Huanglongbing (HLB) is a devastating citrus disease worldwide. A three-pronged approach to controlling HLB has been suggested, namely, removal of HLB-symptomatic trees, psyllid control, and replacement with HLB-free trees. However, such a strategy did not lead to successful HLB control in many citrus-producing regions, such as Florida. We hypothesize that this is because of the small-scale or incomprehensive implementation of the program; conversely, a comprehensive implementation of such a strategy at the regional level can successfully control HLB. To test our hypothesis, we investigated the effects of region-wide comprehensive implementation of this scheme to control HLB in Gannan region, China, with a total planted citrus acreage of over 110,000 ha from 2013 to 2019. With the region-wide implementation of comprehensive HLB management, the overall HLB incidence in Gannan decreased from 19.71% in 2014 to 3.86% in 2019. A partial implementation of such a program (without a comprehensive inoculum removal) at the regional level in Brazil resulted in HLB incidence increasing from 1.89% in 2010 to 19.02% in 2019. Using dynamic regression model analyses with data from both Brazil and China, we constructed a model to predict HLB incidence when all three components were applied at 100%. It was predicated that in a region-wide comprehensive implementation of such a program, HLB incidence would be controlled to a level of less than 1%. We conducted economic feasibility analyses and showed that average net profits were positive for groves that implemented the comprehensive strategy, but groves that did not implement it had negative net profits over a 10-year period. Overall, the key for the three-pronged program to successfully control HLB is the large scale (region-wide) and comprehensiveness in implementation. This study provides valuable information to control HLB and other economically important endemic diseases worldwide. [ ] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Internet of Things (IoT) technologies are widely recognized as one of the most important infrastructures for economic development and technological innovation. By analyzing the influencing factors of vegetable farmers’ intention to adopt agricultural IoT, it helps to formulate effective IoT promotion policies and accelerate the realization of agricultural modernization. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology-Organization-Environment (TOE) theory, this study constructed for the first time a mechanism model of the influence of vegetable farmers’ intention to adopt IoT, expanding the scope of current research on agricultural IoT and revealing the intrinsic influence mechanism of farmers’ adoption of IoT technologies. In this study, 357 quantitative data were obtained by a questionnaire survey, and structural equation modeling was used to test the direct and indirect effects of each factor on vegetable farmers’ intention to adopt IoT. The results show that almost all variables in TOE have significant direct impacts on the intention, while no variables in UTAUT have significant direct impacts. Among variables in TOE, government support and complexity are the two most important elements influencing the intention. Although the interactions among variables in TOE and UTAUT are also found, the indirect effects of variables are non-significant. Therefore, it is proposed to reduce the complexity of operation and use of IoT technologies; improve rural information infrastructure and compatibility of IoT platforms and devices; and governments should increase subsidies, and incentives to promote the use of IoT in agriculture and agricultural practices.

Strawberries (Fragaria × ananassa Duch.) are highly perishable fruit. Timely prediction of yield is crucial for labor management and marketing decision-making. This study demonstrates the use of high-resolution ground-based imagery, in addition to previous yield and weather information, for yield prediction throughout the season at different intervals (3–4 days, 1 week, and 3 weeks pre-harvest). Flower and fruit counts, yield, and high-resolution imagery data were collected 31 times for two cultivars (‘Florida Radiance’ and ‘Florida Beauty’) throughout the growing season. Orthorectified mosaics and digital surface models were created to extract canopy size variables (canopy area, average canopy height, canopy height standard deviation, and canopy volume) and visually count flower and fruit number. Data collected at the plot level (6 plots per cultivar, 24 plants per plot) were used to develop prediction models. Using image-based counts and canopy variables, flower and fruit counts were predicted with percentage prediction errors of 26.3% and 25.7%, respectively. Furthermore, by adding image-derived variables to the models, the accuracy of predicting out-of-sample yields at different time intervals was increased by 10–29% compared to those models without image-derived variables. These results suggest that close-range high-resolution images can contribute to yield prediction and could assist the industry with decision making by changing growers’ prediction practices.

The US produce industry faces intensifying competition from imports, particularly those from Mexico, the largest exporter of produce to the United States. Fresh produce imports from Mexico have grown dramatically in recent years. This study examines the impact of increasing fresh tomato imports from Mexico on market price and revenue of US growers. Results show that tomato prices are highly sensitive to supply, suggesting a saturated market. Imports from Mexico have significant negative impacts on the prices of US domestic tomatoes. A scenario of 50% increase in tomato imports from Mexico could result in a $252 million (27%) revenue loss for American growers, thus posing great challenges to the sustainability of the declining US tomato industry.

The Florida tomato industry is facing challenges of increased production costs and decreased yields resulting from the methyl bromide (MBr) phase-out under the Montreal Protocol for environmental concerns. MBr and several accepted alternative soil fumigant systems are analyzed in this study from an economic perspective. This article focuses on identifying optimal fumigant systems by analyzing the cost effectiveness and economic risk associated with MBr and several other commercially available soil fumigant systems using data collected from scientific field trials. The results obtained show that a 67:33 formulation of MBr: chloropicrin is the most cost-effective treatment, and no alternative fumigant systems investigated can substitute MBr cost-effectively in Florida tomato production. The analysis indicated that switching from MBr (67:33) to the new industry standard PicChlor 60 approximately resulted in a loss of $3,569 per acre in gross revenue and $1,656 per acre in profit using market prices in the 2013/14 season. Higher market prices would further increase the loss.

Bacterial spot of tomato (BST) is a disease that severely afflicts tomato crops, especially in geographic areas such as the Southeastern U.S., where the environmental conditions favor rapid disease development. Farmers usually use chemical treatments such as copper–mancozeb mixtures and acibenzolar-S-methyl, among other methods, to manage BST. However, these chemical treatments generally fail to improve marketable yields, thus raising the question of whether the BST treatments are economical. We evaluated the efficacy and profitability of bactericide treatments consisting of copper-mancozeb, acibenzolar-S-methyl, and streptomycin, as well as three inoculation levels of Xanthomonas euvesicatoria pv. perforans, on the management of BST in Florida. Across three separate field trials, BST severity was inversely correlated with marketable tomato yields; however, bactericide treatments provided no statistical improvement in marketable yields. By accounting for yield and the BST treatment costs, our profitability analysis showed that the BST treatments did not pay off economically; the net returns of these treatments were statistically equivalent to the untreated controls.