Florida ranks first among US states in fresh-market tomato production with annual production exceeding one-third of the total annual production in the country. Although tomato is a signature crop in Florida, current and future ambient temperatures could impose a major production challenge, especially during the fall growing season. This problem is increasingly becoming an important concern among tomato growers in south Florida, but studies addressing these concerns have not been conducted until now. Therefore, this study was conducted to determine the impacts of the present ambient temperature conditions and planting dates on tomato productivity in south Florida. The study was conducted using crop simulation model CROPGRO-Tomato of DSSAT (Decision Support System for Agricultural Transfer) version 4.7. Five treatments were evaluated, and included AT (simulated treatment using 14 years of actual daily weather conditions at the study location) while other treatments were conducted based on a percentage (−20%, −10%, +10%, +20%) of AT to simulate cooler and warmer temperature regimes. The results suggested that under the current temperature conditions during the fall growing season in south Florida, average tomato yield was up to 29% lower compared to the cooler temperature regimes. Tomato yield further decreased by 52% to 85% at air temperatures above the current condition. Yield reduction under high temperature was primarily due to lower fruit production. Contrary to yield, both tomato biomass accumulation and leaf area index increased with increase in temperature. Results also indicated that due to changes in air temperature pattern, tomato yield increased as planting date increased from July to December. Therefore, planting date modification during the fall season from the current July–September to dates between November and December will reduce the impacts of heat stress and increase tomato productivity in south Florida.

Effective nutrient and irrigation management practices are critical for optimum growth and yield in open-field fresh-market tomato production. Although nutrient and irrigation management practices have been well-studied for tomato production in Florida, more studies of the current highly efficient production systems would be considered essential. Therefore, a two-season (Fall 2016 and Spring 2017) study was conducted in Immokalee, FL, to evaluate the effects of the nitrogen (N) rates under different irrigation regimes and to determine the optimum N requirement for open-field fresh-market tomato production. To evaluate productivity, the study investigated the effects of N rates and irrigation regimes on plant and root growth, yield, and production efficiency of fresh-market tomato. The study demonstrated that deficit irrigation (DI) targeting 66% daily evapotranspiration (ET) replacement significantly increased tomato root growth compared with full irrigation (FI) at 100% ET. Similarly, DI application increased tomato growth early in the season compared with FI. Therefore, irrigation applications may be adjusted downward from FI, especially early during a wet season, thereby potentially improving irrigation water use efficiency (iWUE) and reducing leaching potential of Florida sandy soils. However, total marketable yield significantly increased under FI compared with DI. This suggests that although DI may increase early plant growth, the application of DI throughout the season may result in yield reduction. Although N application rates had no significant effects on biomass production, tomato marketable yield with an application rate of 134 kg·ha ⁻¹ N was significantly lower compared with other N application rates (179, 224, and 269 kg·ha ⁻¹ ). It was also observed that there were no significant yield benefits with N application rates higher than 179 kg·ha ⁻¹ . During the fall, iWUE was higher under DI (33.57 kg·m ⁻³ ) than under FI (25.57 kg·m ⁻³ ); however, iWUE was similar for both irrigation treatments during spring (FI = 14.04 kg·m ⁻³ ; DI = 15.29 kg·m ⁻³ ). The N recovery (REC-N) rate was highest with 134 kg·ha ⁻¹ N; however, REC-N was similar with 179, 224, and 269 kg·ha ⁻¹ N rates during both fall and spring. Therefore, these study results could suggest that DI could be beneficial to tomato production only when applied during early growth stages, but not throughout the growing season. Both yield and efficiency results indicated that the optimum N requirement for open-field fresh-market tomato production in Florida may not exceed 179 kg·ha ⁻¹ N.

High-throughput plant phenotyping (HTPP) involves the application of modern information technologies to evaluate the effects of genetics, environment, and management on the expression of plant traits in plant breeding programs. In recent years, HTPP has been advanced via sensors mounted on terrestrial vehicles and small unoccupied aircraft systems (sUAS) to estimate plant phenotypes in several crops. Previous reviews have summarized these recent advances, but the accuracy of estimation across traits, platforms, crops, and sensors has not been fully established. Therefore, the objectives of this review were to (1) identify the advantages and limitations of terrestrial and sUAS platforms for HTPP, (2) summarize the different imaging techniques and image processing methods used for HTPP, (3) describe individual plant traits that have been quantified using sUAS, (4) summarize the different imaging techniques and image processing methods used for HTPP, and (5) compare the accuracy of estimation among traits, platforms, crops, and sensors. A literature survey was conducted using the Web of Science^TM Core Collection Database (THOMSON REUTERS^TM) to retrieve articles focused on HTPP research. A total of 205 articles were obtained and reviewed using the Google search engine. Based on the information gathered from the literature, in terms of flexibility and ease of operation, sUAS technology is a more practical and cost-effective solution for rapid HTPP at field scale level (>2 ha) compared to terrestrial platforms. Of all the various plant traits or phenotypes, plant growth traits (height, LAI, canopy cover, etc.) were studied most often, while RGB and multispectral sensors were most often deployed aboard sUAS in HTPP research. Sensor performance for estimating crop traits tended to vary according to the chosen platform and crop trait of interest. Regardless of sensor type, the prediction accuracies for crop trait extraction (across multiple crops) were similar for both sUAS and terrestrial platforms; however, yield prediction from sUAS platforms was more accurate compared to terrestrial phenotyping platforms. This review presents a useful guide for researchers in the HTPP community on appropriately matching their traits of interest with the most suitable sensor and platform.

Florida is the largest fresh-market tomato ( Solanum lycopersicum L.)–producing state in the United States. Although vegetable production requires frequent water supply throughout the crop production cycle to produce maximum yield and ensure high-quality produce, overirrigation can reduce crop yield and increase negative environmental consequences. This study was conducted to evaluate and compare irrigation schedules by a real-time and location-specific evapotranspiration (ET)-based SmartIrrigation Vegetable App (SI) with a historic ET-based schedule (HI). A field study was conducted on drip-irrigated, fresh-market tomato during the Fall of 2015 and Spring of 2016 on a Florida sandy soil. The two scheduling methods (SI and HI) were evaluated for irrigation water application, plant biomass accumulation, nutrient uptake and partitioning, and yield in open-field tomato production. Treatments included 100% HI (T1); 66% SI (T2); 100% SI (T3); and 150% SI (T4). Treatments were arranged in a randomized complete block design with four replicates per treatment during the two production seasons. In both seasons, depth of irrigation water applied increased in the order of T2 < T3 < T1 < T4. Total water savings was greater for T3 schedule compared with T1 schedule at 22% and 16% for fall and spring seasons, respectively. No differences were observed among treatments for tomato biomass accumulation at all sampling periods during both seasons. However, T3 resulted in significantly greater total marketable yield compared with other treatments in both seasons. The impact of irrigation application rate was greater in fruit and leaf nitrogen accumulation compared with that of stem and root biomass. Based on the plant performance and water savings, this study concludes that under a sandy soil condition, a real-time location-specific irrigation scheduler improves irrigation scheduling accuracy in relation to actual crop water requirement in open-field tomato production.

Soil nutrients and water management practices according to the concept of 4R nutrient stewardship (right rate, right timing, right placement, and right source) can have significant benefits on crop productivity and reduce the negative effects of agricultural practices on the environment. Therefore, this present study evaluated the effects of nitrogen (N) application timing under different irrigation regimes on open-field, fresh-market tomato production in Florida. In this study, 2 N application timings applied at 25% pre-plant with 75% fertigation (BM), and 0 pre-plant with 100% fertigation (NB), were evaluated. The two N application methods were evaluates using three irrigation regimes: full irrigation (FI, 100% ETc), deficit irrigation (DI, 66% ETc), and regulated deficit irrigation (RDI, 66% ETc during the first 4 weeks after transplanting and 100% ETc afterward). The results showed that BM treatment significantly improved early-season tomato growth compared to NB treatment. The results also indicated that under RDI and DI irrigation conditions, tomato root length was lowest (average value of 13%) within the first 15 cm compared to 40% within 15–30 cm and 47% at 30–40 cm soil depths. Similar to plant growth, BM treatment significantly increased tomato yield (average valued 56.00 Mg ha⁻¹) compared to the NB (average value 40.23 Mg ha⁻¹). The application of DI throughout the growing season reduced tomato yield; however, there were no differences in yield under the RDI and FI irrigation regimes. Therefore, based on the results from this study, it can be concluded that, under Florida growing conditions, pre-plant N application is essential for tomato growth and productivity. Additionally, irrigation application using the RDI method could be successfully adopted in Florida tomato production for improved water savings without any negative effects on tomato growth and productivity.

Core Ideas: SmartIrrigation is a smartphone‐based crop irrigation scheduling method using real‐time and location‐specific (RT‐LS) weather information. The RT‐LS irrigation scheduling method improved irrigation water savings and increased crop yield. The RT‐LS model can reduce nutrient leaching by maintaining water and nutrient within crop root zone. Efficient irrigation scheduling can improve crop performance and increase production efficiencies. Irrigation scheduling based on a real‐time and location‐specific (RT‐LS) model increases irrigation water savings and yield. The RT‐LS irrigation scheduling models have been developed as smartphone applications and have been used for crop‐specific irrigation requirements. Although many RT‐LS irrigation models have been tested and used in several agronomic and horticultural crops in Florida, none of these irrigation‐scheduling models has been tested for their impacts on nutrient distribution in Florida's sandy soils. A two‐season (fall 2015 and spring 2016) study was conducted to determine the effects of an RT‐LS–based irrigation scheduling on soil water, NO ₃ ^‐ –N, and NH ₄ ⁺ –N distributions during a tomato cropping season. In both seasons, an RT‐LS model for tomato was evaluated at three irrigation application rates (66, 100, and 150% RT‐LS–suggested amounts) and compared with a historic evapotranspiration (ET)‐based irrigation schedule (Historic ET) currently recommended in Florida. This study suggests that the RT‐LS model improves water savings by 20 and 17% for the fall and spring seasons, respectively, compared with the Historic ET irrigation scheduling method. No specific pattern was observed for soil NH ₄ ⁺ –N concentration between scheduling methods, but the RT‐LS model maintained a higher soil NO ₃ ^‐ –N concentration within the crop root zone and hence could reduce NO ₃ ^‐ –N leaching potential. In each season, compared with the Historic ET irrigation method, the RT‐LS improved both nitrogen recovery and irrigation water use efficiency in the open‐field fresh‐market tomato production system. Results obtained in this study clearly demonstrate that irrigation applications using the RT‐LS irrigation scheduler improved irrigation scheduling accuracy by maintaining nutrients within the tomato root zone and hence could reduce nutrient leaching potential in sandy soil.