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Quarterly published in print and online "Inventi Impact: Agro Tech" publishes high quality unpublished as well as high impact pre-published research and reviews catering to the needs of researchers and professionals. This multidisciplinary journal deals with all the aspects related to involvement of basic and applied sciences and technology in the field of agriculture. Articles are welcome pertaining to soil science, horticulture, agronomy, plant pathology, entomology, plant science, animal science, aquaculture, food science and technology, agricultural engineering, agricultural machinery, post-harvest technology, agricultural biotechnology, plant and animal biotechnology, microbial biotechnology, agricultural extension, agricultural development, agricultural economics, rural development, sustainable agriculture, environmental technology and other related fields.
A conceptual model was developed based on the two basic spatial elements of area-wide integrated pest management (AW-IPM), a core area and a buffer zone, to determine the minimum size of the protected area for the program to be technically feasible and economically justifiable. The model consisted of a biological part (insect dispersal) and an economic part. The biological part used random walks and diffusion equations to describe insect dispersal and to determine the minimum width of the buffer zone required to protect the core area from immigration of pests from outside. In the economic part, the size of the core area was calculated to determine the point at which the revenues from the core area equal the control costs. This model will need to be calibrated and validated for each species and geographic location. Tsetse flies and the Mediterranean fruit fly are used as case studies to illustrate the model....
Plant diseases pose a significant challenge for food production and safety. Therefore, it is
indispensable to correctly identify plant diseases for timely intervention to protect crops from massive
losses. The application of computer vision technology in phytopathology has increased exponentially
due to automatic and accurate disease detection capability. However, a deep convolutional
neural network (CNN) requires high computational resources, limiting its portability. In this study,
a lightweight convolutional neural network was designed by incorporating different attention modules
to improve the performance of the models. The models were trained, validated, and tested
using tomato leaf disease datasets split into an 8:1:1 ratio. The efficacy of the various attention modules
in plant disease classification was compared in terms of the performance and computational
complexity of the models. The performance of the models was evaluated using the standard classification
accuracy metrics (precision, recall, and F1 score). The results showed that CNN with attention
mechanism improved the interclass precision and recall, thus increasing the overall accuracy
(>1.1%). Moreover, the lightweight model significantly reduced network parameters (~16 times) and
complexity (~23 times) compared to the standard ResNet50 model. However, amongst the proposed
lightweight models, the model with attention mechanism nominally increased the network complexity
and parameters compared to the model without attention modules, thereby producing better
detection accuracy. Although all the attention modules enhanced the performance of CNN, the
convolutional block attention module (CBAM) was the best (average accuracy 99.69%), followed by
the self-attention (SA) mechanism (average accuracy 99.34%)....
In Thailand, sugarcane mills have faced supply and demand imbalance problems. Solving such problems is\ncomplicated due to various substantial factors. Sugarcane cultivation and harvest are important processes since they are the\nearly stages of the sugarcane industry. Cultivation and harvest planning can be designed by using optimization model in order\nto balance supply and demand. This paper proposes a linear optimization model used in sugarcane cultivation and harvest\nplanning with multiple suppliers. Sugarcane survival rate is one of the important factors considered in the presented model.\nA case study of the large-size sugarcane mills in Thailand was investigated. Many other significant factors were considered\nsuch as cultivating land size, sugarcane type, harvesting capacity, and delivery contract with the mill. The objective function\nwas to maximize commercially recoverable sugar content in sugarcane (C.C.S.) of the total amount of sugarcane supplied to\nmill. This model can be applied as a supply management tool for both farmers and the mill management based on real\nsituation....
There is a growing interest in using miniature multi-sensor technology to\nmonitor plant, soil, and environmental conditions in greenhouses and in field\nsettings. The objectives of this study were to build a small multi-channel\nsensing system with ability to measure visible and near infrared light reflectance,\nrelative humidity, and temperature, to test the light reflectance sensors\nfor measuring spectral characteristics of plant leaves and soilless media, and\nto compare results of the relative humidity and temperature sensors to identical\nmeasurement obtained from a greenhouse sensor. The sensing system\nwas built with off-the-shelf miniature multispectral spectrometers and relative\nhumidity and temperature sensors. The spectrometers were sensitive to\nvisible, red-edge, and near infrared light. The system was placed in a greenhouse\nsetting and used to obtain relative reflectance measurements of plant\nleaves and soilless media and to record temperature and relative humidity\nconditions in the greenhouse. The spectrometer data obtained from plant leaf\nand soilless media were compatible with baseline spectral data collected with\na hyperspectral spectroradiometer. The greenhouse was equipped with a relative\nhumidity and temperature sensor. The relative humidity and temperature\nsensor measurements from our sensor system were strongly correlated with\nthe relative humidity and temperature results obtained with the greenhouse\nsensors (i.e. , correlation coefficients > 0.70 or <--0.70), and the mean relative\nhumidity and temperature sensor values were similar for our system and the\ngreenhouse system. Overall, the proposed sensor showed good potential as a\ntool to measure spectral response patterns of plant and potting mix material\nand environmental conditions relevant to greenhouse research. The system\nwas inexpensive to build; the total cost of its components was 123 Dollars ....
In order to improve robotic harvesting and reduce production cost, a harvesting robot system for strawberry on the\r\nelevated-trough culture was designed. It was supposed to serve for sightseeing agriculture and technological education. Based\r\non the sonar-camera sensor, an autonomous navigation system of the harvesting robot was built to move along the trough lines\r\nindependently. The mature fruits were recognized according to the H (Hue) and S (Saturation) color feature and the picking-point\r\nwere located by the binocular-vision unit. A nondestructive end-effector, used to suck the fruit, hold and cut the fruit-stem, was\r\ndesigned to prevent pericarp damage and disease infection. A joint-type industrial manipulator with six degrees-of-freedom (DOF)\r\nwas utilized to carry the end-effector. The key points and time steps for the collision-free and rapid motion of manipulator\r\nwere planned. Experimental results showed that all the 100 mature strawberry targets were recognized automatically in the\r\nharvesting test. The success harvesting rate was 86%, and the success harvesting operation cost 31.3 seconds on average,\r\nincluding a single harvest operation of 10 seconds. The average error for fruit location was less than 4.6 mm....
The potential of the globe artichoke biodiversity in the Mediterranean area is enormous\nbut at risk of genetic erosion because only a limited number of varieties are vegetatively propagated\nand grown. In Apulia (southern Italy), the Regional Government launched specific actions to rescue\nand preserve biodiversity of woody and vegetable crops in the framework of the Rural Development\nProgram. Many globe artichoke ecotypes have remained neglected and unnoticed for a long time\nand have been progressively eroded by several causes, which include a poor phytosanitary status.\nSanitation of such ecotypes from infections of vascular fungi and viruses may be a solution for their\nex situ conservation and multiplication in nursery plants in conformity to the current EU Directives\n93/61/CEE and 93/62/CEE that enforce nursery productions of virus-free and true-to-type certified\nstocks. Five Apulian ecotypes, Bianco di Taranto, Francesina, Locale di Mola, Verde di Putignano\nand Violetto di Putignano, were sanitized from artichoke Italian latent virus (AILV), artichoke latent\nvirus (ArLV) and tomato infectious chlorosis virus (TICV) by meristem-tip culture and in vitro\nthermotherapy through a limited number of subcultures to reduce the risk of Ã¢â?¬Å?pastel variantsÃ¢â?¬Â\ninduction of and loss of earliness. A total of 25 virus-free primary sources were obtained and\nconserved ex situ in a nursery....
Sunburn in fruit is caused by excess heat and radiation and has a major economic impact on apple production. Evaporative cooling can be used to keep the apple temperatures below a critical value, but the process needs to be optimised for maximum cooling effect and to avoid excessive use of water. A numerical model was developed to predict the skin and core temperatures of an apple subjected to evaporative cooling. The method makes use of climatic data recorded by a weather station. The model predicted apple skin and core temperatures accurately with a maximum error of 6.4%. The drop in skin temperature when evaporative cooling was applied could be accurately predicted with an error of 5.3%. The results indicate that the model can be used, in combination with a control system and input from a weather station, to control and manage an evaporative cooling system....
Self-propelled fruit harvesters (SPFHs) are agricultural machines designed to facilitate\nfruit picking and other tasks requiring operators to stay close to the foliage or to the upper part\nof the canopy. They generally consist of a chassis with a variable height working platform that\ncan be equipped with lateral extending platforms. The positioning of additional masses (operators,\nfruit bins) and the maximum height of the platform (up to three meters above the ground) strongly\naffect machine stability. Since there are no specific studies on the lateral stability of SPFHs, this study\naimed to develop a specific test procedure to fill this gap. A survey of the Italian market found 20 firms\nmanufacturing 110 different models of vehicles. Observation and monitoring of SPFHs under real\noperational conditions revealed the variables mostly likely to affect lateral stability: the position and\nmass of the operators and the fruit bin on the platform. Two SPFHs were tested in the laboratory to\ndetermine their centre of gravity and lateral stability in four different settings reproducing operational\nconditions. The test setting was found to affect the stability angle. Lastly, the study identified two\nspecific settings reproducing real operational conditions most likely to affect the lateral stability of\nSPFHs: these should be used as standard, reproducible settings to enable a comparison of results....
An agricultural model for allocation of crops is considered in this work using Pollination Intelligence Method. The model was\nconstructed to solve farmerâ??s decision making in allocating crops to a piece of land using market price, known yield of crops, cost\nincurred during planting, and the total amount of land available. A new class of metaheuristic method called Flower Pollinated\nAlgorithm is also presented in this work to solve the designed model. An improved version of the Flower Pollinated Algorithm\ncalled Pollination Intelligence Algorithm using an iterative scheme to override the switch parameter in Flower Pollinated\nAlgorithm is also presented and used in solving the designed model. A case study of a farmer in Ife, Osun State, Nigeria, was used\nto implement the model, and the results obtained suggested that instead of allocating crops to land randomly based on farmerâ??s\nintuition, cost of planting, yield of crops, and market price were factors that must be considered by farmers for optimal profit\nbefore planting crops....
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