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Downy mildew, powdery mildew, and gray mold are major diseases of grapevine with a strong negative impact on fruit yield and fruit quality. These diseases are controlled by the application of chemicals, which may cause undesirable effects on the environment and on human health. Thus, monitoring and forecasting crop disease is essential to support integrated pest management (IPM) measures. In this study, two tree-based machine learning (ML) algorithms, random forest and C5.0, were compared to test their capability to predict the appearance of symptoms of grapevine diseases, considering meteorological conditions, spatial indices, the number of crop protection treatments and the frequency of monitoring days in which symptoms were recorded in the previous year. Data collected in Tuscany region (Italy), on the presence of symptoms on grapevine, from 2006 to 2017 were divided with an 80/20 proportion in training and test set, data collected in 2018 and 2019 were tested as independent years for downy mildew and powdery mildew. The frequency of symptoms in the previous year and the cumulative precipitation from April to seven days before the monitoring day were the most important variables among those considered in the analysis for predicting the occurrence of disease symptoms. The best performance in predicting the presence of symptoms of the three diseases was obtained with the algorithm C5.0 by applying (i) a technique to deal with imbalanced dataset (i.e., symptoms were detected in the minority of observations) and (ii) an optimized cut-off for predictions. The balanced accuracy achieved in the test set was 0.8 for downy mildew, 0.7 for powdery mildew and 0.9 for gray mold. The application of the models for downy mildew and powdery mildew in the two independent years (2018 and 2019) achieved a lower balanced accuracy, around 0.7 for both the diseases. Machine learning models were able to select the best predictors and to unravel the complex relationships among geographic indices, bioclimatic indices, protection treatments and the frequency of symptoms in the previous year.

Dairy sheep systems are relevant for the economy of many rural areas of the Mediterranean Basin and the optimisation of their productive factors is necessary to improve their competitiveness and to reduce their environmental impact. The objective of this study was to assess, through a farm-scale life cycle assessment (LCA) approach, the potential of reducing environmental impacts on ewe milk of an innovative farming system (IF), based on the adoption of a precision feeding approach to improve milk production and quality, compared with a conventional farming system (CF) in dairy sheep farms in Tuscany region, Italy. The LCA analysis was carried out through a cradle-to-farm-gate LCA, comparing three conventional farms with three innovative farms, using 1 kg of fat protein corrected milk (FPCM) as a functional unit. The Small Ruminants Module of Nutritional Dynamic System (NDS) software was used to estimate methane emissions due to enteric fermentation. The introduction of precision feeding strategy reduced the environmental impacts of ewe milk as a consequence of the increased milk production efficiency (+50%). Indeed, the environmental impact of ewe milk was reduced in IF by 42% as the average of the impact categories being significantly different between the two farming systems.HighlightsPrecision feeding is recognised as a strategy to mitigate the environmental impacts of ruminant production.Dairy sheep innovative farms (IF), using a precision feeding approach, were compared with conventional farms (CF).Environmental impacts of ewe mik were assessed through an LCA approach and a mechanistic model for ruminant diet formulation and evaluation.Precision feeding improved milk production efficiency (+50) and lowered environmental impacts.Environmental impact of ewe milk was significantly reduced in IF by 42% in eight impact categories out of 15. Precision feeding is recognised as a strategy to mitigate the environmental impacts of ruminant production. Dairy sheep innovative farms (IF), using a precision feeding approach, were compared with conventional farms (CF). Environmental impacts of ewe mik were assessed through an LCA approach and a mechanistic model for ruminant diet formulation and evaluation. Precision feeding improved milk production efficiency (+50) and lowered environmental impacts. Environmental impact of ewe milk was significantly reduced in IF by 42% in eight impact categories out of 15.

Measuring at high frequency soil Auxes of carbon dioxide (CO 2 ), and nitrous oxide (N 2 O) in agricultural soils requires appropriate technology. With this aim, a prototype was developed and tested in agricultural soils for 5 months, within the framework of the LIFE project AGRESTIC. The prototype is composed by two automatic GHG stations for measuring CO 2 (LI-COR LI-850) and N 2 O (Teledyne GFC-7002TU) fluxes from soil and an IT infrastructure for data management. The two GHG stations were installed one in Ravenna, Italy, (Ca Bosco farm) and the other in Foggia, Italy, (Caione farm), where two different cropping systems were compared. Along the period going from January 1st to May 31st, 2020 the two GHG stations proved to be robust to field conditions (e.g. wind, rain, freeze etc.). The quality of the measurements was different in the two sites, with more than 90% of good measurements in Ravenna and more than 60% in Foggia.

Poplar (Populus L. spp.) Short Rotation Coppice systems (SRCs) for bioenergy production are being converted back to arable land. Transitioning to Alley Cropping Systems (ACSs) could be a suitable strategy for integrating former tree rows and arable crops. A field trial (Pisa, Central Italy) was set up with the aim of assessing the C storage of an ACS system based on hybrid poplar and sorghum (Sorghum bicolor L. Moench) and comparing it with that of an SRC cultivation system. The carbon budget at the agroecosystem scale was assessed in the first year of the transition using the net biome production (NBP) approach with a simplified method. The overall NBP for the SRC was positive (96 &plusmn, 40 g C m&minus, 2 year&minus, 1), highlighting that the system was a net carbon sink (i.e., NBP &gt, 0). However, the ACS registered a net C loss (i.e., NBP &lt, 0), since the NBP was &minus, 93 &plusmn, 56 g C m&minus, 1. In the first year of the transition, converting the SRC into an ACS counteracted the potential beneficial effect of C storage in tree belowground biomass due to the high heterotrophic respiration rate recorded in the ACS, which was fostered by the incorporation of residues and tillage disturbance in the alley. Additional years of heterotrophic respiration measurements could allow for an estimate of the speed and extent of C losses.

Predicting the occurrence of B. oleae infestation is needed in sustainable olive tree growing, for the application of preventive control strategies. In this study, machine learning (ML) algorithms were tested to predict the occurrence of B. oleae infestation. Regional-based and long-term (2002–2019) dataset on infestation collected by trained technicians in the sampling network (Tuscany, central Italy) was related to geographic variables, bioclimatic indices and the frequency of infestation in the previous year. Five ML algorithms were compared. Data collected from 2002 to 2017 were divided with an 80/20 proportion in “training” and “test 20%”, considering the group “farm ID × year”. In addition, data collected in 2018 and 2019 (“test 18–19”) were also tested. The algorithm C5.0 was selected as the most suitable algorithm (AUC = 0.9) and used to predict the occurrence of B. oleae infestation. The following results were obtained: (i) a negative effect on the probability of infestation of the distance from the sea of the olive groves and of the frequency of infestation of the previous year and (ii) a positive effect of doy (day of the year), cumulative degree days and mean air temperature of the previous winter. The occurrence of infestation was predicted with an accuracy of 0.8 on “test 20%” and of 0.7 on “test 18–19”. The potential of this methodology to predict the occurrence of B. oleae infestation in a short-time step, e.g., one week, needs to be tested in a real application, running the model weekly.

In the Mediterranean area, semi-extensive mixed farming systems characterise the inland landscape and guarantee the maintenance of several agroecosystem services. Rationed and rotational grazing have been proposed as efficient agroecological practices for sustainable intensification. Previous studies have highlighted that, during spring, restricted access time to pasture of below four hours per day decreases herbage intake and milk production of rotationally stoked ewes. The aim of this study was to assess the effect of restricted access time on daily herbage intake and milk productivity of Sarda ewes under rotational grazing management in a real farm located in southern Tuscany. The entire flock of 145 lactating ewes was allotted two homogenous groups and rotationally stoked on a grass-legume mixed pasture and fed about 1.7 kg of DM ewe–1 d–1 of supplementation. Each group was then assigned to the following treatments: two hours per day of access time to pasture, from 10:00 to 12:00 CET, and four hours per day of access time to pasture, from 10:00 to 14:00 CET. Data on herbage yield and quality, dry matter intake and milk yield were collected from April 5 to May 10, 2018. The rotational grazing schedule was conducted allowing for abundant herbage and exploiting high-nutritive biomass of the upper horizon sward. The results of our on-farm experiment showed that restricting daily access time to pasture down two hours did not reduce the potential daily herbage intake and the milk performance of dairy ewes rotationally stocked on a mixed pasture in spring. Our study also highlighted the capacity of ewes to self-regulate the herbage intake in order to meet their energy requirements, when neutral detergent fibre is not a limiting factor. Our outcomes should encourage researchers and farmers to co-design further on-farm experiments. Highlights - The challenge lies in comparing data of dairy sheep productivity collected at real farm condition with previous data measured in Mediterranean research stations. - In this study, no difference in milk production was found between ewes allowed to graze two hours and four hours per day in spring. - The ewes’ herbage intake rate correlates positively with pasture quality and a mixed pasture with a high share of legumes led to a high intake rate. - We believe that the outcomes in this manuscript can contribute to increase knowledge about the sustainable management of small ruminant dairy farms in the contest of rural areas.

Agroforestry is indicated as a farming practice suited to enhance ecosystem services generated by cropping systems. However, farmers are often reluctant to implement agroforestry systems due to the potential yield loss of crops. In a field trial, soybean was intercropped with poplar short-rotation-coppice rows in an alley-cropping system with 13.5 m wide alleys, in order to assess the effect of tree presence on soybean yield and quality. The light availability (LA) was significantly affected by the tree presence, with an increasing effect along the season due to tree growth, being at its lowest in the tree&ndash, crop interface positions (West and East). Significant effects of the tree-distance and LA were registered on soybean yield, with the highest reduction of soybean yield in the West (&minus, 78%) and East (&minus, 35%) positions. Crude fat content in soybean grain did not vary among positions in the alley, while crude protein content was the lowest in the most shaded position (West &minus, 8% than the highest value). The assessment of spatial variability among plots of measured soil characteristics highlighted no significant effect of pedological conditions upon soybean yield. Thus, in our study, the LA effect was more important than soil characteristics in determining a detrimental effect of competition for resources between soybean and poplar. Conversely, soybean quality was affected by soil characteristics, since crude fat significantly correlated with soil nutrients, pH, soil organic matter and soil texture.

Limits in propagation are hampering the diffusion of giant reed cultivation for biomass. The objective of this study was to compare rhizomes and micropropagated plants with stem cuttings obtained in spring vs late winter (with and without side shoots, respectively) and immediately planted. A three-years field trial was carried out, assessing how rapidly giant reed establishes, and how its yield components (i.e. crop height, stem density, stem diameter) and its rhizomes develop over years depending on the propagation method adopted. Long-lasting variations in yield components depending on propagation were found. In the three years, biomass yield was steadily higher in rhizome-propagated stands (+64% than the average of the other propagation materials), while no significant interactions with the year of study were observed. Stems were thicker in rhizome-propagated and thinner in micropropagated plants, while cutting-propagated ones showed intermediate values. Micropropagation led to a significantly lower ratio between the biomass of rhizomes and the number of rhizome buds. Moreover, micropropagated plants were shorter (crop height: 34%), while stem density was nearly doubled: an inverse relationship between tillering and elongation was highlighted. Plants obtained from winter cuttings were taller than those obtained in spring, although the height difference was mostly achieved towards the end of the vegetative season. At initial growth stages, winter cuttings were slower than spring cuttings in increasing sprout density. Immediately-planted cuttings showed potential to replace micropropagated plants. In particular, cuttings obtained in spring , showed suitability for on-farm propagation, by means of collection from existing stands followed by direct planting.

Plant Leaf Area Index (LAI) is a key variable for several land surface processes related to vegetation dynamics. Satellite systems offer the opportunity to estimate LAI by remote, allowing to reduce costs for crop monitoring over large areas. Indeed, LAI, is a process variable of several models used for the prediction of crop biomass accumulation, yield and canopy coverage over space and time. Uncertainty of LAI estimation by means of Vegetation Indices extrapolated from multispectral satellite images is related to several factors: (i) crop type (due to the variability of plant architectures, the light extinction coefficient highly variable among crop species), (ii) the effect of environmental covariates, which affects the crop development together with the farm management. This study aimed at evaluating how the ground-LAI (Leaf Area Index) measurements and satellite vegetation indexes from Sentinel 2 reflectance were affected by the variety of crop type and the uncertainties related to different farm managements. We used Sentinel-2 imagery spanning across the growth seasons, over three agricultural sites located in the Mediterranean agroecosystem (Central Italy) and we produced satellite NDVI index to estimate LAI by remote over the sites. In the same period, with a monthly stratified random ground sampling design, the three agricultural farms with prevalent herbaceous crop cover were monitored in terms of ground- LAI variations. The novelty and the added value extracted from the results was that the uncertainty induced by farm management (FARM) variability can be relevant as much as the one caused by crop type (CROP) and seasonality (TIME) variations when ground-LAI measurements and satellite NDVI were analyzed by a set of non-liner regression models.

(A challenge for agriculture is to individuate strategies to reduce greenhouse gas emissions (GHG) from soil while preserving crop yield. Agricultural practices are reported to affect carbon dioxide (CO 2 ), nitrous oxide (N 2 O) and methane (CH 4 ) emissions from soil due to their effects on nutrient cycling and soil conditions (e.g. soil water content, soil temperature etc.). A field campaign was carried out to measure the effect of reducing irrigation level (drip irrigation, rainfed) and N fertilizer rate (170 kg N ha-1, 130 kg N ha-1, 0 kg N ha-1) on GHG emissions from soil and on crop yield on maize cultivated in Tuscany region (Italy). Main result highlighted that decreasing N fertilization of about 20% reduced cumulative N 2 O emissions (on average -42%) without decreasing the crop productivity, indicating that improving the N use efficiency could be the best strategy to reduce GHG emissions from soil cultivated with maize in our environment.)

Nitrous oxide (N2O) is emitted from agricultural soils as a product of biotic pathways of the nitrogen (N) cycle. Agricultural practices may affect soil water content, temperature and N availability, and consequently N2O emissions. Thus, it is necessary to identify strategies to mitigate N2O emissions while maintaining crop yields. This two-year study on durum wheat and sunflower in a Mediterranean environment evaluated the influence of tillage intensity (plowing vs. minimum tillage) and N fertilizer rate (N0, N1 and N2: 0, 110 and 170 kg N ha−1, respectively, for wheat, and 0, 80 and 140 kg N ha−1, respectively, for sunflower) on crop yields and N2O emissions. Reducing the N fertilizer rate by ca. 40% resulted in an average mitigation of ca. 35% of cumulative N2O emissions during the growing season of both crops. From N1 to N2, the grain yield of sunflower did not increase, but that of wheat did so by ca. 25%. Indeed, yield-scaled N2O emissions of N0, were the highest in wheat (259 ± 45 g N2O–N Mg−1 dry grain, 12.2 ± 2.0 g N2O–N kg−1 N uptake) and the lowest in sunflower (62 ± 7 g N2O–N Mg−1 dry grain, 2.0 ± 0.2 g N2O–N kg−1 N uptake). Reducing tillage intensity decreased cumulative N2O emissions significantly only for sunflower during the second year (by 35%), but not for any other treatment. The effect of the reduced tillage depth on grain yield varied between the 2 years, being negative only under wetter growing seasons (− 12% in wheat and − 9% in sunflower).

Besides improving soil properties and N availability, N2-fixing crops may also mitigate soil N2O emissions, by reducing N fertilizer requirements. That said, the N released in their root exudates and through the decomposition of their residues may increase N2O emissions. Agricultural practices like tillage that affect soil parameters are known to influence the processes that lead to N2O production. However, the combined effect of the tillage system used and the crop type being cultivated on soil N2O emissions remains unclear, especially in a Mediterranean climate. A two-year study was carried out on a faba bean (Vicia faba L. var. minor Beck) crop as part of a long-term tillage experiment (> 20 years) in a Mediterranean environment. We evaluated the effects of two tillage systems, ploughing (P) and minimum tillage (MT), on the following parameters: N2O emissions, grain yield, N assimilated in plant biomass and biological N2 fixation. Our results showed grain yield to be higher in MT than P in the first year and roughly similar in the second. Moreover, cumulative N2O emissions were lower in MT than P in both years (up to −80%). Indeed, MT was identified in our environment as a sustainable means of achieving N2O emissions mitigation while also maximizing grain yield. Furthermore, the percentage of N derived from N2 fixation (Ndfa%) in plants stood at 80% on average, affected by tillage only in the second year, with higher values in P than MT. Moreover, a positive relationship between N2 fixation and N2O emissions was reported, particularly in P, and during the fallow period.

In Italy, managed soils account for about 50% of annual national emissions of nitrous oxide (N2O), thus the effect of agricultural practices on N2O emissions must be studied in order to develop mitigation strategies. Soil N2O emissions were measured in two field campaigns (2013–2014 and 2014–2015) on durum wheat in a Mediterranean environment to test the mitigation potential of reduced tillage and nitrogen (N) fertilization rate. N2O emissions were measured with a fully-transportable instrument developed during the project LIFE + IPNOA “Improved flux Prototypes for N2O emission reduction from Agriculture” and equipped with an infrared laser detector. Reducing tillage from ploughing to minimum tillage had no effect on average daily N2O flux, while decreasing the N rate from 170 to 110 kg N ha−1 reduced the average daily N2O flux, without negatively affecting the grain yield. Furthermore, N2O daily flux were positively correlated with soil water filled pore space, NO3-N, and NH4-N concentrations, and they were largely variable between the two field campaigns as a result of different environmental and management conditions (i.e.: rainfall, different amount of crop residues incorporated in soil). Overall, the innovative fully-transportable instrument performed well in the field and allowed us to conclude that decreasing the N fertilizer rate was a valuable option to mitigate N2O emissions without negative effects on wheat productivity.

The assessment of nitrous oxide (N2O) fluxes from agricultural soil surfaces still poses a major challenge to the scientific community. The evaluations of integrated soil fluxes of N2O are difficult owing to their lower emissions when compared with CO2. These emissions are also sporadic as environmental conditions act as a limiting factor. A station prototype was developed to integrate annual N2O and CO2 emissions using an automatic chamber technique and infrared spectrometers within the LIFE project (IPNOA: LIFE11 ENV/IT/00032). It was installed from June 2014 to October 2015 in an experimental maize field in Tuscany. The detection limits for the fluxes were evaluated up to 1.6 ng N-N2O m2 s−1 and 0.3 μg C-CO2 m2 s−1. A cross-comparison carried out in September 2015 with the “mobile IPNOA prototype”; a high-sensibility transportable instrument already validated provided evidence of very similar values and highlighted flux assessment limitations according to the gas analyzers used. The permanent monitoring device showed that temporal distribution of N2O fluxes can be very large and discontinuous over short periods of less than 10 days and that N2O fluxes were below the detection limit of the instrumentation during approximately 70% of the measurement time. The N2O emission factors were estimated to 1.9% in 2014 and 1.7% in 2015, within the range of IPCC assessments.

The production of nitrous oxide (N2O) in soil is mainly related to nitrification and denitrification processes, taking place under aerobic and anaerobic conditions, respectively. Oxygen, ammonium (NH4+) and nitrate (NO3−) concentrations in soil are the main factors controlling the N2O production processes. Many studies confirm that N2O emissions in agroecosystems are stimulated by increasing the N fertilizer rate. Beside the N rate, the fertilizer formulation may affect soil N2O emissions, though the effects are still unclear and may be different according to soil type, soil water content and oxygen availability expressed as soil water filled pores space (WFPS). Enhanced efficiency fertilizers, such as fertilizers with nitrification and urease inhibitors (NIs, UIs) may slow down N2O production processes, although different results were reported regarding their effectiveness. This study contributed to the evaluation of the effect of mineral N fertilizer formulation on N2O and CO2 emissions, through two laboratory experiments carried out on soil cores distributing to two different textured soils: i) nitrate or ammonium-based fertilizer under increasing WFPS levels (Exp.1), and; ii) NIs and UI with various N fertilizers, including a new NI (DMPSA) (Exp.2). The highest N2O and CO2 emissions were recorded after the application of an ammonium-based fertilizer in both soils, suggesting the preponderance of nitrifying organisms. The results confirmed that WFPS is a key driver for N2O emissions, with highest N2O emissions occurring at WFPS > 75%, while CO2 emissions decreased linearly with increasing WFPS across all fertilizer treatments and in both soils. NIs were effective only in the soil with the highest nitrification activity and the lowest clay content, decreasing N2O emissions by an average of 50%, while the UI did not reduce N2O emissions in either soil. These results proved that soil characteristics significantly affect NIs capacity to mitigate N2O emissions from soil. (Abbreviations : CS clay soil ; CLS clay loam soil ; NI nitrification inhibitor ; UI urease inhibitor ; AN ammonium nitrate ; ANi ammonium nitrate + 3.4-dimethylpyrazol succinate (EuroChem Agro, DMPSA) ; ASN ammonium sulphate nitrate ; ASNi ammonium sulphate nitrate + 3.4-dimethylpyrazole phosphate (ENTEC®, DMPP) ; UREA urea ; UREAi urea + N-(n-butyl) thiophosphoric triamide (NBPT) ; AS ammonium sulphate ; KN potassium nitrate

A combination of organic and conservation approaches have not been widely tested, neither considering agronomic implications nor the impacts on the environment. Focussing on the effect of agricultural practices on greenhouse gas (GHG) emissions from soil, the hypothesis of this research is that the organic conservation system (ORG+) may reduce emissions of N2O, CH4 and CO2 from soil, compared to an integrated farming system (INT) and an organic (ORG) system in a two-year irrigated vegetable crop rotation set up in 2014, in a Mediterranean environment. The crop rotation included: Savoy cabbage (Brassica oleracea var. sabauda L. cv. Famosa), spring lettuce (Lactuca sativa L. cv. Justine), fennel (Foeniculum vulgare Mill. cv. Montebianco) and summer lettuce (L. sativa cv. Ballerina). Fluxes from soil of N2O, CH4 and CO2 were measured from October 2014 to July 2016 with the flow-through non-steady state chamber technique using a mobile instrument equipped with high precision analysers. Both cumulative and daily N2O emissions were mainly lower in ORG+ than in INT and ORG. All the cropping systems acted as a sink of CH4, with no significant differences among treatments. The ORG and ORG+ systems accounted for higher cumulative and daily CO2 emissions than INT, maybe due to the stimulating effect on soil respiration of organic material (fertilizers/plant biomass) supplied in ORG and ORG+. Overall, the integration of conservation and organic agriculture showed a tendency for higher CO2 emissions and lower N2O emissions than the other treatments, without any clear results on its potential for mitigating GHG emissions from soil.

Introducing nitrogen N 2 -fixing crops into cereal-based crop rotations reduces N-fertiliser use and may mitigate soil emissions of nitrous oxide (N 2 O). However, the effect of the cultivation of N 2 -fixing crops on N 2 O emissions is still not well understood. N 2 O from N 2 -fixing crops can be emitted in two ways: during biological N 2 fixation itself and when legume residues are returned to the soil. A field trial was carried out on clover ( Trifolium squarrosum Savi) to test the role of leguminous crops on N 2 O emissions in the Mediterranean environment. Monitoring was performed from December 2013 to September 2014. Cumulated N-N 2 O fluxes were calculated for the growing season (Phase 1) and the post-harvest period (Phase 2) in order to assess the importance of each phase. Our results did not show statistically significant differences between the two phases in term of contribution to the total cumulative N-N 2 O emissions, in fact Phase 1 and Phase 2 accounted respectively for 43 and 57% of the total.

Agricultural activities are co-responsible for the emission of the most important greenhouse gases: carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O). Development of methodologies to improve monitoring techniques for N 2 O are still needful. The LIFE+IPNOA project aims to improve the emissions monitoring of nitrous oxide from agricultural soils and to identify the agricultural practices that can limit N 2 O production. In order to achieve this objective, both a mobile and a stationary instrument were developed and validated. Several experimental field trials were set up in two different sites investigating the most representative crops of Tuscany (Central Italy), namely durum wheat, maize, sunflower, tomato and faba bean. The field trials were realized in order to test the effect on N 2 O emissions of key factors: tillage intensity, nitrogen fertiliser rate and irrigation. The field trial on durum wheat was set up in 2013 to test the effect of tillage intensity (minimum and conventional tillage) and nitrogen fertilisation rate (0, 110, 170 kg N ha -1 ) on soil N 2 O flux. Monitoring was carried out using the IPNOA mobile prototype. Preliminary results on N 2 O emissions for the durum wheat growing season showed that mean daily N 2 O fluxes ranged from –0.13 to 6.43 mg m -2 day -1 and cumulative N 2 O-N emissions over the period ranged from 827 to 2340 g N 2 O-N ha -1 . Tillage did not affect N 2 O flux while increasing nitrogen fertilisation rate resulted to significantly increase N2O emissions. The IPNOA mobile prototype performed well during this first year of monitoring, allowing to catch both very low fluxes and peaks on N 2 O emissions after nitrogen supply, showing a good suitability to the field conditions.

During cold acclimation, warm-season grasses exhibit growth stall and eventually the onset of rest. Late-season N fertilization is an alternative way for reduction of the dormancy period. The objectives of the present study were (1) to assess the effects of different N sources, and timing on freezing tolerance using controlled environment acclimation and freezing procedures and (2) to determine the relationship of nonstructural carbohydrates and photosynthetic pigments with the freeze tolerance of bermudagrass and zoysiagrass. source treatment exhibited a relative peak at 14 days (2 weeks) before the treatment. In bermudagrass, treatment depressed starch accumulation at 14 and 28 days compared to the control. As expected, in both species a higher concentration of soluble carbohydrates were observed in sprigs tissues. A sharp decline was evident on the treatment in leaves, stems, and roots tissues at 14 days, in correspondence with a lower freeze tolerance, whereas in the treatment an accumulation...