{"title":"Trend analysis of precipitation data in Turkey and relations to atmospheric circulation: (1955-2013)","authors":"Muhammet Topuz, M. Karabulut, H. Feidas","doi":"10.13128/IJAM-887","DOIUrl":"https://doi.org/10.13128/IJAM-887","url":null,"abstract":"","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"8 1","pages":"91-107"},"PeriodicalIF":1.2,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73944909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simone Falzoi, F. Acquaotta, M. Pulina, S. Fratianni
A 37 year (1981-2017) study of the hydrological drought trend was conducted in two Italian regions, Piedmont and Sardinia, with different climatic features (Temperate Continental climate and Mediterranean climate, respectively). For this purpose, we have examined the daily data of 13 meteorological stations uniformly installed in the two areas, and the trends of the Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI) have been also evaluated. The similarities and differences between the indices of the two regions were then considered. In most stations of both zones, there is a statistically significant trend of increase in the SPI and decrease in the SPEI. Nevertheless, the trend of indices averaged over stations of the two indices is not significant in either of the two climatic zones considered.
{"title":"Hydrological drought analysis in Continental Temperate and Mediterranean environment during the period 1981-2017","authors":"Simone Falzoi, F. Acquaotta, M. Pulina, S. Fratianni","doi":"10.13128/IJAM-798","DOIUrl":"https://doi.org/10.13128/IJAM-798","url":null,"abstract":"A 37 year (1981-2017) study of the hydrological drought trend was conducted in two Italian regions, Piedmont and Sardinia, with different climatic features (Temperate Continental climate and Mediterranean climate, respectively). For this purpose, we have examined the daily data of 13 meteorological stations uniformly installed in the two areas, and the trends of the Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI) have been also evaluated. The similarities and differences between the indices of the two regions were then considered. In most stations of both zones, there is a statistically significant trend of increase in the SPI and decrease in the SPEI. Nevertheless, the trend of indices averaged over stations of the two indices is not significant in either of the two climatic zones considered.","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"68 1","pages":"13-23"},"PeriodicalIF":1.2,"publicationDate":"2019-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86091749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Şaylan, R. Kimura, Nilcan Altınbaş, B. Çaldağ, F. Bakanoğullari
Performances of an Artificial Neural Network (ANN), a multiple linear regression (MLR) and the Jarvis type model were compared to estimate the surface conductance of the sunn hemp crop, which is a driving factor affecting evapotranspiration. It was modeled by ANN and MLR using various parameters including global solar radiation, temperature, soil water content, relative humidity, precipitation and irrigation, vapor pressure deficit, wind speed and leaf area index (LAI). The measurements were carried out during the growing season of sunn hemp in 2004. The best correlation (r2=0.73) between the surface conductance and all variables was estimated by the ANN, whereas r2 was 0.91 in the training period. The average absolute relative error was 26.54% for the ANN (r2=0.80); 51.07% for the MLR (r2=0.53) and 58.30% for Jarvis model (r2=0.26), when the vapor pressure deficit, temperature, soil water content, global solar radiation and leaf area index were considered to model. Comparisons showed that the ANN approach had a better modeling potential of the surface conductance compared to the MLR and Jarvis model. Keywords: Agriculture, Air-water interaction, Evapotranspiration, Network analysis
{"title":"Modeling of Surface Conductance over Sunn Hemp by Artificial Neural Network","authors":"L. Şaylan, R. Kimura, Nilcan Altınbaş, B. Çaldağ, F. Bakanoğullari","doi":"10.13128/IJAM-589","DOIUrl":"https://doi.org/10.13128/IJAM-589","url":null,"abstract":"Performances of an Artificial Neural Network (ANN), a multiple linear regression (MLR) and the Jarvis type model were compared to estimate the surface conductance of the sunn hemp crop, which is a driving factor affecting evapotranspiration. It was modeled by ANN and MLR using various parameters including global solar radiation, temperature, soil water content, relative humidity, precipitation and irrigation, vapor pressure deficit, wind speed and leaf area index (LAI). The measurements were carried out during the growing season of sunn hemp in 2004. The best correlation (r2=0.73) between the surface conductance and all variables was estimated by the ANN, whereas r2 was 0.91 in the training period. The average absolute relative error was 26.54% for the ANN (r2=0.80); 51.07% for the MLR (r2=0.53) and 58.30% for Jarvis model (r2=0.26), when the vapor pressure deficit, temperature, soil water content, global solar radiation and leaf area index were considered to model. Comparisons showed that the ANN approach had a better modeling potential of the surface conductance compared to the MLR and Jarvis model. \u0000 \u0000Keywords: Agriculture, Air-water interaction, Evapotranspiration, Network analysis","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"82 1","pages":"37-48"},"PeriodicalIF":1.2,"publicationDate":"2019-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76923287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Soil heat flux (G) is an important component of energy balance by constraining the available amount of latent heat and sensible heat. There are many methods and formulations in the literature to estimate G accurately. In this study, widely used G estimation models are chosen to test. The models are based on Spectral Vegetation Indices (SVIs) namely, Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI) together with leaf area index (LAI), and crop height. Two successive growing periods of winter wheat (Triticum Aestivum L.), sunflower (Helianthus annuus L.), and maize (Zea mays L.) fields, located in the northwest part of Turkey, are used. Midday values (average of 09:30- 13:30) of G and net radiation (Rn) used in order to capture the time period, when G is proven to be much dominant. According to the results, overall the best relation obtained with an exponential NDVI model with a determination coefficient value of 0.83 and a root mean square (RMS) error value of 20.28 Wm-2 for maize. For winter wheat, G predicted the best with SAVI based model (r2=0.74), and for sunflower, LAI based model worked best with 0.75 r2 value. Crop height (CH) based nonlinear regression G model that suggested in this study worked better than linear models suggested in the literature with a better determination coefficient (r2=0.70) and a lower RMS error value (10.8 Wm-2).
{"title":"Assessment of Soil Heat Flux Equations for Different Crops under Semi Humid Conditions","authors":"Sezel Karayusufoğlu Uysal, L. Şaylan","doi":"10.13128/IJAM-652","DOIUrl":"https://doi.org/10.13128/IJAM-652","url":null,"abstract":"Soil heat flux (G) is an important component of energy balance by constraining the available amount of latent heat and sensible heat. There are many methods and formulations in the literature to estimate G accurately. In this study, widely used G estimation models are chosen to test. The models are based on Spectral Vegetation Indices (SVIs) namely, Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI) together with leaf area index (LAI), and crop height. Two successive growing periods of winter wheat (Triticum Aestivum L.), sunflower (Helianthus annuus L.), and maize (Zea mays L.) fields, located in the northwest part of Turkey, are used. Midday values (average of 09:30- 13:30) of G and net radiation (Rn) used in order to capture the time period, when G is proven to be much dominant. According to the results, overall the best relation obtained with an exponential NDVI model with a determination coefficient value of 0.83 and a root mean square (RMS) error value of 20.28 Wm-2 for maize. For winter wheat, G predicted the best with SAVI based model (r2=0.74), and for sunflower, LAI based model worked best with 0.75 r2 value. Crop height (CH) based nonlinear regression G model that suggested in this study worked better than linear models suggested in the literature with a better determination coefficient (r2=0.70) and a lower RMS error value (10.8 Wm-2).","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"1 1","pages":"49-61"},"PeriodicalIF":1.2,"publicationDate":"2019-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90213356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Baldi, Giada Brandani, Martina Petralli, A. Messeri, S. Cecchi, R. Vivoli, M. Mancini
In a context of climate change, the knowledge of local meteorological trend and variability is a very useful tool in precision farming for crop production and quality. The aim of this study is to analyze the thermo-pluviometric variability of Val d’Orcia olive orchards area (Tuscany, Italy), a hilly region characterized by a great orographic variability that lacs of historical termo-pluviometric information. In this study trend of thermo-pluviometric indices (TX, TN, TG, FD, RR and GDD) for the period 2012-2017 in three weather station located at different height and orientation in the Val d’Orcia Area are presented. During the study period, yearly extra virgin olive oil (EVO) yield was also analyzed. The variability observed in precipitation confirms the strong influence of topography and atmospheric circulation on local precipitation distribution. While the analysis of thermal regimes and frost days evidence the strong presence of thermal inversion phenomenon in this area. A strong relationship was found between yearly EVO yield and GDD during the vegetative period.
在气候变化的背景下，对当地气象趋势和变率的了解是提高作物产量和质量的精准农业的一个非常有用的工具。本研究的目的是分析Val d 'Orcia橄榄园地区(意大利托斯卡纳)的热雨变率，这是一个丘陵地区，其地形变异性很大，缺乏历史气象降水信息。本文分析了奥恰谷地区不同高度和方位气象站2012-2017年的热雨指数(TX、TN、TG、FD、RR和GDD)变化趋势。在研究期间，还分析了年特级初榨橄榄油(EVO)产量。观测到的降水变率证实了地形和大气环流对局地降水分布的强烈影响。而热状态和霜冻日的分析则证明了该地区存在强烈的逆温现象。在营养期，年EVO产量与GDD有较强的相关性。
{"title":"Termo-pluviometric Variability of Val d’Orcia Olive Orchards area (Italy)","authors":"A. Baldi, Giada Brandani, Martina Petralli, A. Messeri, S. Cecchi, R. Vivoli, M. Mancini","doi":"10.13128/IJAM-649","DOIUrl":"https://doi.org/10.13128/IJAM-649","url":null,"abstract":"In a context of climate change, the knowledge of local meteorological trend and variability is a very useful tool in precision farming for crop production and quality. The aim of this study is to analyze the thermo-pluviometric variability of Val d’Orcia olive orchards area (Tuscany, Italy), a hilly region characterized by a great orographic variability that lacs of historical termo-pluviometric information. In this study trend of thermo-pluviometric indices (TX, TN, TG, FD, RR and GDD) for the period 2012-2017 in three weather station located at different height and orientation in the Val d’Orcia Area are presented. During the study period, yearly extra virgin olive oil (EVO) yield was also analyzed. The variability observed in precipitation confirms the strong influence of topography and atmospheric circulation on local precipitation distribution. While the analysis of thermal regimes and frost days evidence the strong presence of thermal inversion phenomenon in this area. A strong relationship was found between yearly EVO yield and GDD during the vegetative period.","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"24 1","pages":"11-20"},"PeriodicalIF":1.2,"publicationDate":"2019-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86532205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Doroteja Kociper, K. V. Mally, Lučka Kajfež Bogataj
Climate variability and extreme weather events, especially droughts, floods, storm hazards, low temperatures with frost and heat waves have significant negative effects on agriculture in Slovenia and increase its vulnerability. This study took into account the concept of vulnerability of the International Panel on Climate Change. The index of climate vulnerability of agriculture was developed on the basis of three indicators: exposure (climate variability and extreme weather events), sensitivity (threats due to natural conditions, changes in agriculture, vitality of the population) and adaptive capacity (income, sustainable management and natural resources). Climate vulnerability of agriculture was quantitatively analyzed with vulnerability indicators through the statistical regions of the Republic of Slovenia, and thus contributed to the regionally oriented approaches that seek to answer the challenges of climate vulnerability of agriculture in Slovenia. The results show higher climate vulnerability of agriculture in the western and central Slovenia and lower vulnerability in the eastern and northeastern part of the country.
{"title":"Climate vulnerability of agriculture in statistical regions of Slovenia","authors":"Doroteja Kociper, K. V. Mally, Lučka Kajfež Bogataj","doi":"10.13128/IJAM-651","DOIUrl":"https://doi.org/10.13128/IJAM-651","url":null,"abstract":"Climate variability and extreme weather events, especially droughts, floods, storm hazards, low temperatures with frost and heat waves have significant negative effects on agriculture in Slovenia and increase its vulnerability. This study took into account the concept of vulnerability of the International Panel on Climate Change. The index of climate vulnerability of agriculture was developed on the basis of three indicators: exposure (climate variability and extreme weather events), sensitivity (threats due to natural conditions, changes in agriculture, vitality of the population) and adaptive capacity (income, sustainable management and natural resources). Climate vulnerability of agriculture was quantitatively analyzed with vulnerability indicators through the statistical regions of the Republic of Slovenia, and thus contributed to the regionally oriented approaches that seek to answer the challenges of climate vulnerability of agriculture in Slovenia. The results show higher climate vulnerability of agriculture in the western and central Slovenia and lower vulnerability in the eastern and northeastern part of the country.","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"241 1","pages":"35-48"},"PeriodicalIF":1.2,"publicationDate":"2019-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77080241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Verdi, M. Mancini, M. Napoli, R. Vivoli, A. Pardini, S. Orlandini, A. D. Marta
During the last decades, climate change and variability are increasingly and negatively affecting agriculture. To ensure satisfactory and stable food production, agriculture is intensifying the adoption of external input with environmental consequences such as the emission of greenhouse gases. In this experiment, we monitored CO2 and CH4 emission dynamics from cultivation of maize for silage grown under different fertilization treatments: (i) liquid fraction of digestate from pig slurries, (ii) urea, and (iii) no fertilization (control), in an extremely dry summer in Central Italy. Results show that the use of the liquid-organic fertilizer (digestate) significantly increased CO2 emissions from soil (685.29 kg-C ha-1) compared to the conventional fertilizer (urea) (391.60 kg-C ha-1). However, CH4 emissions were comparable between the two fertilizers and almost negligible compared to those of CO2. In both treatments CH4 emissions were enhanced by the only precipitation event, coupled with an increase of air temperature. Effectiveness of tested fertilizers was assessed through a yield analysis, and proved that digestate may represent a viable alternative to urea (6.97 and 6.48 t ha-1). Nevertheless, considering CO2 emissions from digestate and the numerous passes in field needed for its spreading, the use of this fertilizer in extreme dry conditions requires specific considerations.
在过去的几十年里，气候变化和变异对农业的负面影响越来越大。为了确保令人满意和稳定的粮食生产，农业正在加紧采用具有温室气体排放等环境后果的外部投入。在这项试验中，我们在意大利中部一个极度干燥的夏季，监测了不同施肥处理下青贮玉米的CO2和CH4排放动态:(i)猪浆消化液的液体部分，(ii)尿素和(iii)不施肥(对照)。结果表明:液体有机肥(消化液)比常规有机肥(尿素)(391.60 kg-C ha-1)显著增加土壤CO2排放量(685.29 kg-C ha-1);然而，两种肥料的甲烷排放量相当，与二氧化碳排放量相比几乎可以忽略不计。在两种处理中，CH4排放均因降水事件和气温升高而增加。通过产量分析评估了所测试肥料的有效性，并证明消化液可能是尿素的可行替代品(6.97和6.48 t ha-1)。然而，考虑到消化过程中二氧化碳的排放和其扩散所需的大量通道，在极端干燥条件下使用这种肥料需要特别考虑。
{"title":"Soil carbon emissions from maize under different fertilization methods in an extremely dry summer in Italy","authors":"L. Verdi, M. Mancini, M. Napoli, R. Vivoli, A. Pardini, S. Orlandini, A. D. Marta","doi":"10.13128/IJAM-648","DOIUrl":"https://doi.org/10.13128/IJAM-648","url":null,"abstract":"During the last decades, climate change and variability are increasingly and negatively affecting agriculture. To ensure satisfactory and stable food production, agriculture is intensifying the adoption of external input with environmental consequences such as the emission of greenhouse gases. In this experiment, we monitored CO2 and CH4 emission dynamics from cultivation of maize for silage grown under different fertilization treatments: (i) liquid fraction of digestate from pig slurries, (ii) urea, and (iii) no fertilization (control), in an extremely dry summer in Central Italy. Results show that the use of the liquid-organic fertilizer (digestate) significantly increased CO2 emissions from soil (685.29 kg-C ha-1) compared to the conventional fertilizer (urea) (391.60 kg-C ha-1). However, CH4 emissions were comparable between the two fertilizers and almost negligible compared to those of CO2. In both treatments CH4 emissions were enhanced by the only precipitation event, coupled with an increase of air temperature. Effectiveness of tested fertilizers was assessed through a yield analysis, and proved that digestate may represent a viable alternative to urea (6.97 and 6.48 t ha-1). Nevertheless, considering CO2 emissions from digestate and the numerous passes in field needed for its spreading, the use of this fertilizer in extreme dry conditions requires specific considerations.","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"27 1","pages":"3-10"},"PeriodicalIF":1.2,"publicationDate":"2019-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86967531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Basma Latrech, H. Ghazouani, Asma Lasram, B. M’hamdi, M. Mansour, A. Boujelben
Field experiment was carried out to examine the effects of full and deficit irrigation treatments on yield and irrigation water productivity of potato crop conducted under semi-arid conditions of Tunisia. In addition, the accuracy of different models for computing daily ET0 have been assessed against the standardized FAO 56-Penman Monteith estimations. An application of the FAO-56 dual approach to calculate actual evapotranspiration (ETa) is reported, implemented by means of the FAO-56 model. The obtained daily values of ET0, were used as input in the FAO-56 model, in order to assess their impact on simulated actual evapotranspiration of potato crop. The obtained results indicate that potato yield decrease significantly with decreasing irrigation amount. However, no significant difference was obtained in term of WPirrig. Comparison between the different ET0 methods against the FAO-56 PM, revealed that the Makkink and Priestley-Taylor models might be considered as efficient alternatives for estimating ET0. Furthermore, the simulated actual evapotranspiration are compared with their corresponding obtained by the water balance method. The statistical results of comparison highlighted that the best performances are accorded to the FAO-56 PM. More detailed analysis, evidenced also that the Hargreaves-Samani, Pristley-Taylor and Makkink approaches can be used as valid alternatives for estimating ETa.
{"title":"Assessment of different methods for simulating actual evapotranspiration in a semi-arid environment","authors":"Basma Latrech, H. Ghazouani, Asma Lasram, B. M’hamdi, M. Mansour, A. Boujelben","doi":"10.13128/IJAM-650","DOIUrl":"https://doi.org/10.13128/IJAM-650","url":null,"abstract":"Field experiment was carried out to examine the effects of full and deficit irrigation treatments on yield and irrigation water productivity of potato crop conducted under semi-arid conditions of Tunisia. In addition, the accuracy of different models for computing daily ET0 have been assessed against the standardized FAO 56-Penman Monteith estimations. An application of the FAO-56 dual approach to calculate actual evapotranspiration (ETa) is reported, implemented by means of the FAO-56 model. The obtained daily values of ET0, were used as input in the FAO-56 model, in order to assess their impact on simulated actual evapotranspiration of potato crop. The obtained results indicate that potato yield decrease significantly with decreasing irrigation amount. However, no significant difference was obtained in term of WPirrig. Comparison between the different ET0 methods against the FAO-56 PM, revealed that the Makkink and Priestley-Taylor models might be considered as efficient alternatives for estimating ET0. Furthermore, the simulated actual evapotranspiration are compared with their corresponding obtained by the water balance method. The statistical results of comparison highlighted that the best performances are accorded to the FAO-56 PM. More detailed analysis, evidenced also that the Hargreaves-Samani, Pristley-Taylor and Makkink approaches can be used as valid alternatives for estimating ETa.","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"39 1","pages":"21-34"},"PeriodicalIF":1.2,"publicationDate":"2019-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89060930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Alvar-Beltrán, C. Saturnin, A. Dao, A. D. Marta, J. Sanou, S. Orlandini
Chenopodium quinoa (Willd.) is an herbaceous C3 crop originating in the Andean Altiplano. Quinoa possesses a great deal of genetic variability, can adapt to diverse climatic conditions, besides of having seeds with high nutritional properties. An experiment conducted in Burkina Faso has determined the response of two quinoa varieties (Titicaca and Negra Collana) to different planting dates (November vs December), irrigation levels (Potential evapotranspiration-PET, 100, 80 and 60% PET), and N fertilization rates (100, 50 and 25 kg N ha-1). Main research findings have shown that quinoa can be highly performant under drought stress conditions and low nitrogen inputs, besides of coping with high temperatures typically of the Sahel. The highest yields (1.9 t ha-1) were achieved when sown in November at 60 % PET and 25 kg N ha-1. For this location, short cycle varieties, such as Titicaca, were recommended in order to avoid thermic stress conditions occurring prior to the onset of the rainy season (May-October).
藜麦(野生)是一种草本C3作物，原产于安第斯高原。藜麦具有很大的遗传变异，能适应不同的气候条件，而且种子营养价值高。在布基纳法索进行的一项试验确定了两个藜麦品种(Titicaca和Negra Collana)对不同种植日期(11月和12月)、灌溉水平(潜在蒸散量PET、100%、80%和60% PET)和施氮量(100、50和25 kg N ha-1)的反应。主要研究结果表明，除了应对萨赫勒地区典型的高温外，藜麦在干旱胁迫条件和低氮投入下也能表现优异。在11月播种时，以60%的PET和25公斤N / hm -1，获得最高产量(1.9 t hm -1)。对于这个地区，推荐短周期品种，如提提卡卡，以避免在雨季(5月至10月)开始之前发生热应激条件。
{"title":"Effect of drought and nitrogen fertilisation on quinoa (Chenopodium quinoa Willd.) under field conditions in Burkina Faso","authors":"J. Alvar-Beltrán, C. Saturnin, A. Dao, A. D. Marta, J. Sanou, S. Orlandini","doi":"10.13128/IJAM-289","DOIUrl":"https://doi.org/10.13128/IJAM-289","url":null,"abstract":"Chenopodium quinoa (Willd.) is an herbaceous C3 crop originating in the Andean Altiplano. Quinoa possesses a great deal of genetic variability, can adapt to diverse climatic conditions, besides of having seeds with high nutritional properties. An experiment conducted in Burkina Faso has determined the response of two quinoa varieties (Titicaca and Negra Collana) to different planting dates (November vs December), irrigation levels (Potential evapotranspiration-PET, 100, 80 and 60% PET), and N fertilization rates (100, 50 and 25 kg N ha-1). Main research findings have shown that quinoa can be highly performant under drought stress conditions and low nitrogen inputs, besides of coping with high temperatures typically of the Sahel. The highest yields (1.9 t ha-1) were achieved when sown in November at 60 % PET and 25 kg N ha-1. For this location, short cycle varieties, such as Titicaca, were recommended in order to avoid thermic stress conditions occurring prior to the onset of the rainy season (May-October).","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"1 1","pages":"33-43"},"PeriodicalIF":1.2,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83751976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Climate change is one of the main issues in agriculture. Considering its involvement in the global anthropogenic emissions (GHG) it is no wonder that research is devising ways on how to reduce such effects. A solution to such problems is climate-smart agriculture (CSA). In this paper, we analysed which are the main opportunities granted by agricultural policies when aimed at sustaining innovative agricultural models. A review of the ongoing 93 Rural Development Projects (RDPs) uncovered potential climate-smart solutions for the identified potential threats. The Ministry of Agriculture, Hunting and Fishing of the Region of Emilia-Romagna in Italy has given importance to RDPs to innovate the agricultural sector through policy measures. We analysed an Operational Group (OG) project as an overview of the work. In the case of Emilia-Romagna, the amount of innovation and solutions that can be achieved if policies invest in CSA is very clear. Emilia-Romagna is on the forefront of technological and practical advancements in the EU by implementing CSA as one of the primary solutions to the aforementioned problems and will continuously work on transitioning its agricultural practices to fight climate change.
{"title":"How can policy influence innovation: An exploration of climate-smart activities in Emilia-Romagna","authors":"C. Chieco, Federica Rossi, Slaven Tadić","doi":"10.13128/IJAM-288","DOIUrl":"https://doi.org/10.13128/IJAM-288","url":null,"abstract":"Climate change is one of the main issues in agriculture. Considering its involvement in the global anthropogenic emissions (GHG) it is no wonder that research is devising ways on how to reduce such effects. A solution to such problems is climate-smart agriculture (CSA). In this paper, we analysed which are the main opportunities granted by agricultural policies when aimed at sustaining innovative agricultural models. A review of the ongoing 93 Rural Development Projects (RDPs) uncovered potential climate-smart solutions for the identified potential threats. The Ministry of Agriculture, Hunting and Fishing of the Region of Emilia-Romagna in Italy has given importance to RDPs to innovate the agricultural sector through policy measures. We analysed an Operational Group (OG) project as an overview of the work. In the case of Emilia-Romagna, the amount of innovation and solutions that can be achieved if policies invest in CSA is very clear. Emilia-Romagna is on the forefront of technological and practical advancements in the EU by implementing CSA as one of the primary solutions to the aforementioned problems and will continuously work on transitioning its agricultural practices to fight climate change.","PeriodicalId":54371,"journal":{"name":"Italian Journal of Agrometeorology-Rivista Italiana Di Agrometeorologia","volume":"26 1","pages":"25-31"},"PeriodicalIF":1.2,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76809833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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