agriculture

摘要： The study evaluated the synergy between the indicators of rainfall,vegetation cover,land productivity in crop production,livestock production and the relationship between the value of aggregate agricultural production and the gross domestic product of municipalities in the semi-arid region of the State of Ceará,Brazil.The data sources are:CearáMeteorology and Water Resources Foundation(FUNCEME)and Brazilian Institute of Geography and Statistics(IBGE)for the years 1996,2006 and 2017.The research used the methodology of factor analysis(FA),with decomposition into principal components,to construct the index of agricultural production preservation(IAPP).The results showed that 1996 had the best rainfall levels and the highest IAPP values compared to the other years studied.Year of 2017 was the last one of a draught period that extended in Cearáfrom 2012 to 2017.In that year the lowest values for IAPP were observed.The main conclusion is:there was the expected interaction between rainfall and agricultural preservation indicators applied in the semi-arid region of the state of Cearáin the years 1996,2006 and 2017.

摘要： Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAASS).The latest IF is 2.848.JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.JIA publishes manuscripts in the categories of Commentary,Review,Research Article.

摘要： Brewery grains have a long history in animal feed. This use in animal feed nevertheless poses a problem, that of bad odors due to the sometimes too long shelf life of spent grains. The objective of this work is to recover spent grains from the BB brewery in Lomé by composting in order to stabilize them. A compost based solely on spent grains was produced after 5 months. The physico-chemical and spectroscopic characterizations at the end of the composting process revealed that the compost obtained has interesting properties with a pH = 7.01;a C/N ratio of 13.7 and a low level of heavy metals (Pb = 1.23 mg/kg, Cd = 0.04 mg/kg etc.).

摘要： Land Management Systems (LMS) are institutional frameworks complex by the tasks they must achieve, national, cultural, political, and judicial settings and technology. The urbanisation process in Nigeria has increased since the 1960s because of the crude oil boom era and other government-backed industrial initiatives and investments. This study employed the use of both primary and secondary sources of data. Preliminary data comprise methods of land use, types of agricultural activities carried out and the process of working on the land by the farmers within a 10 km radius. The secondary data involved the interactive digital and visual techniques of the Geographical Information system for five seasons, with each having a ten-year interval span within 1975 to 2015. Statistical analysis was carried out with SPSS 2013 and XLSTAT 2015. Five land use and land cover types were observed within the Gidan Kwano watershed, which includes wetlands (WL), water bodies (WB), bare grounds (BG), vegetation (VG), and settlements (SL). The most prevalent landform in the study area during the 1975 period was the vegetative area which was 50% of the total landmass. Thus, the vegetation (VG) covered half of the Gidan Kwano watershed. However, the vegetative area decreased substantially during the study period of 1975 to 2015. It was observed that the vegetation (VG) within the study area had the highest percentage of coverage, of 34%. During the study period, a significant decrease was observed in the WL, WB and VG areas. It was also concluded that due to the built-up places, the infiltration of surface runoff from rainwater would be drastically reduced as most of the sections are paved for construction activities while a section of the study area is covered with rock outcrops and farmlands.

摘要： Archaeologists at first regarded the appearance of pottery as the beginning of the Neolithic age,and later the appearance of agriculture as the entry of the Neolithic age.

摘要： Aims and Scope Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinsese Association of Agricultural Science Societies(CAASS).The latest IF is 2.848.JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide.

摘要： Description Journal of Integrative Agriculture(JIA),formerly Agricultural Sciences in China(ASC),founded in 2002,is sponsored by Chinese Academy of Agricultural Sciences(CAAS),co-sponsored by Chinese Association of Agricultural Science Societies(CAASS).JIA is a peer-reviewed and multi-disciplinary international journal and published monthly in English.JIA Editorial Board consists of 275 well-respected scholars of agricultural scientific fields.

摘要： Due to the inconsistency of rice variety,agricultural industry faces an important challenge of rice grading and classification by the traditional grading system.The existing grading system is manual,which introduces stress and strain to humans due to visual inspection.Automated rice grading system development has been proposed as a promising research area in computer vision.In this study,an accurate deep learning-based non-contact and cost-effective rice grading system was developed by rice appearance and characteristics.The proposed system provided real-time processing by using a NI-myRIO with a high-resolution camera and user interface.We firstly trained the network by a rice public dataset to extract rice discriminative features.Secondly,by using transfer learning,the pre-trained network was used to locate the region by extracting a feature map.The proposed deep learning model was tested using two public standard datasets and a prototype real-time scanning system.Using AlexNet architecture,we obtained an average accuracy of 98.2%with 97.6%sensitivity and 96.4%specificity.To validate the real-time performance of proposed rice grading classification system,various performance indices were calculated and compared with the existing classifier.Both simulation and real-time experiment evaluations confirmed the robustness and reliability of the proposed rice grading system.

摘要： Precipitation prediction(PP)have become one of the significant research areas of deep learning(DL)and machine vision(MV)techniques are frequently used to predict the weather variables(WV).Since the climate change has left significant impact upon weather variables(WV)and continuously changes are observed in temperature,humidity,cloud patterns and other factors.Although cloud images contain sufficient information to predict the precipitation pattern but due to changes in climate,the complex cloud patterns and rapid shape changing behavior of clouds are difficult to consider for rainfall prediction.Prediction of rainfall would provide more meticulous assistance to the farmers to know about the weather conditions and to care their cash crops.This research proposes a framework to classify the dark cloud patterns(DCP)for prediction of precipitation.The framework consists upon three steps to classify the cloud images,first step tackles noise reduction operations,feature selection and preparation of datasets.Second step construct the decision model by using convolutional neural network(CNN)and third step presents the performance visualization by using confusion matrix,precision,recall and accuracy measures.This research contributes(1)real-world clouds datasets(2)method to prepare datasets(3)highest classification accuracy to predict estimated as 96.90%.

摘要： Information extraction plays a vital role in natural language processing,to extract named entities and events from unstructured data.Due to the exponential data growth in the agricultural sector,extracting significant information has become a challenging task.Though existing deep learningbased techniques have been applied in smart agriculture for crop cultivation,crop disease detection,weed removal,and yield production,still it is difficult to find the semantics between extracted information due to unswerving effects of weather,soil,pest,and fertilizer data.This paper consists of two parts.An initial phase,which proposes a data preprocessing technique for removal of ambiguity in input corpora,and the second phase proposes a novel deep learning-based long short-term memory with rectification in Adam optimizer andmultilayer perceptron to find agricultural-based named entity recognition,events,and relations between them.The proposed algorithm has been trained and tested on four input corpora i.e.,agriculture,weather,soil,and pest&fertilizers.The experimental results have been compared with existing techniques and itwas observed that the proposed algorithm outperformsWeighted-SOM,LSTM+RAO,PLR-DBN,KNN,and Na飗e Bayes on standard parameters like accuracy,sensitivity,and specificity.

摘要： Because of the development of wireless commu-nication technology and circuit miniaturization techniques lately,the wireless sensor network using intelligent environmental sensor has become available.Many studies on Ubiquitous computing and ad-hoc network are being conducted by using such wireless sensor network.Sensor Node is operated by limited energy resources.Consequently,emerging issues these days are how effective use the limited energy resources should be used to extend the life span of sensor node and to make sensor network be maintained for a long time.On the assumption that sensor node is used for optimizing the growth environment of the crops in the agricultural sector,this study suggested using variable time scheduling based on the residual energy of sensor node so as to extend the life span of sensor node in a Glass greenhouse.If data is transferred from sensor node through variable time scheduling,sensor node might adjust a cycle of data transfer based on the residual average energy of an adjacent node,and might reduce energy consumption of a wireless module which consumes energy most. Consequently,it's thought that variable time scheduling might extend the life span of sensor node and make sensor network be operated stably.

摘要： Because of the development of wireless commu-nication technology and circuit miniaturization techniques lately,the wireless sensor network using intelligent environmental sensor has become available.Many studies on Ubiquitous computing and ad-hoc network are being conducted by using such wireless sensor network.Sensor Node is operated by limited energy resources.Consequently,emerging issues these days are how effective use the limited energy resources should be used to extend the life span of sensor node and to make sensor network be maintained for a long time.On the assumption that sensor node is used for optimizing the growth environment of the crops in the agricultural sector,this study suggested using variable time scheduling based on the residual energy of sensor node so as to extend the life span of sensor node in a Glass greenhouse.If data is transferred from sensor node through variable time scheduling,sensor node might adjust a cycle of data transfer based on the residual average energy of an adjacent node,and might reduce energy consumption of a wireless module which consumes energy most. Consequently,it's thought that variable time scheduling might extend the life span of sensor node and make sensor network be operated stably.

摘要： Because of the development of wireless commu-nication technology and circuit miniaturization techniques lately,the wireless sensor network using intelligent environmental sensor has become available.Many studies on Ubiquitous computing and ad-hoc network are being conducted by using such wireless sensor network.Sensor Node is operated by limited energy resources.Consequently,emerging issues these days are how effective use the limited energy resources should be used to extend the life span of sensor node and to make sensor network be maintained for a long time.On the assumption that sensor node is used for optimizing the growth environment of the crops in the agricultural sector,this study suggested using variable time scheduling based on the residual energy of sensor node so as to extend the life span of sensor node in a Glass greenhouse.If data is transferred from sensor node through variable time scheduling,sensor node might adjust a cycle of data transfer based on the residual average energy of an adjacent node,and might reduce energy consumption of a wireless module which consumes energy most. Consequently,it's thought that variable time scheduling might extend the life span of sensor node and make sensor network be operated stably.