Predicting Soil Water Content on Rainfed Maize through Aerial Thermal Imaging

Restrictions on soil water supply can dramatically reduce crop yields by affecting the growth and development of plants. For this reason, screening tools that can detect crop water stress early have been long investigated, with canopy temperature (CT) being widely used for this purpose. In this study, we investigated the relationship between canopy temperature retrieved from unmanned aerial vehicles (UAV) based thermal imagery with soil and plant attributes, using a rainfed maize field as the area of study. The flight mission was conducted during the late vegetative stage and at solar noon, when a considerable soil water deficit was detected according to the soil water balance model used. While the images were being taken, soil sampling was conducted to determine the soil water content across the field. The sampling results demonstrated the spatial variability of soil water status, with soil volumetric water content (SVWC) presenting 10.4% of variation and values close to the permanent wilting point (PWP), reflecting CT readings that ranged from 32.8 to 40.6 °C among the sampling locations. Although CT correlated well with many of the physical attributes of soil that are related to water dynamics, the simple linear regression between CT and soil water content variables yielded coefficients of determination (R2) = 0.42, indicating that CT alone might not be sufficient to predict soil water status. Nonetheless, when CT was combined with some soil physical attributes in a multiple linear regression, the prediction capacity was significantly increased, achieving an R2 value = 0.88. This result indicates the potential use of CT along with certain soil physical variables to predict crop water status, making it a useful tool for studies exploring the spatial variability of in-season drought stress.

Optimisation of fertigation scheduling based on indicators of soil water status in melon growing in semi-arid areas

<p>In water scarcity areas, it is necessary not only reducing the water applied as much as possible, but also optimizing nutrients application to avoid soil salinization and aquifers pollution because of leaching bellow the root zone. Increasing the sustainability of fertirrigation needs technology to adjust the irrigation time, knowing more precisely the soil water retention capacity and facilitate water absorption by the crop. The aim of this trial was to establish protocols for sustainable fertirrigation in melon crop under semi-arid conditions, both at an environmental and economic level, based on the use of soil water status indicators measured by sensors that allow us to increase the irrigation water use efficiency. Two irrigation treatments were established: i) Control (CTL), irrigated to satisfy the water requirements of the crop, according to the farmer's criterion throughout the crop cycle and ii) DI, deficit irrigation, irrigated to allow a maximum soil water depletion of 20%, with respect to field capacity throughout the crop cycle, from sensors located below the 20 cm depth horizon, in order to limit water leaching into the soil. An experimental design was established with 4 repetitions per treatment distributed at random, with 5 plants per repetition. Macro and micronutrients concentration of soil solution, leaves and fruits were analysed. The crop water status was determined fortnightly by measurements taken at solar midday of stem water potential, net photosynthesis, evapotranspiration rate and leaf conductance. Whereas photosynthetically active radiation absorption, basal stem and fruit equatorial diameters were determined to estimate plant and fruit growth. The physical (longitudinal and equatorial fruit diameters, fruit weight, pulp width and firmness) and chemical (titratable acidity, pH and total soluble solid of the juice, total phenolic content, total antioxidant capacity and total ascorbic acid) characteristics of harvested fruits were determined. Total water applied in CTL treatment was 3,254 m<sup>3</sup> ha<sup>-1</sup> throughout the crop cycle whereas DI received 2,284 m<sup>3</sup> ha<sup>-1</sup>, a 29.8% lower. In both cases, the volume of water applied was lower than recommended by FAO. The regulation of the irrigation time in the DI treatment respect to the CTL promoted a reduction of the soil water content from 30 cm depth, mitigating the water loss below the root system, along with a lower contribution of nutrients, around of 43, 41.8 and 22% of N, P and K, respectively, and less salinization of the soil profile. No significant difference between treatments was detected in the concentration of these nutrients at leaf level. No difference was observed at harvest, with 0.53 and 0.59 g fruit g<sup>-1</sup> total dry mass of harvest index in CTL and DI, respectively. Fruit quality was not negatively affected in DI but improved since ascorbic acid was higher. This means that DI treatment not only did not negatively affect the crop water status and the amount and quality of the yield, but also improved its biochemical quality while reducing water and nutrients use and leaching.</p>

Assessing canopy temperature-based water stress indices for soybeans under subhumid conditions

<p>Sustainable irrigation water management is expected to accurately meet crop water requirements in order to avoid stress and, consequently, yield reduction, and at the same time avoid losses of water and nutrients due to deep percolation and leaching. Sensors to monitor soil water status and plant water status (in terms of canopy temperature) can help planning irrigation with respect to time and amounts accordingly. The presented study aimed at quantifying and comparing crop water stress of soybeans irrigated by means of different irrigation systems under subhumid conditions.</p><p>The study site was located in Obersiebenbrunn, Lower Austria, about 30 km east of Vienna. The region is characterized by a mean temperature of 10.5°C with increasing trend due to climate change and mean annual precipitation of 550 mm. The investigations covered the vegetation period of soybean in 2018, from planting in April to harvest in September. Measurement data included precipitation, air temperature, relative humidity and wind velocity. The experimental field of 120x120 m<sup>2</sup> has been divided into four sub-areas: a plot of 14x120 m<sup>2</sup> with drip irrigation (DI), 14x120 m<sup>2</sup> without irrigation (NI), 36x120 m<sup>2</sup> with sprinkler irrigation (SI), and 56x120 m<sup>2</sup> irrigated with a hose reel boom with nozzles (BI). A total of 128, 187 and 114 mm of water were applied in three irrigation events in the plots DI, SI and BI, respectively. Soil water content was monitored in 10 cm depth (HydraProbe, Stevens Water) and matric potential was monitored in 20, 40 and 60 cm depth (Watermark, Irrometer). Canopy temperature was measured every 15 minutes using infrared thermometers (IRT; SI-411, Apogee Instruments). The IRTs were installed with an inclination of 45° at 1.8 m height above ground. Canopy temperature-based water stress indices for irrigation scheduling have been successfully applied in arid environments, but their use is limited in humid areas due to low vapor pressure deficit (VPD). To quantify stress in our study, the Crop Water Stress Index (CWSI) was calculated for each plot and compared to the index resulting from the Degrees Above Canopy Threshold (DACT) method. Unlike the CWSI, the DACT method does not consider VPD to provide a stress index nor requires clear sky conditions. The purpose of the comparison was to revise an alternative method to the CWSI that can be applied in a humid environment.</p><p>CWSI behaved similar for the four sub-areas. As expected, CWSI ≥ 1 during dry periods (representing severe stress) and it decreased considerably after precipitation or irrigation (representing no stress). The plot with overall lower stress was BI, producing the highest yield of the four plots. Results show that DACT may be a more suitable index since all it requires is canopy temperature values and has strong relationship with soil water measurements. Nevertheless, attention must be paid when defining canopy temperature thresholds. Further investigations include the development and test of a decision support system for irrigation scheduling combining both, plant-based and soil water status indicators for water use efficiency analysis.</p>

Irrigation Scheduling for Agriculture in the United States: The Progress Made and the Path Forward

HighlightsThe progress made in agricultural irrigation scheduling in the past ten years and the current challenges are discussed.The main scientific scheduling strategies are based on soil water status, plant characteristics, and crop modeling.Challenges include large time and data requirements and availability of decision support systems.Opportunities include integration of scheduling strategies and demonstrating their effectiveness through local studies.Abstract. Irrigation scheduling is the process of determining the appropriate amount and timing of water application to achieve desired crop yield and quality, maximize water conservation, and minimize possible negative effects on the environment, such as nutrient leaching below the crop root zone. Effective irrigation scheduling has been shown to save water, save energy, and help agricultural producers achieve improved yields and quality. However, scientific irrigation scheduling methods generally have remained limited to mostly research applications with relatively low adoption by irrigators. There are several main approaches to irrigation scheduling, including those based on soil water status, plant characteristics, and/or crop modeling. Each of these approaches has advantages as well as limitations and sources of uncertainty and variability, depending on application conditions. This article summarizes progress made in the U.S. in each of the main scheduling approaches in the past ten years (since the 2010 Decennial Irrigation Symposium) and existing challenges and opportunities that should be considered moving forward. This article is intended to guide future research and extension projects in improving adoption of scientific irrigation scheduling approaches. Keywords: Computer modeling, Plant characteristics, Soil water status.