The dates displayed for an article provide information on when various publication milestones were reached at the journal that has published the article activities on preceding journals at which the article was previously under consideration are not shown (for instance submission International Biodeterioration and BiodegradationCitation Excerpt :Precipitation could cause preferential metal-ion migration to the surface leading to ‘case hardening’ that can temporarily strengthen the rock surface the associated weakening of the substrate will lead to quicker erosion after the case-hardened surface would be lost and thus inducing enhanced biological weathering (Viles and Goudie Photoautotrophs assimilate complex molecules out of CO2 using light as an energy source (Rosenberg et al. Ecotoxicology and Environmental SafetyCitation Excerpt :In contrast the secondary colonization is pandered by biogenic input patterns Microbial infestation is not only an issue with façade materials but also with other building materials such as stone Microbial growth on building materials and the associated biodeterioration processes form an emerging research topic (Gaylarde et al. International Biodeterioration and BiodegradationCitation Excerpt :The crusts are typically composed of crystals of gypsum which can entrap atmospheric particulates and encourage the formation of precipitates inorganic precipitates and microorganisms (Whalley et al. The major components have been considered to be non-living but we have found cyanobacterial filaments mixed with neoformed gypsum on the churches of Carmo São Francisco and Gloria in Rio de Janeiro (Fig suggesting that cell metabolism is involved in mineral formation All content on this site: Copyright © 2025 Elsevier B.V., its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply. Volume 8 - 2017 | https://doi.org/10.3389/fpls.2017.02074 Forage production is primarily limited by weather conditions under dryland production systems in Brazilian semi-arid regions therefore sowing at the appropriate time is critical The objectives of this study were to evaluate the CSM-CERES-Pearl Millet model from the DSSAT software suite for its ability to simulate growth and forage accumulation of pearl millet [Pennisetum glaucum (L.) R.] at three Brazilian semi-arid locations and to use the model to study the impact of different sowing dates on pearl millet performance for forage Four pearl millet cultivars were grown during the 2011 rainy season in field experiments conducted at three Brazilian semi-arid locations The genetic coefficients of the four pearl millet cultivars were calibrated for the model and the model performance was evaluated with experimental data The model was run for 14 sowing dates using long-term historical weather data from three locations Results showed that performance of the model was satisfactory as indicated by accurate simulation of crop phenology and forage accumulation against measured data The optimum sowing window varied among locations depending on rainfall patterns although showing the same trend for cultivars within the site The best sowing windows were from 15 April to 15 May for the Bom Conselho location; 12 April to 02 May for Nossa Senhora da Gloria; and 17 April to 25 May for Sao Bento do Una The model can be used as a tool to evaluate the effect of sowing date on forage pearl millet performance in Brazilian semi-arid conditions In Brazil, the semi-arid region comprises 95 million hectares of which only 3% is suitable for irrigation, leaving an immense dryland area to be exploited if sustainable production practices can be identified and implemented (Martins et al., 2003) forage production represents one possible alternative the planting date decision is important not only because of its effect on yield but also the need to minimize the risk of establishment failures and to decrease cost and labor required for replanting dynamic crop simulation model that simulates crop growth The overall goal of this study was to evaluate the performance of the CSM-CERES-Pearl Millet model for simulating growth and forage accumulation of four pearl millet cultivars and to determine optimum sowing dates for pearl millet forage yield under rainfed conditions in three Brazilian semi-arid locations with an average depth of 1.5 m and pH of 6.1 to top soil The climate is typically semi-arid with an annual rainfall of 710 mm and average maximum and minimum temperatures of 32 and 20°C The experiment in Sao Bento do Una (08°31′ S elevation of 614 m) was conducted at an experimental station of the Agronomic Institute of Pernambuco (IPA) where the soil was a sandy loam Eutrophic leptosol with medium texture and pH of 6.6 to top soil The megathermal climate at this site is typically semi-arid with an annual rainfall of 655 mm and average maximum and minimum temperatures of 32.6 and 11.6°C The four cultivars were chosen because of their similar duration to maturity and because they are grown under rainfed conditions The cultivars are already being grown by farmers could easily be promoted for use under water deficit conditions once their performance is established The experiments were conducted under rainfed conditions during the rainy season from May to August 2011 Treatments were the four cultivars replicated five times in a randomized complete block design Plots measured 10.5 m2 (5 m × 2.1 m) with seed sown to a depth of 3 cm in four rows (on 0.70 m centers) At sowing the following fertilization was applied: 30 kg ha-1 nitrogen (as ammonium sulfate) 450 kg ha-1 triple superphosphate and 100 kg ha-1 potassium chloride Two side-dress fertilizations were applied and the second on the 60th day after plant emergence with the dose equivalent to 30 kg ha-1 of nitrogen (as ammonium sulfate) Cultivars were harvested when at least 60% of plants in each plot reached the Zadoks scale of 85, which means that plants were at the dough stage of grain maturity (Zadoks et al., 1974) Harvests were manually at 5 cm stubble height and only the two central rows in each plot were harvested The harvested crop from each plot was collected and weighed to estimate fresh forage accumulation ha-1 After chopping a representative sample from each plot a 400 g sub-sample was oven-dried at 55°C for 48 h to determine dry matter concentration and forage accumulation of the four cultivars The minimum input data set required for DSSAT version 4.6 to simulate crop growth was discussed in detail by Jones et al. (2003) Input data required for the models are crop management information cultivar-specific parameters (genetic coefficients) soil properties and daily weather variables of the study areas Meteorological data during the experimental period for the selected locations The crop data collected in 2011 include phenology dates (sowing and anthesis dates), forage accumulation and its components (separated into leaves, stems, and panicles). The forage accumulation was measured at the dough stage since these cultivars were grown for forage production. Physiological maturity was estimated based in previous publications (Duraes et al., 2003; Pereira Filho et al., 2003) The soil fertility factor (SLPF) was assumed to be 1.0 in all simulations The soil surface evaporation limit (SLU1) was set to 6.0 mm d-1 for all sites Initial soil water content was assumed to be at field capacity in all simulations and full recharge at the time of sowing For N fertilization management simulations where N was applied at planting (30 kg ha-1) and as a sidedressing application before flowering (20 kg ha-1) The three locations have characteristics typical of semi-arid tropical regions a hot and dry climate that is highly limited in its hydrologic resources particularly due to low precipitation and high evaporation rates lasting between 3 and 4 months during the summer and fall and this was the main determinant to sowing window The analysis of the series of 15 years (1997–2011) of weather records for Bom Conselho, showed that the average monthly maximum temperatures were always greater than 26°C, and the average monthly minimum temperatures were always higher than 19.5°C (Figure 1A) The rainfall during the 2011 crop growing season (223 mm) was above the 15-year average (163 mm) and there were more rainy days (44) than the long-term average (24 days) and average solar radiation for Bom Conselho (A) and Sao Bento do Una (C) for 1997–2011 For Nossa Senhora da Gloria, the 15-year average of weather records showed that the highest maximum average temperatures and maximum solar radiation occurred in November (32 and 23°C, respectively) while the highest minimum average temperature occurred in December (22.5°C) (Figure 1B) the highest monthly values were observed between January and June The 2011 growing season in Nossa Senhora da Gloria was characterized by a higher amount of rainfall (257 mm) and rainy days (61) than the 15-year long-term average growing season (102 mm and 27 days) Similarly to Nossa Senhora da Gloria, the Sao Bento do Una weather records showed that the highest maximum average temperatures and maximum solar radiation occurred in November (31 and 24°C, respectively) while the highest minimum average temperature occurred in December (21°C) (Figure 1C) with a maximum precipitation of 121 mm in May The 2011 growing season for Sao Bento do Una showed a similar amount of rainfall as the average for 15 years with a total rainfall of 304 mm from 66 rainy days compared with the 15-year average total precipitation of 298 mm from 43 rainy days The combination of coefficients that resulted in the highest d-Stat and the smallest RMSE between observed and simulated values were selected as the final cultivar coefficients Forage accumulation data were analyzed by a mixed model approach with cultivars and locations as a fixed effect and residual random error using the MIXED procedure of SAS Version 9.1 statistical program (SAS 2002) An analysis of the effect of different sowing dates on forage accumulation of pearl millet was conducted using 15 years of weather records for each site 14 different sowing dates were simulated using the seasonal analysis tool of DSSAT Version 4.6.1 The sowing dates started on 1 January and were repeated every 15 days until 15 July These dates were selected because this period is the regional rainy season which coincides with the growth window for forage crops such maize and sorghum there is a significant variation for regional planting window Assumptions for determining the sowing window were that the opening sowing window was the first date on which 85% of the maximum forage accumulation could be obtained and the closing sowing window was the last date for which 85% of the maximum forage accumulation could be obtained Genetic coefficients of pearl millet cultivars calibrated in DSSAT After calibration, the model was able to predict the number of days from planting to anthesis and forage accumulation for the four pearl millet cultivars grown in all three locations during the 2011 growing season (Tables 3, 4) At the three locations phenology varied among cultivars the period from planting to anthesis ranged from 50 to 56 days Forage accumulation for pearl millet under rainfed conditions at three locations in Brazil as measured and simulated after calibration Anthesis date for pearl millet under rainfed conditions at three locations in Brazil the simulation exactly reproduced the observed days from planting to anthesis for the cultivars IPA Bulk1BF The average observed forage accumulation for the four cultivars was 9850 kg ha-1 and the corresponding average simulated forage yield was 9540 kg ha-1 For Nossa Senhora da Gloria the observed number of days from planting to anthesis ranged from 54 to 56 days while the simulated number of days to anthesis ranged from 51 to 56 days the average observed and simulated forage accumulation values were 12270 and 11990 kg ha-1 For Sao Bento do Una the observed number of days from planting to anthesis ranged from 53 to 55 days while the simulated number of days to anthesis ranged from 56 to 58 days The average observed forage accumulation for the four cultivars for this location was 12650 kg ha-1 while average simulated yield was 13050 kg ha-1 The values of normalized RMSE and d for anthesis ranged from 4.4 to 4.9% and from 0.19 to 0.67 It is important to note that a given set of genetic coefficients for a cultivar were optimized across all three sites the normalized RMSE for yield ranged from 2.6 to 5% and the value for d ranged from 0.94 to 0.98 the model was well-capable of simulating yields across the three sites There was not location effect or location × cultivar interaction The sowing date analysis using 15 years of weather data (1997–2011) for Nossa Senhora da Gloria showed that the best sowing date for millet depends However for Bom Conselho and Sao Bento do Una all pearl millet cultivars had similar trends for the best sowing date On the rising slope of yield versus sowing date, the average slope was 37, 54 and 29 kg ha-1 d-1 during the period prior to the peak yield. The slope of decline after peak yield with delayed sowing was 45, 51 and 58 kg ha-1 d-1, for Bom Conselho, Nossa Senhora da Gloria and Sao Bento do Una, respectively (Figure 2) Simulated pearl millet forage accumulation for different cultivars at different sowing dates for Bom Conselho (A) Individual points represent the four cultivars and planting dates The total simulated transpiration for the entire season had the lowest values for the latest sowing dates and reached a maximum between 1 February and 1 April for all three locations (Figure 3) under water-limited conditions yield is highly correlated with transpiration Total crop transpiration from planting to harvest for different cultivars in different sowing dates for Bom Conselho (A) The coefficient of determination between simulated biomass yield and simulated total transpiration for Bom Conselho, Nossa Senhora da Gloria and Sao Bento do Una was 0.97, 0.93, and 0.97, respectively (Figure 4) Relation between simulated total transpiration and pearl millet forage accumulation for Bom Conselho (A) The length of the optimum sowing window for Bom Conselho was 45 days and was shorter than the other locations the cultivars influenced the period of the optimum sowing window but the duration was 60 days for all cultivars the optimum sowing window commenced on 15 February and ended on 15 April while for BRS 1501 it started on 1 March and ended 1 May Sao Bento do Una showed the longest optimum sowing window The sowing window started on 15 January and finished on 1 April for all cultivars The three semi-arid locations of the present study were characterized by similarity in weather variables the rainfall in Sao Bento do Una was higher and the period of the rainy season was more pronounced than in Bom Conselho and Nossa Senhora da Gloria The evaluated Brazilian pearl millet cultivars exhibited a shorter time from planting to anthesis than for three pearl millet varieties grown in Niger (Soler et al., 2008) Bom Conselho had lower simulated and measured period from planting to anthesis likely because higher temperatures accelerated crop development and shortened the crop growth cycle All of the indices imply that there was a good agreement between simulated and measured duration from sowing to anthesis it can be concluded that the model was very robust in predicting the critical phenological growth stages Several studies on sowing date analysis have shown that models can be useful for this type of evaluation, compared with resource-intensive experiments (Jibrin et al., 2012; Dharmarathna et al., 2014; Andarzian et al., 2015) This study showed that long-term simulated forage accumulation of all cultivars was influenced by sowing date For Bom Conselho a delay in sowing date from 1 January to 15 March the average yield was increased by approximately 4.3% per week a delay in sowing date from 15 March to 15 July resulted in a forage accumulation reduction of about 5.1% per week delaying sowing date from 1 January to 15 March resulted in an increase of 4.9% per week but delaying the sowing date from 15 March to 15 July decreased the forage accumulation in 4.1% per week in Sao Bento do Una for the cultivars IPA Bulk1BF when sowing date was delayed from 1 January to 15 February the forage accumulation increased by 39 kg ha-1 d-1 but delaying from 15 February to 15 July decreased yield by 58 kg ha-1 d-1 For the cultivar BRS 1501 the yield increase was only 19 kg ha-1 d-1 when sowing date was delayed from 1 January to 15 March A delay in sowing date from 15 March to 15 July resulted in forage accumulation decrease of 3.2% per week These results show that forage accumulation is influenced by cumulative intercepted solar radiance and rainfall, since in all locations solar radiation decreased and rainfall increased from January to May. This coincides with the findings of Costa et al. (2005) and Soler et al. (2008) who found that pearl millet biomass yield varies mainly due to photoperiod and water availability the current study showed that the CSM–CERES-Pearl Millet model was able to simulate accurately growth and forage accumulation for four forage pearl millet cultivars grown in three Brazilian semi-arid locations under rainfed conditions The sowing date analysis using 15 years of climate records for Bom Conselho Nossa Senhora da Gloria and Sao Bento do Una indicated that the best sowing dates occur before the normal forage sowing season and the sowing window is longer than recommended by the Brazilian government for these regions This is likely due to the absence of definitive climatic zoning which could reduce the dependence of farmers on their individual perception of climatic factors the results of the simulations confirmed previous field observations of pearl millet responses in this region and showed that crop simulation models can play an important role in identifying best management options for specific environmental conditions simulation models can provide farmers and policy-makers with information about forage production strategies to aid in addressing the food demands of livestock in semi-arid environments performed the statistical analysis of the field trials and drafted the work; KB: designed crop modeling evaluation; LS: provided guidance for crop trial evaluation and interpreted data for the work; AN and LP: established experimental design; CS: performed statistical analysis of the field trials; LG: provided guidance for crop trial evaluation The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest Determining optimum sowing date of wheat using CSM-CERES-wheat model Google Scholar Tolerant pearl millet (Pennisetum glaucum (L.) 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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) distribution or reproduction in other forums is permitted provided the original author(s) or licensor are credited and that the original publication in this journal is cited in accordance with accepted academic practice distribution or reproduction is permitted which does not comply with these terms *Correspondence: Rafael D. Santos, cmFmYWVsLmRhbnRhc0BlbWJyYXBhLmJy Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher 94% of researchers rate our articles as excellent or goodLearn more about the work of our research integrity team to safeguard the quality of each article we publish The URI you submitted has disallowed characters.