 to June 2017. The results revealed that the significant weather parameters were frequent at time-lag 12. All the larval stage prediction models from ANN-Feature Selection were able to produce satisfactory R2 values ranging from 0.526 to 0.995. The best model was the L1 model with R2 value of 0.985 and the accuracy of more than 90%.

This paper reports a study on genetic identification of Parthenium hysterophorus and the ability of P. hysterophorus crude extract (PHCE) to inhibit germination of weeds in palm oil plantations, particularly slender buttonweed (Diodia ocimifolia). Parthenium hysterophorus is a noxious plant with invasive properties. It has become one of the world’s seven most devastating and hazardous weed s due to its allelopathic properties. However, a compre hensive study on its genetic identification and its herbicidal activity against weeds in palm oil plantations had never been carried out. In the present study, internal transcribes spacer (ITS) region-based analysis was used as a molecular marker to ascertain the local Rumput Miang Mexico (RMM) as a P. hysterophorus species. From the results, the DNA sequence obtained was 99% matched with P. hysterophorus species database. In the dose-response bioassay study, the phytotoxicity of PHCE on D. ocimifolia was simulated under laboratory conditions. Methanolic extract of P. hysterophorus significantly inhibited germination and growth of shoots and radicles of D. ocimifolia at low concentrations (1−5 g ∙ l−1). A study on the herbicidal activity of PHCE could be an additional management approach for this phy totoxic species and an alternative way to naturally control weeds on palm oil plantations.

Metisa plana (Walker) is a leaf defoliating pest that is able to cause staggering economical losses to oil palm cultivation. Considering the economic devastation that the pest could bring, an early warning system to predict its outbreak is crucial. The state of art of satellite technologies are now able to derive environmental factors such as relative humidity (RH) that may influence pest population’s fluctuations in rapid, harmless, and cost-effective manners. This study examined the relationship between the presence of Metisa plana at different time lags and remote sensing (RS) derived RH by using statistical and machine learning approaches. Metisa plana census data of cumulated larvae instar 1, 2, 3, and 4 were collected biweekly in 2014 and 2015 in an oil palm plantation in Muadzam Shah, Pahang, Malaysia. Relative humidity values derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were apportioned to 6 time lags; 1 week (T1), 2 weeks (T2), 3 week (T3), 4 weeks (T4), 5 week (T5) and 6 weeks (T6) and paired with the respective census data. Pearson’s correlation was carried out to analyse the relationship between Metisa plana and RH at different time lags. Regression analyses and artificial neural network (ANN) were also conducted to develop the best prediction model of Metisa plana’s outbreak. The results showed relatively high correlations, positively or negatively, between the presences of Metisa plana with RH ranging from 0.46 to 0.99. ANN was found to be superior to regression models with the adjusted coefficient of determination (R2) between the actual and predicted Metisa plana values ranging from 0.06 to 0.57 versus 0.00 to 0.05. The analysis on the best time lags illustrated that the multiple time lags were more influential on the Metisa plana population than the individual time lags. The best Metisa plana prediction model was derived from T1, T2 and T3 multiple time lags modelled using the ANN algorithm with R2 value of 0.5

This study was focused on molluscicidal effect and feeding deterrent activity of saponin from five different plant materials; Andrographis paniculata, Entada spiralis, Ficus deltoidea, Furcraea selloa and Ipomoea batatas. Crude plant extracts were prepared from plant powders using methanol. The crude extracts were then tested on Pomacea maculata using five different concentrations (5, 10, 15, 20 and 25 ppm, respectively) against niclosamide (control). After 72 h of exposure, the highest percentage of mortality of 80% was achieved from 15 ppm of F. selloa. Two analyses were conducted to observe the feeding deterrent activity and after 24 h, both analyses demonstrated the feeding deterrent activity in both crude extracts (F. selloa and E. spiralis) similar in niclosamide.

The present study revealed the optimization of nanoemulsion containing palm oil derivatives and Parthenium hysterophorus L. crude extract (PHCE) as pre-emergence herbicide formulation against Diodia ocimifolia. The nanoemulsion formulation was prepared by high energy emulsification method, and it was optimized by mixture experimental design (MED). From the optimization process, analysis of variance (ANOVA) showed a fit quadratic polynomial model with an optimal formulation composition containing 30.91% of palm kernel oil ester (PKOE), 28.48% of mixed surfactants (Tensiofix and Tween 80, 8:2), 28.32% of water and 12.29% of PHCE. The reading of both experimental and predicted particle size in the verification experiment were acceptable with a residual standard error (RSE) was less than 2%. Under the optimal condition, the smallest particle size obtained was 140.10 nm, and the particle was shown by morphology analysis to be spherical and demonstrated good stability (no phase separation) under centrifugation and different storage conditions (25 ± 5°C and 45°C). Nanoemulsion stored for 60 days exhibits monodisperse emulsion with a slight increase of particle size. The increase in particle size over time might have contributed by Ostwald ripening phenomenon which is shown by a linear graph from Ostwald ripening rate analysis. In the in vitro germination test, P. hysterophorus nanoemulsion (PHNE) was shown to cause total inhibition of D. ocimifolia seed at lower concentration (5 g L-1) as compared to PHCE (10 g L-1). The finding of the research could potentially serve as a platform for the development of palm oil based formulation containing plant crude extract for green weed management.

The solar heater box is a modest technology that enables easy collection and retention of solar radiation as heat at levels lethal to stored product arthropod pest inside the box. This study was designed to construct solar heater boxes of appreciable capacities to hold large quantities of grains, assess their heat-trapping efficiency and the influence of beans quantity and exposure time on same. Solar heater boxes of five different sizes were constructed for this study. Their heat-trapping capacity was evaluated by exposure to the sunlight for 5h. The influence of bean quantity and exposure on heat capture capabilities of the best performing solar heater box was evaluated using five different quantities of cocoa beans (9, 12, 15, 18 and 21kg) for 2h of exposure period. The result for heat trapping capacity shows that the largest solar heater box trapped the highest mean between and within bean temperatures (69.38±4.97 and 69.45±3.97C, respectively) in 5h of exposure time. The result of the experiment on the effect of bean quantity and exposure time on heat-trapping efficiency show the highest temperature was obtained at 120min exposure time using 9kg of cocoa beans for both between and within bean temperature (70.00±0.73 and 71.23±0.85oC, respectively). The implications of these findings in applying this technology for stored product arthropods pest management on durable commodities were discussed.

The effect of different initial adult population densities of Tribolium castaneum (Herbst) at several post infestation storage times on the final adult population density, the percentage of damaged beans, the percentage of weight loss, and the weight of insect feeding residues on cocoa beans was investigated in laboratory experiments. Both factors interactively had highly significant (P < 0.01) effects on variables assessed. The highest mean final adult population density of 129.7 ± 4.6 was recorded in samples infested with the highest initial adult population density and stored for 150 d, while the least mean adult population density of 10.8 ± 0.54 was recorded on samples infested with the lowest initial adult population density in samples stored for 30 d. The highest percentage damaged cocoa beans 51.0 ± 1.21% was recorded in samples infested with the highest initial adult population density, while the least mean percentage damaged beans of 16.9 ± 1.26% was also recorded on samples infested with the lowest initial adult population density. Similar trends of means were recorded for all the remaining variables. Correlation between factors was significant and positive. Multiple and simple linear regressions analyses were also significant (P < 0.01) and all equations fitted the regression models and perfectly described the relationship between the independent and the dependent variables. Our results show that T. castaneum can impact negatively on both the quantity and quality of stored cocoa within just 30 days of infestation, with the impact increasing with increasing population density and post infestation storage time.

The structural characterization of two phenazines, produced simultaneously through biosynthesis by Pseudomonas aeruginosa UPMP3 were studied. The phenazine antibiotics play an important role in antimicrobial activities and potentially could be used in biopesticide formulation to control basal stem rot of oil palm. The antibiotics were identified through high-performance liquid chromatography (HPLC) and confirmed using Fourier Transform Infrared (FTIR) spectroscopy. The specific representations in the FTIR spectra of the purified compounds such as absorption peaks at 1353.68 (aromatic nitro compound), 1118.84 and 729.43 cm-1 (aromatic ring) were indications of phenazine (PHZ) whereas, absorption peaks at 1717.92 (carboxylic acid), 861.78 and 738.54 cm-1 (aromatic ring) were indicatives of phenazine-1-carboxylic acid (PCA). The structures of the compounds were further confirmed by 1H NMR/13C NMR spectroscopy as PHZ (C12H8N2) and PCA (C13H8N2O2). Ganoderma boninense was sensitive to purified phenazine antibiotics especially phenazine and a concentration of 1000 ppm completely inhibited the mycelial growth. As far as we know, this is the first study where purified phenazine antibiotics isolated from P. aeruginosa UPMP3 were structurally characterised and tested to have positive antagonism against G. boninense.

Metisa plana (Walker) is leaves defoliating insect that is able to cause a staggering loss of USD 2.32 billion within two years to Malaysian oil palm industry. Therefore, an early warning system to predict the outbreak of Metisa plana that is cost, time, and energy effective is crucial. In order to do this, the role of environmental factors such as relative humidity (RH) on the pests’ population’s fluctuations should be well understood. Hence, this study utilized the geospatial technologies to i) to construct the relationship between the geospatially derived relative humidity and Metisa plana outbreak, and ii) to predict the outbreak of Metisa plana in oil palm plantation. Metisa plana census data of larvae instar 1, 2, 3, and 4 were collected approximately biweekly over the period of 2014 and 2015. Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images providing values of RH were extracted and apportioned to 6 time lags; 1 week (T1), 2 weeks (T2), 3 week (T3), 4 weeks (T4), 5 week (T5) and 6 weeks (T6) prior to census date. Pearson’s correlation, multiple linear regression (MLR) and multiple polynomial regression analysis (MPR) were carried out to analyse the linear relationship between Metisa plana and RH. Artificial neural network (ANN) was then used to develop the best prediction model of Metisa plana’s outbreak. Results show that there are correlations between the presence of Metisa plana with RH, however, the time lag effect was not prominent. MPR was able to produce model with higher R2 in comparison to MLR with the highest R2 for both analysis were 0.48 and 0.15 respectively at T4 to T6. Model with the highest accuracy was achieved by ANN that utilized the RH at T1 to T3 at 95.29%. Based on the result of this study, the prediction of Metisa plana’s landscape ecology was possible with the utilization of geospatial technology and RH as the predictor parameter.

A comparative study was conducted to see the effect of Sida cordifolia L. aerial and root extracts on seed germination and seedling vigour performance of Lacttuca sativa (Lettuce), Lycopersicon esculentum (Tomato) and Daucus carota (Carrot). Four treatments were prepared 50, 25, 10 and 0 g/l (control). The result showed a significant decrease in germination and growth in all the treatments and regardless of concentrations lettuce was observed to be more susceptible in all extracts. Leaf extract exhibited the highest phytotoxicity followed by root while shoot extract produced the least effect. Inhibition index showed decrease in growth appeared to be concentration dependent. Liquid chromatography mass spectrum analysis of leaf and root extracts revealed presence of aliphatic acids notably stearic and palmitic which may act as inhibitory agents.

Cardboard and Plywood were the materials which used for solar heater boxes to control adult and developmental stages of cowpea beetle Callosobruchus maculatus (F.) according to their effectiveness in previous study on solar heaters. The effect of solar heat on hatchability, oviposition, 4th instars and mortality was evaluated. Adult mortality, hatchability, oviposition and adult emergence were significantly affected by solar heater boxes treatment. A temperature of 66.4°C was achieved in solar heater boxes within 15 minutes which caused 100% mortality of adults and 4th larval instars of C. maculatus compared to 0% mortality after 1,2 and 3 days for untreated adults. Heat treatment decreased hatchability by 70% and 66.7% in Plywood and Cardboard respectively comparing with untreated eggs. To verify the effect of solar temperatures, another experiment was done using the oven. Adults of C. maculatus and eggs were exposed to constant temperatures to evaluate the effect on oviposition, adult emergence and mortality. Times needed for 100% adult’s mortality were 10, 20, 40 and 50 minutes with temperatures of 70, 60, 50 and 40°C respectively. The oviposition was also affected significantly by different temperatures.

The effect of solar heater boxes on germination, moisture content and seedling characteristics of adzuki bean beans seeds V. angularis was determined using cardboard and plywood solar heater boxes. Results showed that, exposure to cardboard and plywood solar heater boxes did not show enormous effect on germination characters for adzuki bean seeds. In addition, experiment in oven was done for more verification. Exposure to temperatures of 40, 50, 60, and 70°C did not affect germination of adzuki bean seeds.

Experiments were conducted to study the effects of solar heat treatment in a solar heater box on all the life stages, namely adult, larvae, eggs and pupa of T. castaneum infested on cocoa beans. Thirty (30) adults, larvae, eggs and pupae of T. castaneum were infested on cocoa beans and exposed to solar radiation in the solar heater box for 30, 45, 60, 90 and 120 min. Mortalities were assessed in the treated adults and larval stages 24 h after exposure for 3 days. Eggs hatchability and pupal eclosions were also assessed daily until 9 and 7 days after treatment respectively. The results show that adult and larval mortalities in the solar heater box treated populations were significant and ranged from 96.66-100%. Similarly, both egg hatchability and pupal eclosion were absolutely inhibited. It was concluded that the solar heater box can be used as a reliable tool for heat sequestrations for the eco-friendly control of T. castaneum on cocoa beans.

The selection and evaluation of solar heaters for trapping and using solar energy to disinfest legume grains are described. The effectiveness of five materials (cardboard, plywood, Perspex timber and metal) in collecting heat as temperature from the sun was investigated two different linings materials were used to coat solar heater boxes aluminium foil, and black paint. Solar heater boxes were covered with clear plastic to trap solar radiation. Cardboard and plywood were the best materials to construct the solar heater boxes as they trap and retained more heat due to their high thermal diffusivity compared to perspex and timber solar heater boxes. In addition, these materials are cheaper and easier to handle compared to metal. It was also concluded that, aluminium foils combined with black paint was the best lining than aluminium foil or black paint used separately. The effect of seed depth on solar energy collection inside cardboard and plywood solar heater boxes was also evaluated. Temperatures trapped in cardboard solar heater boxes with 7 kg of seeds was 13.9% higher than temperatures trapped in plywood solar heater boxes. Therefore, cardboard solar heater boxes were better than plywood solar heater boxes.