Farm Equipment Research Articles

AgriWealth: IoT based farming system

The agricultural sector in India accounts for a significant part of the country's GDP and is the primary income source for many farmers in rural areas. While it creates employment opportunities and offers food security for the entire nation, the lack of infrastructure and resources might be limiting its potential to thrive further. One of the aspects addressed in this paper is low yield production. With the aid of a sensor-based irrigation model, data is collected and analyzed in the cloud to enable real-time monitoring. It is then integrated with an Android application for displaying results in an user-friendly interface. Through the application, farmers can control the farm manually, or with a timer in minutes. The Machine Learning model predicts the suitable crops, in accordance with varying weather parameters. The application has a classified portal for farmers and customers to buy/sell directly, eliminating any involvement of mediators. One of the novelties in this research includes monitoring/controlling farm equipment and predicting field crops from a locally installed LCD display and keypad present in farmer's respective homes. The proposed work aims to create an energy-efficient, user-friendly framework for the agricultural workforce, yielding better crop production, improving farmers' living standards, and contributing effectively to the nation's economic growth. The prototype shows a reduction of water usage in fields by more than 60%. In order to incorporate the model with the best behavior in Android Application, different Machine Learning algorithms have been studied, among which Random Forest has been selected with a test accuracy of 91.59%.

Deep learning-based system development for black pine bast scale detection

The prevention of the loss of agricultural resources caused by pests is an important issue. Advances are being made in technologies, but current farm management methods and equipment have not yet met the level required for precise pest control, and most rely on manual management by professional workers. Hence, a pest detection system based on deep learning was developed for the automatic pest density measurement. In the proposed system, an image capture device for pheromone traps was developed to solve nonuniform shooting distance and the reflection of the outer vinyl of the trap while capturing the images. Since the black pine bast scale pest is small, pheromone traps are captured as several subimages and they are used for training the deep learning model. Finally, they are integrated by an image stitching algorithm to form an entire trap image. These processes are managed with the developed smartphone application. The deep learning model detects the pests in the image. The experimental results indicate that the model achieves an F1 score of 0.90 and mAP of 94.7% and suggest that a deep learning model based on object detection can be used for quick and automatic detection of pests attracted to pheromone traps.

Farm Fatal Injury Trends in Illinois from 1999 to 2019

HighlightsWe identified 510 fatal agricultural incidents in Illinois from 1999 to 2019.Tractors and roadway-related incidents were the two leading sources of fatalities.Older farmers (65 and older) accounted for the highest percentage of fatalities.Among tractor-related incidents, overturns accounted for the highest percentage.Abstract. The objective of this study was to analyze fatal injury trends and injury types in Illinois from 1999 to 2019. Data on fatal farm injuries in Illinois were collected from a newspaper clipping service. The data were analyzed by incident type and victim age. The types of farm-related incidents were classified as confined space, ATV, tractor, electrical, farm equipment, and other. From 1999 to 2019, the University of Illinois reported 510 fatal incidents, of which 213 (42%) were tractor-related. Tractor-related incidents represented the largest proportion of fatalities, followed by 82 (16%) roadway-related fatalities and 45 (9%) grain bin fatalities. In the past two decades, there has been an average of 24 fatalities per year. The number of incidents has declined over time, and the five-year moving average for 2019 was approximately 17 incidents. However, the proportion of tractor-related fatalities has remained consistent overtime and represents approximately 34% to 46% of all incidents per year on a five-year moving average. The results reflect a decreasing number of total farm fatalities in the past two decades with yearly fluctuations. Moreover, the results suggest that tractors remain one of the main causes of farm fatalities in Illinois. These results provide a better understanding of agricultural injuries in Illinois, which will help design targeted outreach efforts and provide new focus areas for research. Keywords: Agricultural fatality, Agriculture injuries, Farm fatalities, Injury, Newspaper clippings, Tractor fatalities.

Constraints of Farm Mechanization and Subsidies Distribution in the Agriculture Sector of Bihar

Farm mechanization in agriculture can play an important role in boosting food production with limited resources. The advantages of agricultural mechanization should be made available to all types of farmers, paying special attention to small and marginal farmers. The goal of the current study was to analyze the constraints to farm mechanization and the farm equipment subsidies program in Bihar's agriculture sector. Primary data have been collected by using the questionnaire method, from a total of 210 farmers of the Begusarai district of Bihar based on multistage sampling. The data were analyzed using the Garret ranking method. Results indicate that the large majority of respondents have chosen to give rank 1 to the constraint of ‘small and fragmented land holding’, followed by ‘high initial cost’ (rank 2) and lack of financial resources and credit facilities (rank 3). The study focuses on increasing the scope for farm mechanization through farm equipment subsidy programs and custom hiring services. Thus, the outcomes of the study will be helpful for policymakers for an effective distribution management system.

Evaluation of technical efficiency of some rain-fed cereal and legume crops production in Syria: does crisis matter?

BackgroundSyria is a developing country whose economy is still dominated by the agricultural sector. The agricultural sector is considered as the main source of food in Syria and a major source of employment and income generation. Food and agricultural policies in Syria focus heavily on achieving food security and improving its four pillars (availability, accessibility, stability and utilization). As a result, until 2011, a good progress has been attained in food availability. The food security situation deteriorated in Syria after 2011 crisis, with the number of people facing acute food insecurity rising from 7.9 million in 2020 to a staggering 12.4 million in 2021. This is the result of many shocks that the agricultural sector has been exposed to, such as the relative decrease in cultivated areas, high costs of production, reduced input availability including labour, prevailing violence, related damage to farm equipment, and abandoned land. In view of the changes that the agricultural sector has been exposed to in Syria as a result of the crisis, the study concerns measuring the technical efficiency of production of some rain-fed cereal and legume crops in Syria and comparing it in the pre and post-crisis period, which has started in 2011. A non-parametric (DEA) method is applied for measuring technical efficiency during the time period 2003–2010 (pre-crisis) and the period 2011–2018 (post-crisis) with censored regression (the tobit model) to investigate the determinants of technical efficiency. A t test is used to test the null hypothesis (H0) that there was no difference in technical efficiency of the production of studied crops before and after the crisis in Syria and the alternative hypothesis (Ha) that there was a significant difference in technical efficiency.ResultsThe findings show low level of technical efficiency in the post-crisis period. The results verified differences in the technical efficiency of pre- and post-crisis period. The use of censored regression with dummy for crisis has shown negative and significant effect on technical efficiency of each of the durum wheat and lentil crops, while it had no significant effect on the other studied crops.ConclusionsThis study can provide important information to the government to pursue a new policy for recovery and improving the agricultural production and productivity. There is an urgent need to adopt new policies that focus on providing production requirements in the form of low-interest loans, sustainable use of resources, providing support for the marketing process, and focusing on the export markets of some study crops (chickpeas and lentils). Government should improve agricultural extension services for farmers and encouraging them to adopt new technologies.

Farm Equipment Sharing in Emerging Economies

Farm Equipment Sharing in Emerging Economies

The Adoption of Bundled Sustainable Farm and Environmental Practices by Coffee Farmers in Southwest Ethiopia.

Despite numerous efforts to introduce sustainable farm and environmental practices (SFEPs), such as pruning, soil erosion control, and water pollution abatement measures), their adoption by smallholder farmers is awfully low in Ethiopia. As a result, smallholder coffee farmers in the country remain in poverty traps even if there is room to enjoy coffee returns by doubling the yield by implementing sustainable practices. On the other hand, most previous coffee sustainability studies focus on the economic, livelihood, and poverty alleviation impact of private sustainability standard schemes. Despite the holistic advantages of the adoption of bundled SFEPs over individual adoption practices, it has been overlooked by earlier scholars in the country. In southwest Ethiopia, few farmers applied sustainable coffee farm practices (particularly pruning, stumping, the use of fertilizer, and mulching), and the yields gained by the farmers are quite low. Therefore, this study seeks to examine the factors affecting the adoption of bundled SFEPs and their intensity at the farm household level in southwest Ethiopia based on cross-sectional data obtained from 153 sampled coffee farm households for the 2019/2020 cropping season. The study results showed that the farmers' adoption of different SFEPs depended on farm and management characteristics (total size of coffee holdings, multiple plots, remoteness of coffee farm, hired labor, and farming experience), socioeconomic variables (literacy, household size, and training), and Fairtrade coffee certification. Likewise, the intensity of SFEPs implementation is influenced by literacy and hired labor. Providing training and supplementing coffee farmers with farm equipment used for SFEPs, promoting small-scale mechanization options to address seasonal labor constraints, as well as strengthening Fairtrade organizations will facilitate the adoption of multiple SFEPs by coffee farmers in the country.

Factors that facilitate development of small agricultural cooperative farm alliances

Although cooperative movement in Russia has a pretty long history, achieving its proper functioning failed for a variety of reasons. With new support measures in place, namely, to establish a basic infrastructure - since 2015, to acquire assets and farm equipment, agro-processing equipment - since 2019, cooperatives in Russia geared to promoting small farms are expected to flare up. In this context, this paper reviews key statistical indicators of the current structural changes in agro-industry, as well as the health and contribution of small farms to the agricultural industry in general. This work aimed to identify preconditions for Russian farmers to form cooperatives. This is of the utmost importance since small farms produce nearly half of the country’s total agricultural output, own 37% of arable land, 56% of cattle, and ensure a quarter of employment. Through the research, a range of malpractices affecting the progress of small farms has been identified. They are dearth of modern technology, efficient staff, impossibility to invest in working capital, problems with marketing of produced goods, etc. Creating well-functioning agricultural cooperatives will address the above challenges today’s Russian farmers face.

Determinants of farmers’ knowledge on soil and water conservation technologies in dry zones of Central Highlands, Kenya


 
 
 This study ascertained the socioeconomic determinants of farmers’ knowledge on soil and water conservation technologies in Dry zones of Central Highlands of Kenya involving 400 farming households. Results showed that the majority of the farmers had inadequate knowledge on the use and benefits of soil and water conservation technologies. The socio-economic factors that influence knowledge levels of the knowledge-intensive technologies were education level, gender, perceptions on soil fertility, farmer group membership, access to training, farm size, access to credit, number of livestock kept and access to farm equipment. This implies that there is the need to come up with an all-inclusive policy that can be employed in improving farmer’s level of knowledge through the use of more innovative methods of information dissemination. This can be done by strengthening the existing farmer groups, enhancing extension services, and also formulating gender-friendly policies.
 
 

Behavior and body temperature alterations in piglets anesthetized for castration during a four-hour recovery phase

One way to eliminate pain during surgical castration is to provide general anesthesia by intramuscular injection. However, its disadvantage is the long recovery phase, during which anesthetized piglets have to be separated from the sow and managed appropriately. In this study, rectal temperatures, respiration rate, soiling and behavior changes were monitored in 119 piglets for 4 h after the intramuscularly administration of a ketamine-azaperone-mixture for general anesthesia and castration. The study aimed to identify the least distressing form of separation. For this, different types of separation containers, farm equipment and heat sources were used in 3 individual trials during separation of piglets. Over the course of the recovery period, body temperatures and behaviors of piglets underwent significant alterations. The temperature span was largest after 2 h in all trials (35.0–42.6 °C). Rectal temperatures were influenced by the kind of separation, heat provision, and age: Piglets separated in boxes were warmer than piglets separated in crate corners (P = 0.0016). Non-warmed piglets had lower temperatures than fully (P < 0.0001) warmed piglets. Additionally, rectal temperatures of 4-days old piglets were lower than those of 5-days old ones after 2 h (P < 0.0001). Piglets were more soiled after 4 h when they were not warmed compared to piglets in containers fully warmed (P < 0.0001). The kind of container also had an effect on soiling, as scores were higher after 2 h for piglets kept in buckets than those in perforated boxes (P = 0.0522). Warmed piglets breathed more frequently than non-warmed piglets (P = 0.0039). The behaviors pedaling and lying were more prominent in the first 2 h of the recovery period, while moving forward and head bumping occurred more often in the later half. The behavior slipping was only observed in buckets. It was concluded that the recovery phase is a stressful experience, especially for very young piglets. This means that piglets need to be taken care of appropriately to ensure that animal welfare is not reduced past a general anesthesia, which was originally applied to increase welfare during a painful intervention. Anesthetized piglets need to be warmed and possibly dried during the recovery phase to avoid life-threatening cooling.

Zero and controlled traffic improved soil physical conditions and soybean yield under no-tillage

Soil compaction can negatively affect a range of soil hydraulic, biogeochemical and plant physiological processes. A study conducted in Luján (Argentina) investigated the effect of three traffic treatments (zero, controlled, and random traffic) on soil physical properties and soybean yield over a period of eight years. The soil at the site (Typic Argiudoll) had been managed under continuous no-tillage for nine years. Field-wheeled areas under controlled and random traffic management were 3309 m2 ha−1 or 33.1% and 4622 m2 ha−1 or 46.2%, respectively. ‘Random’, non-controlled traffic farming represented the standard mechanisation management practice. The three traffic treatments relied on commercially available (unmodified) farm equipment. Results showed that soil cone Index (depth range: 0–450 mm) increased in the order: zero (1.90 ± 0.31 MPa) > controlled (2.46 ± 0.19 MPa) > random (3.75 ± 0.21 MPa) traffic, respectively, which therefore explained treatment differences in root biomass. Water infiltration rates decreased significantly with increased traffic footprint (by up to 35% in random traffic), which therefore reduced plant available water and influenced crop performance. Grain yields with zero traffic were fairly consistent between-years, but increased with controlled traffic (which progressively approached the yields achieved with zero traffic) and decreased in random traffic at average rates of 33 and 29 kg ha−1 per year, respectively. Treatment differences in grain yield widened in drier compared with wetter years when plant growth and yield were less constrained by water availability. An average yield penalty of ≈ 30% was recorded in random traffic relative to the other treatments. Gross income with random traffic was USD787 per ha, which compared to USD1179 and USD1116 per ha with zero and controlled traffic, respectively. The proposed approaches to mitigating adverse effects of compaction on crop productivity, sustainability and profitability appear to be cost-effective options and may be adopted when fully-matched machinery is not available. There is potential for future development of controlled traffic farming in Argentina.

Development of multiutility wheelbarrow

Wheelbarrow is a simple machine a large open container to move things, which belong to the second-class lever. This is because the load or resistance is placed between the effort and the fulcrum. Wheelbarrow can be used as farm equipment, industrial equipment, among others. A wheelbarrow might consists of a tray or bed composed of steel, wood, or plastic. A steel brace attaches this bed to steel support legs and to a steel or plastic wheel, with a rubber tire around. In two- or four-wheeled models, the wheels may be similar to bicycle tires, complete with inner tubes. Materials used in the construction of the wheelbarrow. Our goal is to innovate a product that is useful on everyday basis but also turns into a safety equipment when needed. With extensive research we have designed a wheelbarrow that is multipurpose in nature. It can be used as a normal wheelbarrow on the day-to-day activities and as a floatation device to carry load and children in terms of floods. Our process included everything from research into the selection of materials into the most optimum design that would be feasible both technically and economically. The analysis has been done by using Ansys. We also tuned the ergonomics of the wheelbarrow so that it is easy in operation which can be used on day-to-day basis.

Community engagement in the development and implementation of a rural road safety campaign: Steps and lessons learned

IntroductionRural crashes result in fatality rates twice as high as urban, after accounting for vehicle miles traveled, and those involving farm vehicles tend to be the most severe. Farm vehicle crash interventions have focused on the farm equipment (e.g., lighting and marking) or the farm vehicle operator (e.g., training), despite crashes being most frequently caused by other vehicle driver actions. Community-based campaigns focused on rural drivers have potential to influence driver behavior. The objective of this study was to describe the role, formation, and lessons learned from a community advisory board (CAB) in the development and dissemination of a community-based rural roadway safety campaign. MethodsThe CAB provided campaign input through quarterly meetings and email. The campaign had three main CAB and crash data-informed messages: 1) Slow Down, 2) Leave More Space, and 3) Avoid Passing. The CAB led campaign activities to publicize the message, distribute swag, and organize event logistics. To evaluate CAB effectiveness and inform future community engagement efforts, we conducted in-depth, semi-structured telephone interviews with CAB members in July 2020. Interviews were transcribed, coded, and codes were categorized into five main themes. ResultsOverall, CAB membership was described as an overwhelmingly positive experience in terms of the CAB structure, culture fostered among the group, responsibilities, and time commitment. Board members reported successful campaign implementation, gave positive feedback regarding the research team's engagement efforts, and provided valuable recommendations for future campaigns (e.g., adding social media components, expansion of CAB age and industry diversity, and increasing group bonding activities). ConclusionsResults from this study demonstrate the instrumental role and logistics involved in engagement of community advisors for the development and implementation of a rural roadway safety campaign. Steps and lessons from this study can be applied to other community-level injury and violence prevention topics, with a particular focus on rural communities.

Disinfection of various materials with 3-(trimethoxysilyl)-propyldimethyloctadecyl ammonium chloride in hatchery facilities.

ObjectiveSurface disinfection is important in the proper running of livestock farms. However, disinfection of farm equipment and facilities is difficult because they are made of different materials, besides having large surface areas and complex structures. 3-(trimethoxysilyl)-propyldimethyloctadecyl ammonium chloride (Si-QAC) is a quaternary ammonium salt-based disinfectant that attaches to various surfaces by forming covalent bonds and maintains its disinfecting capacity for a considerable time. Our aim was to evaluate the potential use of Si-QAC for disinfection of farm equipment and facilities.MethodsThe short- and long-term antimicrobial and antiviral effects of Si-QAC were evaluated in both laboratory and farm settings using modified quantitative assessment method based on the standard operating procedures of the United States Environmental Protection Agency.ResultsSi-QAC was highly effective in controlling the growth of the Newcastle disease virus and avian pathogenic Escherichia coli. Electron microscopy revealed that the mechanism underlying the disinfection activity of Si-QAC was associated with its ability to damage the outer membrane of the pathogen cells. In the field test, Si-QAC effectively reduced viral contamination of surfaces of equipment and space.ConclusionOur results suggest that Si-QAC has great potential as an effective chemical for disinfecting farm equipment and facilities. This disinfectant could retain its disinfection ability longer than other commercial disinfectants and contribute to better farm biosecurity.

Trust in the Adoption of Internet of Things for Smart Agriculture in Developing Countries

Trust in online environments is based on beliefs in the trustworthiness of a trustee, which is composed of three distinct dimensions - integrity, ability, and benevolence. Zimbabwe has slowly adopted Internet of Things for smart agriculture as a way of improving on food security in the country, though there is hesitancy by most farmers citing trust issues as monitoring of crops, animals and farm equipment’s would be done online through connecting several devices and accessing data. Farmers are facing difficulties in trusting that the said technology has the ability to perform as expected in a specific situation or to complete a required task, i.e. if the technology will work consistently and reliably in monitoring the environment, nutrients, temperatures and equipment status. The integrity of the collected data as it will be used for decision making. There is a growing need to determine how trust in the technology influence the adoption of IoT for smart agriculture in Zimbabwe. The mixed methodology was used to gather data from 50 A2 model farmers randomly sampled in Zimbabwe. The findings revealed that McKnight etal. trust in technology model can be used to influence the adoption of IoT through trusting that the technology will be reliable and will operate as expected.Additional constructs such as security and distrust of technology can be used as reference for future research.

Routine Activity Theory and Farm Equipment Theft: A Macro-Level Approach

Though a handful of studies have explored the relationship between farm characteristics and theft of farm equipment, all have been focused at the micro level. Put differently, they have sought to determine whether a relationship exists between likelihood of theft victimization and the characteristics (e.g., size, location) of individual farming operations. The current study builds upon this work by seeking to determine whether county-level factors (in line with the routine activity theory framework) serve to influence the incidence of farm equipment theft within counties. Data are derived from the National Incident-Based Reporting System, the Census of Agriculture and the United States Census of the Population. Results are on the whole supportive of the theory's application to the problem and suggest that macro-level investigations constitute a worthwhile approach to better understanding agricultural victimization.

The role of urban vegetable production in Jos (Nigeria) as a source of livelihood

Many cities of developing countries experience widespread poverty due to accelerated migration of people from rural to urban areas as well as high population growth rates. The city of Jos in Plateau State is experiencing rapid population growth as well, with the attendant problems of food insecurity, insufficient income, unemployment and environmental degradation. This study assessed the role that urban vegetable production plays in providing a source of livelihood to small-scale farmers in Jos. The farmers were registered with the third Fadama Project in Nigeria. Such projects derive their name from the native Hausa word ‘fadama’ which means irrigable lands on flood-prone and low-lying plains. Forty percent (40%) of urban vegetable farmers were randomly selected to have a sample size of 94 participants. A mixed method approach was used and this involved questionnaire-administered interviews. The primary data obtained were transcribed and subjected to ANOVA and t-test analysis. From the results obtained, most of the vegetables farm plots are located predominantly in the southern part of the study area. Results indicated that vegetable farming is playing an important role in providing 84% part-time and 5% full-time employment opportunities as well as reducing food insecurity among the study participants. In addition, most farmers achieved an income of more than the minimum wage of ₦30, 000 (US$ 72. 24) as approved by the Nigerian Government. The results also showed that lack of credit facilities, seasonal variations and the high cost of farm inputs and equipment are the most serious problems faced by participants. Other challenges associated with small-scale urban farming entailed the negative environmental impacts that may lead to the decline of environmental quality, thus undermining long term sustainability. Furthermore, there were no statistically significant differences among participants in terms of the relationship between the type of vegetables they produce, incomes generated, environmental impacts and their demographical attributes. These attributes are the age, gender, marital status, and educational background of participants. Based on these findings, and the socio-economic importance of vegetable farming in this study area, governments and financial institutions should establish better policies in order to solve the problems faced by small-scale vegetable farmers in urban areas.

Role of Agricultural Education Farm Workshop in Development of Students’ Skills in Indigenous Mechanized Technology for Self-Reliance in Rivers State

The study examined the role of agricultural education farm workshops in development of students’ skills in indigenous mechanized technology for self-reliance in Rivers State. Two research questions and two hypotheses were formulated for the study. The study adopted a descriptive research design. The sample size for the study was 293 respondents (278 students and 15 agricultural education lecturers) in the study area. The instrument for data collection was a self-structured questionnaire designed in a 4-point rating scale of agreement. The reliability of the instrument was established using the test-retest method which yielded 0.82. Data was analyzed using mean and standard deviation with a criterion mean value of 2.50 and above while a z-test statistical tool was used to test the null hypotheses at a significance level of 0.05. Findings from the study revealed that agricultural education workshop gives students access to hands-on-experience on the production of indigenous mechanized technologies for farming activities, improves students’ skills in construction and installation of agricultural indigenous mechanized tools. The study also revealed that agricultural education farm workshops inculcate students with the required skills in maintenance of indigenous mechanized farm equipment and aid students access to industrial workshop activities. Based on the findings, the study recommends that government at all levels should provide well-equipped farm workshops for agricultural education programmes to train and inculcate students with the necessary skills that will enhance the fabrication of agricultural indigenous mechanized technology.

Farm vehicle crashes on public roads: Analysis of farm-level factors.

Rural public roads experience higher crash fatality rates than other roadways, with agricultural equipment adding greater risk of injury and fatality. This study set out to describe farmers' experiences with farm equipment crashes and predictors of crashes at the farm level. A survey of farm operators was conducted in 9 Midwestern states (IL, IA, KS, MN, MO, NE, ND, SD, and WI) in collaboration with the US Department of Agriculture's National Agricultural Statistical Service. From 1,282 farms operating equipment on public roads in 2013, 7.6% of farmers reported that equipment from their farm had ever been in a crash (n = 97). Crashes occurred most often in June-August (44.0%) and were most often reported as being during the daytime (71.3%), on dry roads (79.4%), or in clear weather (71.4%). While most farmers responded that they were driving the farm equipment at the time of the crash (52.0%), nearly half of crashes involved their employees as the driver (48.0%). Crashes often went unreported to law enforcement (28.6%). To illustrate crash probabilities for farms with different profiles, we included farm acreage, crop farming, vehicle horsepower, annual miles driven, and the total number of farm vehicles driven on public roads in a predictive model. Large crop farms of 241+ acres, those who drove farm vehicles 1,430+ miles per year, and those with 20 or more farm vehicles had the highest probability of crash of 0.14.

Application of Digital Technologies for the Next Level of Agriculture Growth and Transformation under Changing the Indian Agriculture: A Critical Review

The rapid population growth has driven the demand for more food, fiber, energy, and water, which is associated to an increase in the need to use natural resources in a more sustainable way. The growing connectivity in the rural environment, in addition to its greater integration with data from sensor systems, remote sensors, equipment, and smart-phones have paved the way for new concepts from the so-called digital agriculture. The information that crops offer is turned into profitable decisions only when efficiently managed. Current advances in data management are making Smart Farming grow exponentially as data have become the key element in modern agriculture to help producers with critical decision-making. Valuable advantages appear with objective information acquired through sensors with the aim of maximizing productivity and sustainability. These kind of data-based managed farms rely on data that can increase efficiency by avoiding the misuse of resources and the pollution of the environment. Data-driven agriculture, with the help of robotic solutions incorporating artificial intelligent techniques, sets the grounds for the sustainable agriculture of the future. Digital agriculture offers far-reaching opportunities for accelerating agricultural transformation. Although there are concerns that digital agriculture will enhance the market power of large agribusiness enterprises and increase the digital divide, a combination of new actors and public action can help accelerate the supply of digital agricultural technology, manage threats of market concentration, and harness the opportunities of digital agriculture for all.&#x0D; The agriculture industry has radically transformed over the past 50 years. Advances in machinery have expanded the scale, speed, and productivity of farm equipment, leading to more efficient cultivation of more land. Seed, irrigation, and fertilizers also have vastly improved, helping farmers increase yields. Now, agriculture is in the early days of yet another revolution, at the heart of which lie data and connectivity. Artificial intelligence, analytics, connected sensors, and other emerging technologies could further increase yields, improve the efficiency of water and other inputs, and build sustainability and resilience across crop cultivation and animal husbandry. This paper reviews the current status of advanced farm management systems by revisiting each crucial step, from data acquisition in crop fields to variable rate applications, so that growers can make optimized decisions to save money while protecting the environment and transforming how food will be produced to sustainably match the forthcoming population growth.