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The challenge to increase agricultural production with a minimum environmental impact requires to reach the maximum efficiency in the capture and use of resources such as photosynthetically active radiation (PAR), water, and nitrogen (N). Such requisites are encompassed in the ecological intensification (EI) concept. The aims of this work were to evaluate at a crop sequence level: i) crops yields, ii) water and radiation productivity and its components, i.e. resource capture and resource use efficiency, and iii) partial factor productivity of applied N (PFPN), partial nutrient balance for N (PNB), N uptake and N utilization efficiency of a two-year, three-crop sequence (wheat [Triticum aestivum L.]/soybean [Glycine max (L.) Merr.] double crop – maize [Zea mays L.]) carried-out under EI principles in comparison with the same crop sequence under current farmer practices (FP) in two contrasting locations of the Argentinean Pampas, i.e. Paraná (-31°50′; -60°31′) at the northern Pampas and Balcarce (-37°45′ -58°18′) at the southern Pampas. Experiments were carried-out during four consecutive years, covering two complete cycles of the crop sequence. For the accumulated grain production of the crop sequence, EI management outyielded FP from 13 to 42%, depending on environmental conditions. Maize yield accounted for most of the variation (41–64%) of the accumulated grain yield of crop sequence, whether in EI as in FP. Average grain yield differences between EI and FP treatments were 274 g m −2 for maize, 69 g m −2 for wheat and -2 g m −2 for soybean. Water and radiation productivities of the sequence were higher in EI than in FP (26% for water and 17% for radiation; P < 0.0001), mainly because of increases in resource use efficiencies. EI reduced partial factor productivity of applied N, but improved partial nutrient balance for N as compared with FP. These reductions in partial factor productivity of applied N were less than proportional than the increases in N rate. Moreover, in spite of the higher N rate in EI respect to FP, N utilization efficiency (N ut E), i.e. grain per unit N uptake, was higher across all situations in EI. Our results showed that the challenge to obtain high grain yields by increasing N rate in a medium-input system could be achieved even with an increase in N ut E. Grain yields improvements, and increases in radiation and water productivity were reached by applying a set of agronomic practices that included improved genetics, crop and fertilizer N management englobed under EI concept. Fil: Caviglia, Octavio Pedro. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina. Universidad Nacional de Entre Ríos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Rizzalli, Roberto Héctor. Universidad Nacional de Mar del Plata; Argentina Fil: Monzon, Juan Pablo. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Garcia, Fernando Oscar. Universidad Nacional de Mar del Plata; Argentina. International Plant Nutrition Institute Latinoamérica; Argentina Fil: Melchiori, Ricardo José Miguel. Instituto Nacional de Tecnología Agropecuaria; Argentina Fil: Martinez, J.J.. Instituto Nacional de Tecnología Agropecuaria; Argentina Fil: Cerrudo, Anibal Alejandro. Instituto Nacional de Tecnología Agropecuaria; Argentina. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Irigoyen, Andrea Inés. Universidad Nacional de Mar del Plata; Argentina Fil: Barbieri, Pablo Andres. Universidad Nacional de Mar del Plata; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Van Opstal, Natalia. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina Fil: Andrade, Fernando Héctor. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina

Soybean is the main rainfed crop in a wide range of latitudes and sowing dates of the Argentine Pampas. It is sown alone or as a second crop after other winter and summer crops. Modelling approaches have proved to be helpful in the decision making process. The on-farm evaluation of CROPGRO is rather difficult since input data are scarce and frequently of worse quality than those from experimental works. Moreover, CROPGRO simulation of water dynamic processes and their relation with biomass production has not been comprehensively evaluated in soybean crops. The aims of this study were (i) to evaluate the CROPGRO-soybean performance, with emphasis on water demand and supply and biomass production under water limited conditions, (ii) to generate a revised CROPGRO model improving those aspects, and (iii) to compare simulations outputs using the original and the revised CROPGRO models, with on-farm crop data set. In the revised model, we multiplied potential evapotranspiration by 1–1.22 when LAI increased from 0 to ≥4.0. We set a root extension rate of 4.0 cm/thermal day and a maximum rooting depth of 2.5 m. Finally, we included a nonlinear equation to simulate the relationship between relative transpiration and relative gross photosynthesis. The ability of the revised CROPGRO-soybean to simulate water content depletion and biomass production was tested against several experiments with an imposed drought period. We also calibrated cultivar parameters using “ad hoc” tests in a range of environments (combinations of sowing dates and locations). The models were evaluated with data from 155 commercial farms. V (%) (root mean square error as percentage of the observed mean) for the total cycle length, vegetative period, and reproductive phase simulations were 7, 13 and 15%, respectively. The revised CROPGRO was more accurate in simulating crop yield, biomass, harvest index and yield numeric components. V (%) values ranged from 11 to 17% (revised version) and from 13 to 22% (original version). Besides, V (%) values for yield were 16% with the revised model versus 32% with the original one, considering only paddocks with higher water stress level. The robust prediction of phenology, biomass and yield components obtained with the revised model across different environmental conditions, support its use in the decision making process of the soybean crop at the farm scale.