scholarly journals Risk Assessment of Soil Salinization Due to Tomato Cultivation in Mediterranean Climate Conditions

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1503 ◽  
Author(s):  
Angela Libutti ◽  
Anna Cammerino ◽  
Massimo Monteleone

The Mediterranean climate is marked by arid climate conditions in summer; therefore, crop irrigation is crucial to sustain plant growth and productivity in this season. If groundwater is utilized for irrigation, an impressive water pumping system is needed to satisfy crop water requirements at catchment scale. Consequently, irrigation water quality gets worse, specifically considering groundwater salinization near the coastal areas due to seawater intrusion, as well as triggering soil salinization. With reference to an agricultural coastal area in the Mediterranean basin (southern Italy), close to the Adriatic Sea, an assessment of soil salinization risk due to processing tomato cultivation was carried out. A simulation model was first arranged, then validated, and finally applied to perform a water and salt balance along a representative soil profile on a daily basis. In this regard, long-term weather data and physical soil characteristics of the considered area (both taken from international databases) were utilized in applying the model, as well as considering three salinity levels of irrigation water. Based on the climatic analysis performed and the model outputs, the probability of soil salinity came out very high, such as to seriously threaten tomato yield. Autumn–winter rainfall frequently proved to be insufficient to leach excess salts away from the soil profile and reach sustainable conditions of tomato cultivation. Therefore, alternative cropping strategies were investigated.

Author(s):  
Angela Libutti ◽  
Anna Rita Bernadette Cammerino ◽  
Massimo Monteleone

Mediterranean climate is marked by arid climate conditions in summer, therefore, crop irrigation is crucial to sustain plant growth and productivity in this season. If groundwater is utilized for irrigation, an impressive water pumping is needed to satisfy crop water requirements at catchment scale. Consequently, irrigation water quality gets worse, specifically considering groundwater salinization near the coastal areas due to seawater intrusion, also triggering soil salinization. With reference to an agricultural coastal area in the Mediterranean basin (Southern Italy), close to the Adriatic sea, an assessment of soil salinization risk due to processing tomato cultivation was carried out. A simulation model was arranged to perform, on daily basis, a water and salt balance along the soil profile. Long-term weather data and soil physical parameters representative of the considered area were utilized in applying the model, also considering three salinity levels of irrigation water. Based on the climatic analysis performed and the model outputs, the probability of soil salinity came out very high, such as to seriously threaten tomato yield. Autumn-winter rainfall resulted frequently insufficient to leach excess salts away from the soil profile and reach sustainable conditions of tomato cultivation. Therefore, alternative cropping strategies were prospected.


Botany ◽  
2018 ◽  
Vol 96 (9) ◽  
pp. 589-599 ◽  
Author(s):  
Lubia M. Guedes ◽  
Narciso Aguilera ◽  
Bruno G. Ferreira ◽  
José Becerra ◽  
Katia Sáez ◽  
...  

Environment, plant, and gall-inducing insect genotypes are key factors in determining the morphogenesis of galls. However, the exact roles of these factors have not been clarified. We used anatomical and histochemical methods to evaluate the determining factors in the final structure of galls induced by Calophya mammifex on leaves of Schinus polygama (Cav.) Cabrera under the Mediterranean climate conditions of southern Chile. Also, we compared mature galls with those induced by the congeneric Calophya rubra on the same host plant. Calophya mammifex develops a univoltine life cycle and a diapause period in the Mediterranean climate conditions of southern Chile. Morphogenetic and histochemical leaf patterns were altered by C. mammifex feeding activity. For the first time, two specialized tissue compartments, a nutritive-like tissue and a common storage tissue, are reported for Calophyidae-induced galls in the Mediterranean region of southern Chile. Galls induced by C. mammifex and C. rubra have sufficient anatomical and histochemical alterations to be diagnosed as complex structures, whose distinction in vascular system differentiation implies structural constraints imposed by host plant organs.


2021 ◽  
Vol 12 ◽  
Author(s):  
Rui Liu ◽  
Peng-Fei Zhu ◽  
Yao-Sheng Wang ◽  
Zhen Chen ◽  
Ji-Rong Zhu ◽  
...  

The efficient utilization of irrigation water and nitrogen is of great importance for sustainable agricultural production. Alternate partial root-zone drip irrigation (APRD) is an innovative water-saving drip irrigation technology. However, the coupling effects of water and nitrogen (N) supply under APRD on crop growth, water and N use efficiency, as well as the utilization and fate of residual nitrates accumulated in the soil profile are not clear. A simulated soil column experiment where 30–40 cm soil layer was 15NO3-labeled as residual nitrate was conducted to investigate the coupling effects of different water [sufficient irrigation (W1), two-thirds of the W1(W2)] and N [high level (N1), 50% of N1 (N2)] supplies under different irrigation modes [conventional irrigation (C), APRD (A)] on tomato growth, irrigation water (IWUE) and N use efficiencies (NUE), and the fate of residual N. The results showed that, compared with CW1N1, AW1N1 promoted root growth and nitrogen absorption, and increased tomato yield, while the N absorption and yield did not vary significantly in AW2N1. The N absorption in AW2N2 decreased by 16.1%, while the tomato yield decreased by only 8.8% compared with CW1N1. The highest IWUE appeared in AW2N1, whereas the highest NUE was observed in AW2N2, with no significant difference in NUE between AW2N1 and CW1N1 at the same N supply level. The 15N accumulation peak layer was almost the same as the originally labeled layer under APRD, whereas it moved 10–20 cm downwards under CW1N1. The amount of 15N accumulated in the 0-40 cm layer increased with the decreasing irrigation water and nitrogen supply, with an increase of 82.9–141.1% in APRD compared with that in CW1N1. The utilization of the 15N labeled soil profile by the tomato plants increased by 9–20.5%, whereas the loss rate of 15N from the plant-soil column system decreased by 21.3–50.1% in APRD compared with the CW1N1 treatment. Thus, APRD has great potential in saving irrigation water, facilitating water use while reducing the loss of residual nitrate accumulated in the soil profile, but has no significant effect on the NUE absorbed.


2017 ◽  
Vol 234-235 ◽  
pp. 182-195 ◽  
Author(s):  
Daniel. D.M. Bassimba ◽  
Diego S. Intrigliolo ◽  
Anna Dalla Marta ◽  
Simone Orlandini ◽  
Antonio Vicent

Author(s):  
Rumiana Kireva ◽  
Roumen Gadjev

The deficit of the irrigation water requires irrigation technologies with more efficient water use. For cucumbers, the most suitable is the drip irrigation technology. For establishing of the appropriate irrigation schedule of cucumbers under the soil and climate conditions in the village of Chelopechene, near Sofia city, the researchеs was conducted with drip irrigation technology, adopting varying irrigation schedules and hydraulic regimes - from fully meeting the daily crops water requirements cucumbers to reduced depths with 20% and 40%. It have been established irrigation schedule with adequate pressure flows in the water source, irrigation water productivity and yields of in plastic unheated greenhouses of the Sofia plant.


Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3313
Author(s):  
Juan Luis Aguirre ◽  
María Teresa Martín ◽  
Sergio González ◽  
Manuel Peinado

The effects of two types of biochar on corn production in the Mediterranean climate during the growing season were analyzed. The two types of biochar were obtained from pyrolysis of Pinus pinaster. B1 was fully pyrolyzed with 55.90% organic carbon, and B2 was medium pyrolyzed with 23.50% organic carbon. B1 and B2 were supplemented in the soil of 20 plots (1 m2) at a dose of 4 kg/m2. C1 and C2 (10 plots each) served as control plots. The plots were automatically irrigated and fertilizer was not applied. The B1-supplemented plots exhibited a significant 84.58% increase in dry corn production per square meter and a 93.16% increase in corn wet weight (p << 0.001). Corn production was no different between B2-supplemented, C1, and C2 plots (p > 0.01). The weight of cobs from B1-supplemented plots was 62.3%, which was significantly higher than that of cobs from C1 and C2 plots (p < 0.01). The grain weight increased significantly by 23% in B1-supplemented plots (p < 0.01) and there were no differences between B2-supplemented, C1, and C2 plots. At the end of the treatment, the soil of the B1-supplemented plots exhibited increased levels of sulfate, nitrate, magnesium, conductivity, and saturation percentage. Based on these results, the economic sustainability of this application in agriculture was studied at a standard price of €190 per ton of biochar. Amortization of this investment can be achieved in 5.52 years according to this cost. Considering the fertilizer cost savings of 50% and the water cost savings of 25%, the amortization can be achieved in 4.15 years. If the price of biochar could be reduced through the CO2 emission market at €30 per ton of non-emitted CO2, the amortization can be achieved in 2.80 years. Biochar markedly improves corn production in the Mediterranean climate. However, the amortization time must be further reduced, and enhanced production must be guaranteed over the years with long term field trials so that the product is marketable or other high value-added crops must be identified.


Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1207
Author(s):  
Gonçalo C. Rodrigues ◽  
Ricardo P. Braga

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 unavailable.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3030
Author(s):  
Simon Liebermann ◽  
Jung-Sup Um ◽  
YoungSeok Hwang ◽  
Stephan Schlüter

Due to the globally increasing share of renewable energy sources like wind and solar power, precise forecasts for weather data are becoming more and more important. To compute such forecasts numerous authors apply neural networks (NN), whereby models became ever more complex recently. Using solar irradiation as an example, we verify if this additional complexity is required in terms of forecasting precision. Different NN models, namely the long-short term (LSTM) neural network, a convolutional neural network (CNN), and combinations of both are benchmarked against each other. The naive forecast is included as a baseline. Various locations across Europe are tested to analyze the models’ performance under different climate conditions. Forecasts up to 24 h in advance are generated and compared using different goodness of fit (GoF) measures. Besides, errors are analyzed in the time domain. As expected, the error of all models increases with rising forecasting horizon. Over all test stations it shows that combining an LSTM network with a CNN yields the best performance. However, regarding the chosen GoF measures, differences to the alternative approaches are fairly small. The hybrid model’s advantage lies not in the improved GoF but in its versatility: contrary to an LSTM or a CNN, it produces good results under all tested weather conditions.


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