Behaviour of relative evapotranspiration with agrometeorological stress indices in wheat

Complex behaviour of stress indices with relative evapotranspiration was observed in early and late sown wheat, however, under normal sown conditions it was linearly decreasing. Predawn leaf water potential and transpiration rate proved to be a stable stress index parameter for characterizing the internal moisture status in the plant as compared to the canopy temperature and stomatal resistance under stress conditions in wheat. Since it is easy to quantify canopy/leaf temperature and within seasonal variations it is widely used for scheduling irrigation and quantigying moisture stress effects on growth and development in wheat.

Assessing the Maize (Zea mays L.) Crop Performance Using Spectral Indices under Different Sowing Dates and Irrigations Schedules

Field experiment was conducted at ARI, PJTSAU, Hyderabad with four dates of sowing (18th June, 04th July, 19th July and 03rd August in Kharif, 2016 and 01st November, 18th November, 01st December and 17th December in rabi, 2016–17) as main plots and four irrigations regimes (Control, 0.4 IW/CPE, 0.6 IW/CPE and 0.8 IW/CPE in kharif and 0.4 IW/CPE, 0.6 IW/CPE, 0.8 IW/CPE and 1.0 IW/CPE in rabi) as sub-plots in split plot design replicated thrice. Scheduling irrigation at unstressed conditions, 0.8 IW/CPE (I3) and 1.0 IW/CPE (I4) of maize resulted in low reflectance in visible region (400 to 700 nm) and mid infrared (MIR) region (1350–2500 nm) and high in near infrared (NIR) region (700 to 1350 nm) during kharif and rabi respectively. While, under stressed condition, the reflectance was high in visible and MIR region and low in NIR region in rainfed and 0.4 IW/CPE (I0) respectively in kharif and rabi. Significantly higher drymatter, LAI and grain yield was observed in 04th July (D2) and 01st November (D1) sown crop in kharif and rabi respectively. However, spectral indices (SR, PRI, NDWI at 1240, 1640 and 2130 nm, NDII, NMDI, WBI and SWRI) was attained by 18th June (D1) and 01st November (D1) during kharif and rabi respectively. Higher drymatter, LAI, grain yield and spectral indices was recorded with I3 (0.8 IW/CPE) and I4 (1.0 IW/CPE) in kharif and rabi respectively. All the spectral vegetation indices correlated positively with LAI, drymatter and grain yield.

Avocado cv. Hass Needs Water Irrigation in Tropical Precipitation Regime: Evidence from Colombia

The primary natural source of water for the Hass avocado crop in the tropics is precipitation. However, this is insufficient to provide most crops’ water requirements due to the spatial and temporal variability. This study aims to demonstrate that Hass avocado requires irrigation in Colombia, and this is done by analyzing the dynamics of local precipitation regimes and the influence of Intertropical Convergence Zone phenomena (ITCZ) on the irrigation requirement (IR). This study was carried out in Colombia’s current and potential Hass avocado production zones (PPA) by computing and mapping the monthly IR, and classifying months found to be in deficit and excess. The influence of ITCZ on IR by performing a metric relevance analysis on weights of optimized Artificial Neural Networks was computed. The water deficit map illustrates a 99.8% of PPA requires water irrigation at least one month a year. The movement of ITCZ toward latitudes far to those where PPA is located between May to September decreases precipitation and consequently increases the IR area of Hass avocado. Water deficit visualization maps could become a novel and powerful tool for Colombian farmers when scheduling irrigation in those months and periods identified in these maps.

The Effects of Flood, Drought, and Flood Followed by Drought on Yield in Cotton

Cotton suffers from alternations of flood and drought in China. A lysimeter trial was conducted to investigate the responses of various cotton yield indices under water-stress treatments including, flood (five-day, eight-day), drought (10-day, 15-day), and five-day flood followed by 10-day drought, during the flowering and boll-forming stage. The results showed that the seed cotton yield was significantly (p < 0.05) reduced under all water-stress treatments, while the harvest index was not affected under any treatment. Significant decreases in dry matter yield, boll number, and boll hull mass were detected under flood treatments but not under drought treatments. The percentage cotton yield losses per day induced by flood and drought were 6.22% and 2.48%, respectively. Under water stress, the associations between seed cotton yield and relevant yield indices were weakened, but yield losses were still strongly related to the decreases in dry matter yield and boll number. Flood followed by drought caused significant reductions in all yield indices except harvest index; however, the reduction was much lower than the additive reductions induced by flood and drought. These results provide bases for scheduling irrigation and drainage under climate change.

Remote Sensing of Evapotranspiration Using SEBAL and Metric Energy Balance Models for Enhanced Precision Agriculture Cotton Irrigation Scheduling

&lt;p&gt;Irrigation scheduling is one of the main factors that affect the crop ability to resist stress symptoms in addition to affecting directly the final yield. In the last decade, many remote sensing methods have been developed to help in scheduling irrigation with higher precision. Some of these methods estimate irrigation needs indirectly such as those using normalized difference vegetation index (NDVI) or crop coefficient curve, and other methods that directly calculate Evapotranspiration (ET) through satellite images. Cotton SmartIrrigation App (Cotton App) is one of the recent applications that have been developed to help farmers in scheduling irrigation during the growing season. The App is based on an interactive ET-based soil water balance model. In this study, remote sensing of Evapotranspiration has been used to detect and map crop water requirements in order to enhance the Cotton App predictions for irrigation schedule during the growing season. Two remote sensing ET models based on thermal infrared (TIR), The surface energy balance algorithm for land (SEBAL) and Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), were used to derive ET over cotton. Results showed higher values of actual Evapotranspiration calculated by both SEBAL and METRIC models during the first 45 days of the growing season compared to the calculated values of ETa from crop coefficient. This is expected to be due to the higher evaporation fraction from bare soil since the plant cover is still very low and accordingly the plant transpiration too. However, later in the second growing stage, the models showed that the crop coefficient calculated ETa (ETa- Calculated) has overestimated the plant Evapotranspiration giving higher values compared to the values from the models. These results indicate that, the use of remote sensing techniques along with the ET-models will increase the app efficiency in giving more precise irrigation scheduling.&lt;/p&gt;