The increasing global population has led to a higher demand for food production, while a decrease in rural labor and a rise in production costs present complex challenges for the food industry. Smart agriculture is a ...The increasing global population has led to a higher demand for food production, while a decrease in rural labor and a rise in production costs present complex challenges for the food industry. Smart agriculture is a farm management concept that considers the deployment of Internet of Things (IoT) to address current food production challenges. In this regard, the agricultural sector is becoming increasingly data-focused, and requires data and technologies that are more precise, advanced, and cutting-edge than in the past. IoT enables agriculture to become data-driven, resulting in timely and more cost-effective farm intervention while reducing environmental impact. This review provides an analytical survey of the current and potential applications of IoT in smart agriculture to overcome challenges posed by spatio-temporal variability under varying environments and task diversity. This review also discusses the challenges that may arise from IoT deployment and presents an overview of the existing applications and those that may be developed in the future.展开更多
Validity of CA-Markov in land use and cover change simulation was investigated at the Langat Basin, Selangor, Malaysia. CA-Markov validation was performed using validation metrics, allocation disagreement, quantity di...Validity of CA-Markov in land use and cover change simulation was investigated at the Langat Basin, Selangor, Malaysia. CA-Markov validation was performed using validation metrics, allocation disagreement, quantity disagreement, and figure of merit in a three-dimensional space. The figure of merit, quantity error, and allocation error for total landscape simulation using the 1990-1997 calibration data were 5.62%, 3.53%, and 6.13%, respectively. CA-Markov showed a poor performance for land use and cover change simulation due to uncertainties in the source data, the model, and future land use and cover change processes in the study area.展开更多
Fusarium species were reported to produce biofilms.Biofilms are superficial societies of microbes bounded and endangered by being situated or taking place outside a cell or cells.The most destructive fungal diseases c...Fusarium species were reported to produce biofilms.Biofilms are superficial societies of microbes bounded and endangered by being situated or taking place outside a cell or cells.The most destructive fungal diseases caused by phytopathogens are as a result of biofilms formation.Fusarium wilt of banana(Panama disease)is caused by a soil-borne pathogen called Fusarium oxysporum f.sp.cubense.Fusarium oxysporum occurs in a form of a species complex(FOSC)which encompasses a crowd of strains.Horizontal genetic factor transfer may donate to the observed assortment in pathogenic strains,while sexual reproduction is unknown in the FOSC.Fusarium wilt is a notorious disease on several crops worldwide.Yield loss caused by this pathogen is huge,and significant to destroy crop yields annually,thereby affecting the producer countries in various continents of the world.The disease is also resistant to various synthetic chemical fungicides.However,excessive use of synthetic fungicides during disease control could be lethal to humans,animals,and plants.This calls for alternative eco-friendly management of this disease by targeting the biofilms formation and finally suppressing this devastating phytopathogen.In this review,we,therefore,described the damage caused by Fusarium wilt disease,the concept of filamentous fungal biofilms,classical control strategies,sustainable disease control strategies using essential oils,and prevention and control of vegetables Fusarium wilt diseases.展开更多
The present study, conducted during 2016 and 2017 seasons, aimed to investigate the effect of IBA on rooting of Piper betle L. stem cuttings (softwood and semi-hardwood). The experiment was undertaken in misting house...The present study, conducted during 2016 and 2017 seasons, aimed to investigate the effect of IBA on rooting of Piper betle L. stem cuttings (softwood and semi-hardwood). The experiment was undertaken in misting house field 2 UPM using the sand media to determine the adventitious roots initiation and development using the histological method. The cuttings were treated with different IBA concentrations (0, 500, 1000, 1500 and 2000 mg/L). The nodes explants were used in the development of a protocol for in vitro propagation of P. betle L., with different concentrations of Clorox with different times of immersion (20% Clorox 10 minutes, 30% Clorox 10 minutes, 20% Clorox 20 minutes, and 30% 20 minutes). In multiplication of the plantlets, Murashige and Skoog (MS) medium with different concentrations of BAP (0, 0.5, 1.0, 2.0 mg/L) were used to investigate the rooting of the explants. The results indicated that the types of the cuttings were different in the rooting capacity and the length of the roots. Moreover, it was found that in comparison with the control treatment, by a rise in the concentrations of the IBA, there was a significant upsurge in the rooting percentage, the root diameter, and the number of the roots. The results indicated that the types of cutting with 1000, 1500 and 2000 mg/L IBA perform better in the root percentage (100%) in the semi hardwood cuttings. The best results, however, were 2000 mg/L IBA in the semi hardwood cuttings, with the number of the roots to be 35.05, and the fresh weight of the roots to be 3.94 g, the dry weight of the roots to be 0.33 g, the length of the roots to be 391.88 cm, the roots diameter to be 1.21 mm, the surface area of the roots to be 121.83 cm2, and the root volume to be 2.99 cm3. Nonetheless, the optimal concentration of Clorox with the time immersion was 20% with the 20-minute immersion time, which produced a shoot induction percentage of 30% dead explants and a mean number of 70.00 shoots per explant and the optimal concentration of benzylaminopurine (BAP) at 1.0 mg/L. It is of note that a shoot induction percentage of 22.29% and a mean number of 4.1% number of auxiliary bud per treatment. P. betle shoots in MS medium without PGR MS (0.0) yielded a good rooting.展开更多
Red tip disease on pineapple (Ananas comosus) was first recognized about 20 years ago in a commercial pineapple stand located in Simpang Renggam, Johor, Peninsular Malaysia. Since its discovery, there has been no conf...Red tip disease on pineapple (Ananas comosus) was first recognized about 20 years ago in a commercial pineapple stand located in Simpang Renggam, Johor, Peninsular Malaysia. Since its discovery, there has been no confirmation on the causal agent of red tip disease. The epidemiology of red tip disease is still not fully understood. However, based on disease symptoms and field transmission mode, red tip disease seems to be strongly associated with viral infection. The aim of this work was to assess the feasibility of using an optical sensor to estimate red tip disease severity. This work was performed in a commercial pineapple plantation located in Simpang Renggam, Johor. Four observation plots bearing pineapple variety SR36 were demarcated based on crop growth stage. Each plot comprised a total of eighty corresponding measurements of percent Disease Severity (% DS) and Normalized Difference Vegetation Index (NDVI). Our data showed a strong correlation between % DS and NDVI. The 7- and 11-month plantings registered a correlation coefficient (r) of -0.83 and -0.88, respectively. The negative correlation infers that NDVI increases when disease severity is low. This is expected since healthy leaves reflect more near-infrared light and less visible light which results in a higher NDVI. The regression of NDVI on % DS for the 7-month planting was explained by: % DS = 181.6 - 185.6*NDVI. Meanwhile, the regression of NDVI on % DS for the 11-month planting was explained by: % DS = 213.2 - 219.8*NDVI. The linear fit between measured % DS and estimated % DS from the 7-month and 11-month plantings was relatively strong. This work has demonstrated that NDVI is a reliable predictor of % DS in pineapple.展开更多
Agrobacterium-mediated transformation through floral dip and rapid selection process after transgenic event had become a preference as it will overcome the difficulties faced in tissue culturing procedures and lengthy...Agrobacterium-mediated transformation through floral dip and rapid selection process after transgenic event had become a preference as it will overcome the difficulties faced in tissue culturing procedures and lengthy time for screening transformed progenies. Therefore, in this study, three constructs, p5b5 (14,289 bp), p5d9 (15,330 bp) and p5f7 (15,380 bp) in pDRB6b vector which has hygromycin as a selectable marker gene were introduced individually into Agrobacterium tumefaciens strain (AGL1). The cell suspension was applied to Amaranthus inflorescence by drop-by-drop technique and was left to produce seeds (T1). The T1 seeds were germinated and grown to produce seedlings under non-sterile condition. Hygromycin selection on seedling cotyledon leaves results in identification of 12 putative transformants, three from p5b5, four from p5d9 and five from p5f7. All positive putative transformants that were selected at the first stage through hygromycin spraying showed positive result in leaf disk hygromycin assay and in a construct specific polymerase chain reaction-based assay. A ~750 bp amplified hygromycin gene was further verified through sequencing. Our results suggest that Amaranthus inflorescences were able to be transformed and the transformed progenies could be verified through a combination of simple and rapid methods .展开更多
Every breeding program that aims to create new and improved cultivars with desired traits mostly relies on information related to genetic diversity.Therefore,molecular characterization of germplasms is important to ob...Every breeding program that aims to create new and improved cultivars with desired traits mostly relies on information related to genetic diversity.Therefore,molecular characterization of germplasms is important to obtain target cultivars with desirable traits.Sweet potato[Ipomoea batatas(L.)Lam]is widely considered the world’s most important crop,with great diversity in morphological and phenotypic traits.The genetic diversity of 20 sweet potato germplasms originating from Bangladesh,CIP,Philippines,Taiwan,and Malaysia were compared,which was accomplished by genetic diversity analysis by exploring 20 microsatellite DNA markers for germplasm characterization and utilization.This information was effective in differentiating or clustering the sweet potato genotypes.A total of 64 alleles were generated using the 20 primers throughout the 20 germplasm samples,with locus IBS97 having the highest number of alleles(5),whereas locus IbU33 had the fewest alleles(2).The alleles varied in size from 105(IbU31)to 213 base pairs(IBS34).The Polymorphism Information Content(PIC)values for the loci IbL46 and IBS97 varied from 0.445 to 0.730.IBS97 has the highest number of effective alleles(3.704),compared to an average of 2.520.The average Shannon’s diversity index(H)was 1.003,ranging from 0.673 in IbU3 to 1.432 in IBS97.The value of gene flow(Nm)varied between 0.000 and 0.005,with an average of 0.003,whereas genetic differentiation(FST-values)ranged between 0.901 and 1.000.The sweet potato germplasm included in this study had a broad genetic base.SP1 vs.SP9 and SP12 vs.SP18 germplasm pairings had the greatest genetic distance(GD=0.965),while SP1 vs.SP2 germplasm couples had the least genetic diversity(GD=0.093).Twenty genotypes were classified into two groups in the UPGMA dendrogram,with 16 genotypes classified as group“A”and the remaining four genotypes,SP10,SP18,SP19,and SP20,classified as group“B.”According to cluster analysis,the anticipated heterozygosity(gene diversity)of Nei(1973)was 0.591 on average.In summary,SSR markers successfully evaluated the genetic relationships among the sweet potato accessions used and generated a high level of polymorphism.The results of the present study will be useful for the management of germplasm,improvement of the current breeding strategies,and the release of new cultivars as varieties.展开更多
The study explores the factors influencing attitude towards agricultural technology adoption among Permanent Food Production Park(PFPP)program participants in West Malaysia and the factors that influence their attitud...The study explores the factors influencing attitude towards agricultural technology adoption among Permanent Food Production Park(PFPP)program participants in West Malaysia and the factors that influence their attitudes.The PFPP program is one of the programs introduced by the government of Malaysia with the objectives of increasing food production,as well as supporting local agriculture entrepreneurs.The study employed a cross-sectional study design and has been conducted in four West Malaysian states with a sample of size of 275 respondents.The results indicated that the respondents had a positive attitude towards technology adoption and factors such as knowledge and skill,benefit,education level,years of experience in agriculture and gross income had influenced their attitude.展开更多
Prediction of highly non-linear behavior of suspended sediment flow in rivers has prime importance in environmental studies and watershed management. In this study, the predictive performance of two Artificial Neural ...Prediction of highly non-linear behavior of suspended sediment flow in rivers has prime importance in environmental studies and watershed management. In this study, the predictive performance of two Artificial Neural Networks (ANNs), namely Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) were compared. Time series data of daily suspended sediment discharge and water discharge at the Langat River, Malaysia were used for training and testing the networks. Mean Square Error (MSE), Normalized Mean Square Error (NMSE) and correlation coefficient (r) were used for performance evaluation of the models. Using the testing data set, both models produced a similar level of robustness in sediment load simulation. The MLP network model showed a slightly better output than the RBF network model in predicting suspended sediment discharge, especially in the training process. However, both ANNs showed a weak robustness in estimating large magnitudes of sediment load.展开更多
The study was carried out to evaluate the efficiency of a natural coagulant that is Moringa oleifera seeds in removing turbid from Malaysian water. Three water samples were used in this study subjected to purification...The study was carried out to evaluate the efficiency of a natural coagulant that is Moringa oleifera seeds in removing turbid from Malaysian water. Three water samples were used in this study subjected to purification studies using Moringa oleifera seeds that were collected during two different seasons that are dry season (February-March) and rainy season (October-November). The treated water samples were tested for turbidity level, pH level and color index. The result shows that Moringa oleifera seed collected during drought season has the ability to remove turbidity up to 88.0% and has better color index compared seeds collected during rainy season. The ability of Moringa oleifera seeds protein to act as a magnet assists in attracting the flocks and turbid in the water. Although not as effective as conventional chemicals, Moringa oleifera shows remarkable ability to remove turbid and encourages the use of natural coagulant in water treatment plants as it is cheap and environmental friendly.展开更多
Digital farming is the practice of modern technologies such as sensors,robotics,and data analysis for shifting from tedious operations to continuously automated processes.This paper reviews some of the latest achievem...Digital farming is the practice of modern technologies such as sensors,robotics,and data analysis for shifting from tedious operations to continuously automated processes.This paper reviews some of the latest achievements in agricultural robotics,specifically those that are used for autonomous weed control,field scouting,and harvesting.Object identification,task planning algorithms,digitalization and optimization of sensors are highlighted as some of the facing challenges in the context of digital farming.The concepts of multi-robots,human-robot collaboration,and environment reconstruction from aerial images and ground-based sensors for the creation of virtual farms were highlighted as some of the gateways of digital farming.It was shown that one of the trends and research focuses in agricultural field robotics is towards building a swarm of small scale robots and drones that collaborate together to optimize farming inputs and reveal denied or concealed information.For the case of robotic harvesting,an autonomous framework with several simple axis manipulators can be faster and more efficient than the currently adapted professional expensive manipulators.While robots are becoming the inseparable parts of the modern farms,our conclusion is that it is not realistic to expect an entirely automated farming system in the future.展开更多
Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade.Agricultural robots are complex systems that require interdisciplina...Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade.Agricultural robots are complex systems that require interdisciplinary collaborations between different research groups for effective task delivery in unstructured crops and plants environments.With the exception of milking robots,the extensive research works that have been carried out in the past two decades for adaptation of robotics in agriculture have not yielded a commercial product to date.To accelerate this pace,simulation approach and evaluation methods in virtual environments can provide an affordable and reliable framework for experimenting with different sensing and acting mechanisms in order to verify the performance functionality of the robot in dynamic scenarios.This paper reviews several professional simulators and custom-built virtual environments that have been used for agricultural robotic applications.The key features and performance efficiency of three selected simulators were also compared.A simulation case study was demonstrated to highlight some of the powerful functionalities of the Virtual Robot Experimentation Platform.Details of the objects and scenes were presented as the proof-of-concept for using a completely simulated robotic platform and sensing systems in a virtual citrus orchard.It was shown that the simulated workspace can provide a configurable and modular prototype robotic system that is capable of adapting to several field conditions and tasks through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment.This review suggests that an open-source software platform for agricultural robotics will significantly accelerate effective collaborations between different research groups for sharing existing workspaces,algorithms,and reusing the materials.展开更多
This paper reviews advanced Neural Network(NN)techniques available to process hyperspectral data,with a special emphasis on plant disease detection.Firstly,we provide a review on NN mechanism,types,models,and classifi...This paper reviews advanced Neural Network(NN)techniques available to process hyperspectral data,with a special emphasis on plant disease detection.Firstly,we provide a review on NN mechanism,types,models,and classifiers that use different algorithms to process hyperspectral data.Then we highlight the current state of imaging and nonimaging hyperspectral data for early disease detection.The hybridization of NNhyperspectral approach has emerged as a powerful tool for disease detection and diagnosis.Spectral Disease Index(SDI)is the ratio of different spectral bands of pure disease spectra.Subsequently,we introduce NN techniques for rapid development of SDI.We also highlight current challenges and future trends of hyperspectral data.展开更多
This paper presents the study reports on evaluating a new transplanting operation by taking into accounts the interactions between soil,plant,and machine in line with the System of Rice Intensification(SRI)practices.T...This paper presents the study reports on evaluating a new transplanting operation by taking into accounts the interactions between soil,plant,and machine in line with the System of Rice Intensification(SRI)practices.The objective was to modify planting claw(kuku-kambing)of a paddy transplanter in compliance with SRI guidelines to determine the best planting spacing(S),seed rate(G)and planting pattern that results in a maximum number of seedling,tillers per hill,and yield.Two separate experiments were carried out in two different paddy fields,one to determine the best planting spacing(S=4 levels:s_(1)=0.16 m×0.3 m,s_(2)=0.18 m×0.3 m,s_(3)=0.21 m×0.3 m,and s_(4)=0.24 m×0.3 m)for a specific planting pattern(row mat or scattered planting pattern),and the other to determine the best combination of spacing with seed rate treatments(G=2 levels:g1=75 g/tray,and g2=240 g/tray).Main SRI management practices such as soil characteristics of the sites,planting depth,missing hill,hill population,the number of seedling per hill,and yield components were evaluated.Results of two-way analysis of variance with three replications showed that spacing,planting pattern and seed rate affected the number of one-seedling in all experiment.It was also observed that the increase in spacing resulted in more tillers and more panicle per plant,however hill population and sterility ratio increased with the decrease in spacing.While the maximum number of panicles were resulted from scattered planting at s_(4)=0.24 m×0.3 m spacing with the seed rate of g1=75 g/tray,the maximum number of one seedling were observed at s_(4)=0.16 m×0.3 m.The highest and lowest yields were obtained from 75 g seeds per tray scattered and 70 g seeds per tray scattered treatment respectively.For all treatments,the result clearly indicates an increase in yield with an increase in spacing.展开更多
Agricultural crop abandonment negatively impacts local economy and environment since land,as a resource for agriculture,is not optimally utilized.To take necessary actions to rehabilitate abandoned agricultural lands,...Agricultural crop abandonment negatively impacts local economy and environment since land,as a resource for agriculture,is not optimally utilized.To take necessary actions to rehabilitate abandoned agricultural lands,the identification of the spatial distribution of these lands must be acknowledged.While optical images had previously illustrated potentials in the identification of agricultural land abandonment,tropical areas often suffer cloud coverage problem that limits the availability of the imageries.Therefore,this study was conducted to investigate the potential of ALOS-1 and 2(Advanced Land Observing Satellite-1 and 2)PALSAR(Phased Array L-band Synthetic Aperture Radar)images for the identification and classification of abandoned agricultural crop areas,namely paddy,rubber and oil palm fields.Distinct crop phenology for paddy and rubber was identified from ALOS-1 PALSAR;nonetheless,oil palm did not demonstrate any useful phenology for discriminating between the abandoned classes.The accuracy obtained for these abandoned lands of paddy,rubber and oil palm was 93.33%±0.06%,78%±2.32%and 63.33%±1.88%,respectively.This study confirmed that the understanding of crop phenology in relation to image date selection is essential to obtain high accuracy for classifying abandoned and non-abandoned agricultural crops.The finding also portrayed that PALSAR offers a huge advantage for application of vegetation in tropical areas.展开更多
文摘The increasing global population has led to a higher demand for food production, while a decrease in rural labor and a rise in production costs present complex challenges for the food industry. Smart agriculture is a farm management concept that considers the deployment of Internet of Things (IoT) to address current food production challenges. In this regard, the agricultural sector is becoming increasingly data-focused, and requires data and technologies that are more precise, advanced, and cutting-edge than in the past. IoT enables agriculture to become data-driven, resulting in timely and more cost-effective farm intervention while reducing environmental impact. This review provides an analytical survey of the current and potential applications of IoT in smart agriculture to overcome challenges posed by spatio-temporal variability under varying environments and task diversity. This review also discusses the challenges that may arise from IoT deployment and presents an overview of the existing applications and those that may be developed in the future.
文摘Validity of CA-Markov in land use and cover change simulation was investigated at the Langat Basin, Selangor, Malaysia. CA-Markov validation was performed using validation metrics, allocation disagreement, quantity disagreement, and figure of merit in a three-dimensional space. The figure of merit, quantity error, and allocation error for total landscape simulation using the 1990-1997 calibration data were 5.62%, 3.53%, and 6.13%, respectively. CA-Markov showed a poor performance for land use and cover change simulation due to uncertainties in the source data, the model, and future land use and cover change processes in the study area.
基金the Ministry of Higher Education Malaysia for providing funds under the Long-term Research Grant Scheme(LRGS/1/2019/UPM/2/2)。
文摘Fusarium species were reported to produce biofilms.Biofilms are superficial societies of microbes bounded and endangered by being situated or taking place outside a cell or cells.The most destructive fungal diseases caused by phytopathogens are as a result of biofilms formation.Fusarium wilt of banana(Panama disease)is caused by a soil-borne pathogen called Fusarium oxysporum f.sp.cubense.Fusarium oxysporum occurs in a form of a species complex(FOSC)which encompasses a crowd of strains.Horizontal genetic factor transfer may donate to the observed assortment in pathogenic strains,while sexual reproduction is unknown in the FOSC.Fusarium wilt is a notorious disease on several crops worldwide.Yield loss caused by this pathogen is huge,and significant to destroy crop yields annually,thereby affecting the producer countries in various continents of the world.The disease is also resistant to various synthetic chemical fungicides.However,excessive use of synthetic fungicides during disease control could be lethal to humans,animals,and plants.This calls for alternative eco-friendly management of this disease by targeting the biofilms formation and finally suppressing this devastating phytopathogen.In this review,we,therefore,described the damage caused by Fusarium wilt disease,the concept of filamentous fungal biofilms,classical control strategies,sustainable disease control strategies using essential oils,and prevention and control of vegetables Fusarium wilt diseases.
文摘The present study, conducted during 2016 and 2017 seasons, aimed to investigate the effect of IBA on rooting of Piper betle L. stem cuttings (softwood and semi-hardwood). The experiment was undertaken in misting house field 2 UPM using the sand media to determine the adventitious roots initiation and development using the histological method. The cuttings were treated with different IBA concentrations (0, 500, 1000, 1500 and 2000 mg/L). The nodes explants were used in the development of a protocol for in vitro propagation of P. betle L., with different concentrations of Clorox with different times of immersion (20% Clorox 10 minutes, 30% Clorox 10 minutes, 20% Clorox 20 minutes, and 30% 20 minutes). In multiplication of the plantlets, Murashige and Skoog (MS) medium with different concentrations of BAP (0, 0.5, 1.0, 2.0 mg/L) were used to investigate the rooting of the explants. The results indicated that the types of the cuttings were different in the rooting capacity and the length of the roots. Moreover, it was found that in comparison with the control treatment, by a rise in the concentrations of the IBA, there was a significant upsurge in the rooting percentage, the root diameter, and the number of the roots. The results indicated that the types of cutting with 1000, 1500 and 2000 mg/L IBA perform better in the root percentage (100%) in the semi hardwood cuttings. The best results, however, were 2000 mg/L IBA in the semi hardwood cuttings, with the number of the roots to be 35.05, and the fresh weight of the roots to be 3.94 g, the dry weight of the roots to be 0.33 g, the length of the roots to be 391.88 cm, the roots diameter to be 1.21 mm, the surface area of the roots to be 121.83 cm2, and the root volume to be 2.99 cm3. Nonetheless, the optimal concentration of Clorox with the time immersion was 20% with the 20-minute immersion time, which produced a shoot induction percentage of 30% dead explants and a mean number of 70.00 shoots per explant and the optimal concentration of benzylaminopurine (BAP) at 1.0 mg/L. It is of note that a shoot induction percentage of 22.29% and a mean number of 4.1% number of auxiliary bud per treatment. P. betle shoots in MS medium without PGR MS (0.0) yielded a good rooting.
文摘Red tip disease on pineapple (Ananas comosus) was first recognized about 20 years ago in a commercial pineapple stand located in Simpang Renggam, Johor, Peninsular Malaysia. Since its discovery, there has been no confirmation on the causal agent of red tip disease. The epidemiology of red tip disease is still not fully understood. However, based on disease symptoms and field transmission mode, red tip disease seems to be strongly associated with viral infection. The aim of this work was to assess the feasibility of using an optical sensor to estimate red tip disease severity. This work was performed in a commercial pineapple plantation located in Simpang Renggam, Johor. Four observation plots bearing pineapple variety SR36 were demarcated based on crop growth stage. Each plot comprised a total of eighty corresponding measurements of percent Disease Severity (% DS) and Normalized Difference Vegetation Index (NDVI). Our data showed a strong correlation between % DS and NDVI. The 7- and 11-month plantings registered a correlation coefficient (r) of -0.83 and -0.88, respectively. The negative correlation infers that NDVI increases when disease severity is low. This is expected since healthy leaves reflect more near-infrared light and less visible light which results in a higher NDVI. The regression of NDVI on % DS for the 7-month planting was explained by: % DS = 181.6 - 185.6*NDVI. Meanwhile, the regression of NDVI on % DS for the 11-month planting was explained by: % DS = 213.2 - 219.8*NDVI. The linear fit between measured % DS and estimated % DS from the 7-month and 11-month plantings was relatively strong. This work has demonstrated that NDVI is a reliable predictor of % DS in pineapple.
文摘Agrobacterium-mediated transformation through floral dip and rapid selection process after transgenic event had become a preference as it will overcome the difficulties faced in tissue culturing procedures and lengthy time for screening transformed progenies. Therefore, in this study, three constructs, p5b5 (14,289 bp), p5d9 (15,330 bp) and p5f7 (15,380 bp) in pDRB6b vector which has hygromycin as a selectable marker gene were introduced individually into Agrobacterium tumefaciens strain (AGL1). The cell suspension was applied to Amaranthus inflorescence by drop-by-drop technique and was left to produce seeds (T1). The T1 seeds were germinated and grown to produce seedlings under non-sterile condition. Hygromycin selection on seedling cotyledon leaves results in identification of 12 putative transformants, three from p5b5, four from p5d9 and five from p5f7. All positive putative transformants that were selected at the first stage through hygromycin spraying showed positive result in leaf disk hygromycin assay and in a construct specific polymerase chain reaction-based assay. A ~750 bp amplified hygromycin gene was further verified through sequencing. Our results suggest that Amaranthus inflorescences were able to be transformed and the transformed progenies could be verified through a combination of simple and rapid methods .
基金The work was financially supported by National Agricultural Technology Program-II Project(NATP-2)BARC Component Bangladesh Agricultural Research Council,Farmgate,Dhaka-1215+2 种基金Bangladesh Agricultural Research Institute(BARI),Joydebpur,Gazipur 1701The work was partially supported by the Taif University Researchers Supporting Project No.(TURSP-2020/39)Taif University,Taif,Saudi Arabia.
文摘Every breeding program that aims to create new and improved cultivars with desired traits mostly relies on information related to genetic diversity.Therefore,molecular characterization of germplasms is important to obtain target cultivars with desirable traits.Sweet potato[Ipomoea batatas(L.)Lam]is widely considered the world’s most important crop,with great diversity in morphological and phenotypic traits.The genetic diversity of 20 sweet potato germplasms originating from Bangladesh,CIP,Philippines,Taiwan,and Malaysia were compared,which was accomplished by genetic diversity analysis by exploring 20 microsatellite DNA markers for germplasm characterization and utilization.This information was effective in differentiating or clustering the sweet potato genotypes.A total of 64 alleles were generated using the 20 primers throughout the 20 germplasm samples,with locus IBS97 having the highest number of alleles(5),whereas locus IbU33 had the fewest alleles(2).The alleles varied in size from 105(IbU31)to 213 base pairs(IBS34).The Polymorphism Information Content(PIC)values for the loci IbL46 and IBS97 varied from 0.445 to 0.730.IBS97 has the highest number of effective alleles(3.704),compared to an average of 2.520.The average Shannon’s diversity index(H)was 1.003,ranging from 0.673 in IbU3 to 1.432 in IBS97.The value of gene flow(Nm)varied between 0.000 and 0.005,with an average of 0.003,whereas genetic differentiation(FST-values)ranged between 0.901 and 1.000.The sweet potato germplasm included in this study had a broad genetic base.SP1 vs.SP9 and SP12 vs.SP18 germplasm pairings had the greatest genetic distance(GD=0.965),while SP1 vs.SP2 germplasm couples had the least genetic diversity(GD=0.093).Twenty genotypes were classified into two groups in the UPGMA dendrogram,with 16 genotypes classified as group“A”and the remaining four genotypes,SP10,SP18,SP19,and SP20,classified as group“B.”According to cluster analysis,the anticipated heterozygosity(gene diversity)of Nei(1973)was 0.591 on average.In summary,SSR markers successfully evaluated the genetic relationships among the sweet potato accessions used and generated a high level of polymorphism.The results of the present study will be useful for the management of germplasm,improvement of the current breeding strategies,and the release of new cultivars as varieties.
文摘The study explores the factors influencing attitude towards agricultural technology adoption among Permanent Food Production Park(PFPP)program participants in West Malaysia and the factors that influence their attitudes.The PFPP program is one of the programs introduced by the government of Malaysia with the objectives of increasing food production,as well as supporting local agriculture entrepreneurs.The study employed a cross-sectional study design and has been conducted in four West Malaysian states with a sample of size of 275 respondents.The results indicated that the respondents had a positive attitude towards technology adoption and factors such as knowledge and skill,benefit,education level,years of experience in agriculture and gross income had influenced their attitude.
文摘Prediction of highly non-linear behavior of suspended sediment flow in rivers has prime importance in environmental studies and watershed management. In this study, the predictive performance of two Artificial Neural Networks (ANNs), namely Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) were compared. Time series data of daily suspended sediment discharge and water discharge at the Langat River, Malaysia were used for training and testing the networks. Mean Square Error (MSE), Normalized Mean Square Error (NMSE) and correlation coefficient (r) were used for performance evaluation of the models. Using the testing data set, both models produced a similar level of robustness in sediment load simulation. The MLP network model showed a slightly better output than the RBF network model in predicting suspended sediment discharge, especially in the training process. However, both ANNs showed a weak robustness in estimating large magnitudes of sediment load.
文摘The study was carried out to evaluate the efficiency of a natural coagulant that is Moringa oleifera seeds in removing turbid from Malaysian water. Three water samples were used in this study subjected to purification studies using Moringa oleifera seeds that were collected during two different seasons that are dry season (February-March) and rainy season (October-November). The treated water samples were tested for turbidity level, pH level and color index. The result shows that Moringa oleifera seed collected during drought season has the ability to remove turbidity up to 88.0% and has better color index compared seeds collected during rainy season. The ability of Moringa oleifera seeds protein to act as a magnet assists in attracting the flocks and turbid in the water. Although not as effective as conventional chemicals, Moringa oleifera shows remarkable ability to remove turbid and encourages the use of natural coagulant in water treatment plants as it is cheap and environmental friendly.
文摘Digital farming is the practice of modern technologies such as sensors,robotics,and data analysis for shifting from tedious operations to continuously automated processes.This paper reviews some of the latest achievements in agricultural robotics,specifically those that are used for autonomous weed control,field scouting,and harvesting.Object identification,task planning algorithms,digitalization and optimization of sensors are highlighted as some of the facing challenges in the context of digital farming.The concepts of multi-robots,human-robot collaboration,and environment reconstruction from aerial images and ground-based sensors for the creation of virtual farms were highlighted as some of the gateways of digital farming.It was shown that one of the trends and research focuses in agricultural field robotics is towards building a swarm of small scale robots and drones that collaborate together to optimize farming inputs and reveal denied or concealed information.For the case of robotic harvesting,an autonomous framework with several simple axis manipulators can be faster and more efficient than the currently adapted professional expensive manipulators.While robots are becoming the inseparable parts of the modern farms,our conclusion is that it is not realistic to expect an entirely automated farming system in the future.
文摘Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade.Agricultural robots are complex systems that require interdisciplinary collaborations between different research groups for effective task delivery in unstructured crops and plants environments.With the exception of milking robots,the extensive research works that have been carried out in the past two decades for adaptation of robotics in agriculture have not yielded a commercial product to date.To accelerate this pace,simulation approach and evaluation methods in virtual environments can provide an affordable and reliable framework for experimenting with different sensing and acting mechanisms in order to verify the performance functionality of the robot in dynamic scenarios.This paper reviews several professional simulators and custom-built virtual environments that have been used for agricultural robotic applications.The key features and performance efficiency of three selected simulators were also compared.A simulation case study was demonstrated to highlight some of the powerful functionalities of the Virtual Robot Experimentation Platform.Details of the objects and scenes were presented as the proof-of-concept for using a completely simulated robotic platform and sensing systems in a virtual citrus orchard.It was shown that the simulated workspace can provide a configurable and modular prototype robotic system that is capable of adapting to several field conditions and tasks through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment.This review suggests that an open-source software platform for agricultural robotics will significantly accelerate effective collaborations between different research groups for sharing existing workspaces,algorithms,and reusing the materials.
文摘This paper reviews advanced Neural Network(NN)techniques available to process hyperspectral data,with a special emphasis on plant disease detection.Firstly,we provide a review on NN mechanism,types,models,and classifiers that use different algorithms to process hyperspectral data.Then we highlight the current state of imaging and nonimaging hyperspectral data for early disease detection.The hybridization of NNhyperspectral approach has emerged as a powerful tool for disease detection and diagnosis.Spectral Disease Index(SDI)is the ratio of different spectral bands of pure disease spectra.Subsequently,we introduce NN techniques for rapid development of SDI.We also highlight current challenges and future trends of hyperspectral data.
基金We acknowledge the financial support by the German Research Foundation and the Open Access Publication Fund of the Technische Universitaet Berlin.
文摘This paper presents the study reports on evaluating a new transplanting operation by taking into accounts the interactions between soil,plant,and machine in line with the System of Rice Intensification(SRI)practices.The objective was to modify planting claw(kuku-kambing)of a paddy transplanter in compliance with SRI guidelines to determine the best planting spacing(S),seed rate(G)and planting pattern that results in a maximum number of seedling,tillers per hill,and yield.Two separate experiments were carried out in two different paddy fields,one to determine the best planting spacing(S=4 levels:s_(1)=0.16 m×0.3 m,s_(2)=0.18 m×0.3 m,s_(3)=0.21 m×0.3 m,and s_(4)=0.24 m×0.3 m)for a specific planting pattern(row mat or scattered planting pattern),and the other to determine the best combination of spacing with seed rate treatments(G=2 levels:g1=75 g/tray,and g2=240 g/tray).Main SRI management practices such as soil characteristics of the sites,planting depth,missing hill,hill population,the number of seedling per hill,and yield components were evaluated.Results of two-way analysis of variance with three replications showed that spacing,planting pattern and seed rate affected the number of one-seedling in all experiment.It was also observed that the increase in spacing resulted in more tillers and more panicle per plant,however hill population and sterility ratio increased with the decrease in spacing.While the maximum number of panicles were resulted from scattered planting at s_(4)=0.24 m×0.3 m spacing with the seed rate of g1=75 g/tray,the maximum number of one seedling were observed at s_(4)=0.16 m×0.3 m.The highest and lowest yields were obtained from 75 g seeds per tray scattered and 70 g seeds per tray scattered treatment respectively.For all treatments,the result clearly indicates an increase in yield with an increase in spacing.
基金supported by the Fakulti Pertanian,Universiti Putra Malaysia[Grant GP-IPM/2014/9434000].
文摘Agricultural crop abandonment negatively impacts local economy and environment since land,as a resource for agriculture,is not optimally utilized.To take necessary actions to rehabilitate abandoned agricultural lands,the identification of the spatial distribution of these lands must be acknowledged.While optical images had previously illustrated potentials in the identification of agricultural land abandonment,tropical areas often suffer cloud coverage problem that limits the availability of the imageries.Therefore,this study was conducted to investigate the potential of ALOS-1 and 2(Advanced Land Observing Satellite-1 and 2)PALSAR(Phased Array L-band Synthetic Aperture Radar)images for the identification and classification of abandoned agricultural crop areas,namely paddy,rubber and oil palm fields.Distinct crop phenology for paddy and rubber was identified from ALOS-1 PALSAR;nonetheless,oil palm did not demonstrate any useful phenology for discriminating between the abandoned classes.The accuracy obtained for these abandoned lands of paddy,rubber and oil palm was 93.33%±0.06%,78%±2.32%and 63.33%±1.88%,respectively.This study confirmed that the understanding of crop phenology in relation to image date selection is essential to obtain high accuracy for classifying abandoned and non-abandoned agricultural crops.The finding also portrayed that PALSAR offers a huge advantage for application of vegetation in tropical areas.
