Precision Agriculture: Strategies and Technology Adoption

This article belongs to the Special Issue Precision Agriculture Adoption StrategiesThe purpose of this Special Issue was to publish high-quality research and review papers that cover the definition of strategies that may promote the adoption of PA, assessing the adoption rates, bottlenecks for adoption, adoption promotion, strategic plans, and incentives. The Special Issue covers nine peer-reviewed research papers and one systematic review paperinfo:eu-repo/semantics/publishedVersio

Estimation of daily reference evapotranspiration from NASA POWER reanalysis products in a hot summer Mediterranean climate

This study aims at assessing the accuracy of estimating daily reference evapotranspiration (ETo) computed with NASA POWER reanalysis products. Daily ETo estimated from local observations of weather variables in 14 weather stations distributed across Alentejo Region, Southern Portugal were compared with ETo derived from NASA POWER weather data, using raw and biascorrected datasets. Three different methods were used to compute ETo: (a) FAO Penman-Monteith (PM); (b) Hargreaves-Samani (HS); and (c) MaxTET. Results show that, when using raw NASA POWER datasets, a good accuracy between the observed ETo and reanalysis ETo was observed in most locations (R2 > 0.70). PM shows a tendency to over-estimating ETo with an RMSE as high as 1.41 mm d-1, while using a temperature-based ET estimation method, an RMSE lower than 0.92 mm d-1 is obtained. If a local bias correction is adopted, the temperature-based methods show a small over or underestimation of ETo (–0.40 mm d-1 MBE < 0.40 mm d-1). As for PM, ETo is still underestimated for 13 locations (MBE < 0 mm d-1) but with an RMSE never higher than 0.77 mm d-1. When NASA POWER raw data is used to estimate ETo, HS_Rs proved the most accurate method, providing the lowest RMSE for half the locations. However, if a data regional bias correction is used, PM leads to the most accurate ETo estimation for half the locations; also, when a local bias correction is performed, PM proved the be the most accurate ETo estimation method for most locations. Nonetheless, MaxTET proved to be an accurate method; its simplicity may prove to be successful not only when only maximum temperature data is available but also due to the low data required for ETo estimationinfo:eu-repo/semantics/publishedVersio

Evaluation of NASA POWER reanalysis products to estimate daily weather variables in a hot summer Mediterranean climate

This study aims to evaluate NASA POWER reanalysis products for daily surface maximum (Tmax) and minimum (Tmin) temperatures, solar radiation (Rs), relative humidity (RH) and wind speed (Ws) when compared with observed data from 14 distributed weather stations across Alentejo Region, Southern Portugal, with a hot summer Mediterranean climate. Results showed that there is good agreement between NASA POWER reanalysis and observed data for all parameters, except for wind speed, with coefficient of determination (R2) higher than 0.82, with normalized root mean square error (NRMSE) varying, from 8 to 20%, and a normalized mean bias error (NMBE) ranging from –9 to 26%, for those variables. Based on these results, and in order to improve the accuracy of the NASA POWER dataset, two bias corrections were performed to all weather variables: one for the Alentejo Region as a whole; another, for each location individually. Results improved significantly, especially when a local bias correction is performed, with Tmax and Tmin presenting an improvement of the mean NRMSE of 6.6 C (from 8.0 C) and 16.1 C (from 20.5 C), respectively, while a mean NMBE decreased from 10.65 to 0.2%. Rs results also show a very high goodness of fit with a mean NRMSE of 11.2% and mean NMBE equal to 0.1%. Additionally, bias corrected RH data performed acceptably with an NRMSE lower than 12.1% and an NMBE below 2.1%. However, even when a bias correction is performed, Ws lacks the performance showed by the remaining weather variables, with an NRMSE never lower than 19.6%. Results show that NASA POWER can be useful for the generation of weather data sets where ground weather stations data is of missing or unavailableinfo:eu-repo/semantics/publishedVersio

Estimation of Reference Evapotranspiration during the Irrigation Season Using Nine Temperature-Based Methods in a Hot-Summer Mediterranean Climate

The FAO-56 Penman–Monteith (PM) equation is regarded as the most accurate equation to estimate reference evapotranspiration (ETo). However, it requires a broad range of data that may not be available or of reasonable quality. In this study, nine temperature-based methods were assessed for ETo estimation during the irrigation at fourteen locations distributed through a hot-summer Mediterranean climate region of Alentejo, Southern Portugal. Additionally, for each location, the Hargreaves–Samani radiation adjustment coefficient (kRs) was calibrated and validated to evaluate the appropriateness of using the standard value, creating a locally adjusted Hargreaves–Samani (HS) equation. The accuracy of each method was evaluated by statistically comparing their results with those obtained by PM. Results show that the calibration of the kRs, a locally adjusted HS method can be used to estimate daily ETo acceptably well, with RMSE lower than 0.88 mm day−1, an estimation error lower than 4% and a R2 higher than 0.69, proving to be the most accurate model for 8 (out of 14) locations. A modified Hargreaves–Samani method also performed acceptably for 4 locations, with a RMSE of 0.72–0.84 mm day−1, a slope varying from 0.95 to 1.01 and a R2 higher than 0.78. One can conclude that, when weather data is missing, a calibrated HS equation is adequate to estimate ETo during the irrigation seasoninfo:eu-repo/semantics/publishedVersio

A Simple Application for Computing Reference Evapotranspiration with Various Levels of Data Availability—ETo Tool

Reference evapotranspiration (ETo) estimations may be used to improve the efficiency of irrigated agriculture. However, its computation can be complex and could require numerous weather data that are not always available for many locations. Different methods are available to estimate ETo when limited data are available, and the assessment of the most accurate one can be difficult and time consuming. There are some standalone softwares available for computing ETo but none of them allow for the comparison of different methods for the same or different datasets simultaneously. This paper aims to present an application for estimating ETo using several methods that require different levels of data availability, namely FAO-56 Penman–Monteith (PM), the Original and the three modified Hargreaves–Samani (HS and MHS1, MHS2 and MHS3), Trajkovic (TR) and the single temperature procedure (MaxTET). Also, it facilitates the comparison of the accuracy estimation of two selected methods. From an example case, for where the application was used to compute ETo for three different locations, results show that the application can easily and successfully estimate ETo using the proposed methods, allowing for statistical comparison of those estimations. HS proves to be the most accurate method for the studied locations; however, the accuracy of all methods tends to be lower for costal locations than for more continental sites. With this application, users can select the best ETo estimation methods for a specific location and use it for irrigation purposesinfo:eu-repo/semantics/publishedVersio

Determining farmers' willingness to pay for irrigation water in the Alentejo region (Southern Portugal) by residual value method

This paper aims to determine farmers’ willingness to pay for irrigation water, using the residual value method, for the most representative crops at six Irrigation Communities from the Alentejo region, southern Portugal. The main objective of this assessment was to determine the value that farmers would be able to pay for the water to irrigate different crops at different locations, and to show that this approach can be used to provide information about farming economic sustainability and provide support on if crop prices need to be revised or if a national policy should be conceived to cover for farming costs. The results show that vegetables and fruit trees have the highest Residual Value ofWater (RVW), while Wheat, Sunflower, Fodder crops, Semi-intensive Olive Orchards and Rice tend to have an RVW lower than the current variable irrigation water price. The results also show that, while, for Melon, Tomato, Onion, Super-high-density Olive Orchards, Peach and Almonds, both yields and price may decrease significantly, allowing one to save for faming inputs, Sunflower and Rice would require an increase in yields or prices to cover for the irrigation water priceinfo:eu-repo/semantics/publishedVersio

Phosphorous nanofertilizers for Precise application in rice cultivation as an adaptation to climate change

Rice is the staple food of more than half of the world’s population, which is still growing. The great dependence that agriculture, and rice specially, has on fertilizers alongside extreme events that result from climatic change creates an urge for adaptation. Fertilizers are expensive, finite and a potential environmental problem. Their precise application, by the use of slow-release nanofertilizers, thus avoiding losses and consequently reducing the pressure on water resources, is one step forward in this adaptation. It can reduce costs and protect the environment while ensuring food production. Phosphorous is very important for rice, since it is involved in its flowering and root development, and its low availability to the plants constitutes a serious problem. The delivery of phosphorous through the crop cycle in the form of slow-release phosphorus nanofertilizer (Pnf) instead of the conventional annual bulk application reduces the amount of nutrients applied and increases the absorption by the crop. Combining the fertilizing effect with the use of natural stimulant compounds such as chitosan can protect the crop from diseases and increase its resilience to stress. The use of Pnf reduces the pressure on water resources and avoids imbalances in soil nutrients, thus responding to climatic change challenges and abiotic stresses.info:eu-repo/semantics/publishedVersio

Effect of Aging on the Lower Limb Kinematics in Karate Practitioners: Comparing Athletes and Their Senseis

With the life expectancy increasing, older adult population has gained the attention of many researchers. Aging is known to lead to a general decline in bodily functions, which affect the quality of life. The aim of this study was to analyze how the aging process affects veteran active karate practitioners, in the kinematic and temporal structure of the frontal kick. Nine black belt karate practitioners over 50 years old and 24 black belt karate practitioners, aged between 20 and 30 years old, all male, performed the frontal kick mae-geri. Results showed that knee is the structure that holds most differences between young and veterans, both for linear and for angular variables during the mae-geri performance. Statistical differences were found in linear velocity for the knee; linear acceleration of the knee, hip, and RASIS; maximum angular velocity for knee and hip; maximum angular acceleration for ankle and hip; and in the range of motion of knee. The temporal variables show differences, between groups, in maximum linear velocity, maximum linear acceleration, and maximum angular acceleration. However, no differences were found between groups for the time before contact in the maximum linear and angular acceleration, which allow us to remark both the effects of the aging process and the effect of training. This study corroborates the ability of older people to achieve benefits from sports practice, achieving higher efficiency than the younger adults in task execution, but using different motor control strategies.info:eu-repo/semantics/publishedVersio

Athletes and their Sensei’s: did aging affect the lower limb kinematics in karate practitioners

[EN] Aging leads to a general decline in body functions that affects quality of life

Modelling economic impacts of deficit irrigated maize in Brazil with consideration of different rainfall regimes

Deficit irrigation is often required to cope with droughts and limited water availability. However, to select an appropriate irrigation management, it is necessary to assess when economic impacts of deficit irrigation are acceptable. Thus, the main goal of this study was to evaluate economic water productivity for maize submitted to various levels of water deficits and different irrigation systems. The study was based on two different experiments conducted in Southern Brazil, one using sprinkler irrigation to supplement rainfall and the other using drip irrigation with precipitation excluded by a rainfall shelter to simulate cultivation under dry conditions. Water productivity indicators were calculated referring to: a) actual field collected data, including yields, commodity prices and production costs; and b) a sensitivity analysis to commodity prices and production costs. Alternative centrepivot irrigation scenarios were also developed to assess their feasibility in terms of water use and productivity when irrigation is used to supplement rainfall or when rainfall is scarce. Results show that the feasibility of deficit irrigation is highly influenced by commodity prices and by the irrigation (and water) costs when the irrigation costs are a large part of the production costs. Results also show that deficit irrigation applied when rainfall is abundant is easier to implement than deficit irrigation where rainfall is very scarce, when only a mild stress is economically viable. For well-designed and managed centrepivot systems, results confirm that adopting deficit irrigation when rainfall is scarce is less attractive than under conditions of irrigation to supplement rainfall. It could be concluded that farmers are unlikely to choose a deficit irrigation strategy unless they are facing reduced water availability for irrigatio