The level of agricultural production efficiency (APE) affects farmers' livelihood decisions and the transformation and reconstruction of the rural territorial system. This paper constructs an evaluation index system of China's APE from the perspective of input–output. The spatial autocorrelation model and econometric model are used to calculate the spatio-temporal evolution characteristics and influencing

This study aimed to strengthen trust in the cross-border beef supply chain between Australia and China from a consumer perspective based on a blockchain-based supply chain implementation. Using a design science approach, this study’s initial prototype was developed to strength consumer trust. The study was conducted in partnership with Australian agricultural producers and processors, and empirically

The prediction of tree stem volumes has conventionally been based on simple field measurements and applicable allometric functions, but terrestrial laser scanning (TLS) has enabled new opportunities for extracting stem volumes of single trees. TLS-based tree dimensions are commonly estimated by automatized cylinder- or circle-based fitting approaches which, given that the stem cross-sections are relatively

The diet of seabirds can yield important insights into the status of economically and ecologically important fish. By analyzing the otoliths found in the birds’ droppings, researchers can observe which fish the birds eat in which abundances. However, identifying the species based on an otolith image is quite labor-intensive and requires particular expertise. In this work, we show that a deep convolutional

Accurate daily estimates of pasture biomass can improve the profitability of pasture-based dairy system by optimising input of feed supplements and pasture utilisation. However, obtaining accurate pasture mass estimates is a laborious and time-consuming task. The aim of this study was to test the performance of an integrated method combining remote sensing imagery acquired with a multispectral camera

Soil chemical variables are among the main factors that influence forest production; however, there is no consensus on which soil variables are most correlated with the individual volume spatial variability. Moreover, no studies that used the ordinary cokriging geostatistical technique to model the variability of the volume with soil chemical variables correlated as secondary variables in agroforestry

This paper explores how the energy-efficient integration of IoT-based sensing and blockchains, an innovation in the field of Digital Infrastructure technologies, can be used to incentivize virtuous behaviors in agricultural practices. The novelty of the study lies specifically in the unprecedented use of constrained sensing devices as trustworthy data sources for a permissionless blockchain. Furthermore

As the poultry farming industry attaches great importance to the welfare of poultry, an understanding of the daily behaviours of poultry is becoming more important. Eating behaviour is an important daily behaviour in poultry. Based on the difference between the eating vocalization and the normal vocalization of poultry, this study proposed an automatic detection method for the eating behaviour of poultry

When the harvester cuts the sugarcane, the forces acting on the cutter blade surfaces and the sugarcane roots are unclear, which is not conducive to further clarify the cutting mechanism of sugarcane and the role of the roots in the cutting process, as well as reduce the stubble damage rate. This paper aimed at: (1) verifying the rationality of the modeling method of sugarcane cutting system based

At present, processing substantial livestock excreta produced by numerous concentrated small–middle-type livestock farms (SMLFs) has been a major problem of livestock farm owners and government departments. To solve this problem, this study established a suitability evaluation system for the spatial layout of a centralized treatment center of livestock excreta (CTCLE). On this basis, combined with

Climate strongly determines the growing range of fruit plant species that can be grown successfully in an area, and also the cultivars that will perform best. Therefore, the assessment of the adequacy of a climate is critical for decision-making in the design of fruit orchards and vineyards, and also for the evaluation of the potential consequences of future climate on fruit production. Bioclimatic

It is of great significance to study the optimization control of greenhouse light environment that can meet the demands of crop growth and reduce the regulation cost to improve the production efficiency and economic benefits of greenhouse crops. However, due to the complexity of the actual optimization control problem of greenhouse light environment, such as multi-objective, high dimensionality and

High cost and low milk yield per dairy cow are current problems mainly faced by dairy farms in China. Thus, optimizing the regional layout and integrating the advantages to enhance the competitiveness of dairy farming in China is necessary. However, existing studies on comparative advantage analysis of dairy breeding have a relatively single perspective. Therefore, comprehensively identifying the advantage

Scientific studies on species identification in fish have considerable significance in aquatic ecosystems and quality evaluation. The morphological differences between different fish species are obvious. Machine learning methods use artificial prior knowledge to extract fish features, which is time-consuming, laborious, and subjective. Recently, deep learning-based identification of fish species has

Due to a series of issues raised in recent years, such as global water crisis, drought, and shortage of freshwater resources, researchers seek solutions to these problems by rationalizing water consumption in the agricultural sector as one of the most water-consuming sectors in the world. Wireless sensor networks (WSN) represent an exciting and important technology that has experienced significant

Energy demand by a controller extensively depends on how its control strategy incorporates the desired environment. For greenhouses, existing optimal environment considerations by the control strategies are fixed level reference trajectory and allowable range for control outputs. The fixed level reference approach only favours a reference trajectory taken from a specified permissible range, instead

Mangos are native to South and Southeast Asian regions. They are one of the favorite fruits consumed globally, with an overall estimated consumption reaching up to 50.65 million metric tons in 2017. However, the production of mango is usually severely affected by pests that attack the fruit, stem, root or mango leaf. Addressing the need for an early stage automated or semi-automated pest identification

Variable-rate technology (VRT) is necessary for the site-specific application of fertilizer. VRT can be used not only to minimize the amount of fertilizer used and fertilizer pollution but also to improve work efficiency and reduce the cost of production. However, the utilization of technology has been limited to the existing ground machines, and studies on UAV-based variable-rate fertilization have

Real-time irrigation scheduling systems attempt to eliminate crop water stress and achieve a high yield at harvest through the control of soil moisture. Artificial intelligence algorithms are possibly to learn the soil moisture dynamics in the soil-plant-atmosphere system and then are embedded into a low-cost controller to generate appropriate irrigation schedules. In this study, a neural network (NN)

Rapid quality assessment of nuts is important to increase the shelf life and minimise the nut loss due to rancidity. Existing methods for nut quality estimation are usually slow and destructive. In this study, a quick and non-destructive method using hyperspectral imaging (HSI) coupled with deep learning classification was applied for the quality estimation of unblanched kernels in Canarium indicum

The operational planning for agricultural production systems become an important tool for decision making for farmers. This paper shows a mathematical model as a decision support tool for crop maintenance planning problems. The model seeks the minimization of waste generated by the use of resources necessary for the task of crop maintenance. The model is inspired on the types of wastes from Lean Manufacturing

Poultry behavior is an important indicator for diagnosing poultry diseases. Accurate pose estimation is the basis of poultry behavior analysis, and it provides poultry disease warning methods. On large-scale poultry farms, it is usually a farmer or veterinarian who watches the pose of the broiler chicken to determine whether they are sick. When the posture of the bird is abnormal, the breeders can

Predicting the occurrence of B. oleae infestation is needed in sustainable olive tree growing, for the application of preventive control strategies. In this study, machine learning (ML) algorithms were tested to predict the occurrence of B. oleae infestation. Regional-based and long-term (2002–2019) dataset on infestation collected by trained technicians in the sampling network (Tuscany, central Italy)

Crop red–green–blue (RGB) images are powerful tools in nitrogen (N) nutrition estimation. Various regression models using crop N nutrition parameters and image indices have been suggested, but their accuracy and generalization performance for N estimation have not been thoroughly evaluated. In this study, a commercial digital camera was used to capture rice canopy RGB images in a 2-year field experiment

Crop type information such as its location and spatial distribution is relevant for agricultural planning and decision making about food sustainability and security. This information can be obtained through the analysis of images obtained through optical satellite remote sensing. Activities such as accurate discrimination of crops require dense time-series of satellite data which can capture the diverse

Chinese named entity recognition is a crucial initial step of information extraction in the field of agricultural diseases and pests. This step aims to identify named entities related to agricultural diseases and pests from unstructured texts but presents challenges. The available corpus in this domain is limited, and most existing named entity recognition methods only focus on the global context information

Airborne invasions of crop pests pose a significant challenge in agriculture. Novel infestations, such as the recently observed invasion of sugarcane aphid [Melanaphis sacchari (Zehntner) (Hemiptera:Aphididae)] on sorghum [Sorghum bicolor (L.) Moench] in the Great Plains of the U.S., emerge rapidly and require fast management actions to mitigate economic losses. Areawide integrated pest management

Standard methods for measuring pesticide deposition include water sensitive paper and fibre (paper or cord) collectors, which require time consuming manual steps to gather, process and interpret results. Measurement of pesticide deposition is important in evaluating the efficacy of a spray, which affects the total crop yield. A lack of knowledge about spray quality often results in the need to spray

Drought is a major area of interest within the field of water resources management, agriculture, energy resources and community health. Recently researchers have examined not only the mathematical expression of drought indices but also statistical predictions. Accordingly, high accuracy results were obtained using stand-alone machine learning techniques such as artificial neural networks (ANN) and

During spawn incubation in mushroom cultivation, spawns can be contaminated by a variety of pests and pathogenic molds, which cause virulent crop damage. Contaminated spawns must be classified and discarded before they are delivered to the fruiting stage. In most mushroom farms, humans visually classify spawn, which is labor-intensive and susceptible to human errors. To solve this problem, we designed

To provide technical support for lodging-resistant wheat breeding, post-disaster assessment, and analysis of factors affecting lodging, the dynamic and accurate extraction of lodging area is particularly important. Most existing methods of monitoring wheat lodging aim to extract the lodging area at a single growth stage, rendering the dynamic monitoring of wheat lodging highly difficult. Thus, this

Inertial motion sensors located on the animal have been used to study the behaviour of ruminant livestock. The time window size of segmented signal data can significantly affect the classification accuracy of animal behaviours. To date, there have been no studies evaluating the impact of a mixture of time window size features on the accuracy of animal behaviour classification. In this study, data was

Fast and accurate detection of kiwifruit in orchard under natural environment is the primary technology for yield estimation. Deep learning has become a prevalent way of fruit detection and achieved outstanding results. Besides, easy-carry smartphones are getting popular and powerful. In this paper, single shot multibox detector (SSD) with two lightweight backbones MobileNetV2 and InceptionV3 were

This paper presents the results of the evaluation of five deep learning architectures for the classification of soybean pest images. The performance of Inception-v3, Resnet-50, VGG-16, VGG-19 and Xception was evaluated for different fine-tuning and transfer learning strategies over a dataset of 5,000 images captured in real field conditions. The experimental results showed that the deep learning architectures

Plants’ dynamic eco-physiological responses are vital to their productivity in continuously fluctuating conditions, such as those in agricultural fields. However, it is currently still very difficult to capture these responses at the field scale for phenotyping purposes. Advanced hyperspectral imaging tools are increasingly used in phenotyping, and have been applied to detect changes in plants in response

In order to achieve rapid recognition of the common pests in agriculture and forestry, a new method based on deep convolution neural network was proposed. In this paper, the images of 19 insects and 1 larvae were collected. The data were enhanced by image processing methods such as flipping, rotating, scaling, adding Gussian noise and fancy PCA. The constructed image dataset CPAF had 73,635 insect

Monitoring some of the parameters that affect the quality of table olives for green processing is fundamental in a farmer's decision making. This work develops an affordable system for in-the-field evaluation of fruit calibre, ripeness and bruise index. The system consists of an illuminated cube that acquires images of fruit samples and generates an instantaneous report, using computer vision techniques

The recent advances in sensor technology have allowed accurate predictions of estrus events using animal behavior information. Behavioral variables generated by electronic feed and water bins have not been explored as potential predictors for estrus detection. The objectives of this study were: (i) to evaluate the effect of estrus expression on feed intake and animal behavior (feeding and drinking)

Humidity control, which is affected by the performance of humidifying device and structure of the container, is very important for delaying water loss of fresh products. Humidifying rate and humidity distribution uniformity in fresh-keeping container were investigated to evaluate the characteristic of humidity control by Computational Fluid Dynamics (CFD) models. A pressure gauge was adopted to measure

Sunflower lodging is a common agricultural disorder taking place in the middle and late sunflower growth periods. This disorder reduces the sunflower seed yield, damages the seed quality, and hence usually causes great losses in both crop quantity and quality. Sunflower lodging is mainly caused by extreme and destructive weather events, which have been recently occurring more frequently. This is why

Body condition scoring of livestock is widely used as a subjective method for assessing energy reserves and making management decisions for livestock. Since animal dimensions are often measured manually, the procedure is time-consuming, expensive and stressful for both the farmer and animal. Recent advances in three-dimensional sensor technology provide innovative tools for the design of automated

Agricultural drought has great impact on crop yields. Soil water content can directly reflect the degree of agricultural drought. The Water Cloud Model (WCM) is a vegetation contribution model which has been widely used in soil water content retrieval over vegetated areas. However, when optical remote sensing images are absent or are of a poor quality due to cloud cover and haze, the WCM parameters

In the field of agricultural information, identification and prediction of rice leaf diseases has always been a research focus. Deep learning and support vector machine (SVM) technology are hot research topics in the field of pattern recognition at present. Their combination can not only solve the problem effectively, but also improve the recognition accuracy. In this study, firstly, we use convolution

Measuring the bioelectric potential of plants is believed to be a suitable real time and noninvasive method of evaluating plant activities, including photosynthetic reactions. When plants are illuminated, the amplitude of their bioelectric potential response correlates to their photosynthetic rate. However, in practice, the variation of the illuminating colors, the bioelectric potential responses,

Macronutrients (phosphorus, potassium, calcium, and magnesium) and micronutrients (manganese, iron, copper, zinc, and boron) play an essential role not only in the general physiology of vines but also in the quality of wine produced. The quantity of each nutrient in the vine is generally determined by analyzing the leaf blades or petioles, but this approach imposes a typical delay of two weeks between

Robust vegetation segmentation is required for a vision-based weed control robot in an agricultural field operation. The output of vegetation segmentation is a fundamental element in the subsequent process of weed/crop discrimination as well as weed control actuation. Given the abundance of colour indices and thresholding techniques, it is still far from clear how to choose a proper threshold technique

During storage, the sweetness of kiwifruit increases and its firmness decreases quickly. Since the sweetness is linked to consumers’ taste preference, and the firmness is regarded as the primary indicator of kiwifruit eating ripeness, detecting the sweetness and firmness are welcome by kiwifruit sellers, consumers and processors. To make the detected results intuitive and acceptable to more people

The present investigation aims to develop symbolic regression based substitute to the FAO56 Penman-Monteith (FAO56-P-M) equation for calculating reference evapotranspiration (ET0) using meteorological data of thirty sites in northeast India. Further, five different input combination models were developed using a symbolic regression (SR) technique. Extraterrestrial radiation(Ra), altitude (Alt), maximum

Fish counting is a fundamental operation for biomass estimation in aquaculture. It is also vital for achieving reasonable feeding and improving breeding efficiency. Existing fish counting methods generally require each fish to be detected; in this regard, fish images with complex adhesions are difficult to process. Therefore, an automatic fish counting method using image density grading and local regression

Cotton (Gossypium hirsutum L.) is one of the main crops in Southern Xinjiang of China, and it is the major component of the regional economy. However, cotton cultivation in this region is facing severe challenges, e.g., the projected increase in the frequency of droughts and the decrease in precipitation in the future. Development and evaluation of deficit irrigation strategies in this region can potentially

A Discrete Element Method (DEM), a computerized testing rig and a soil bin were used to explain soil profile deformation caused by mouldboard plough. By using DEM, the motion of particles is given by collisions between particles. Soil-tillage tool interaction simulation was established by a 3D geometry of a mouldboard plough created using PTC Creo Parametric 3D Modelling software and soil bed modeled

Determining the index for monitoring the freshness of green pepper during storage is still a challenge to be solved in research to avoid food loss, linked to the economical loss. The aim of the present study was to investigate the potentiality of fluorescence spectroscopy for the determination of the freshness index. Time series fluorescence characteristics from different parts of green pepper (Capsicum

Robotic pruning is a potential solution to address the issues of labor shortages and high associated costs, but it has challenges due to the unstructured working environment. For successful robotic pruning, target branches have to be reached with fewer spatial requirements for the end-effector cutter and the manipulator. A three-rotational (3R) degrees of freedom (DoF) end-effector was designed considering

Increasing variability in energy-saving equipment and systems in the greenhouse industry raises the question of how to best utilize the various equipment in such a setting. The development of adequate solutions for deployment and control of this diversity of equipment has not kept pace with the innovations in the greenhouse industry. In earlier work a two-step dynamic optimization framework was developed