Jose A. Terra

Rice is a staple crop relevant to present and future human feeding. However, these agroecosystems significantly contribute to greenhouse gas methane emissions. In Uruguay, a traditional low-intensity, reduced-tillage rice system alternates annual rice crops with pastures for livestock. We hypothesize that rice crop intensification impacts aerobic methanotrophic communities associated with rice roots, which are crucial in mitigating methane emissions. The pmoA gene abundance, methane oxidation potential (MOP), and methanotrophic community composition by 16S rRNA gene Illumina MiSeq (V4 region) allowed us to determine the dynamics of these communities in bulk and rhizospheric soils from continuous rice (CR) and rice-pastures (RP) rotations throughout the crop cycle. Results showed that rice crop intensification significantly affected MOP and pmoA abundance in both compartments. The tillering stage showed the greatest pmoA abundance and MOP. Rhizospheric methanotrophic communities from the CR and RP systems at flowering differed greatly. While Methylocystis dominated rhizospheric CR soil, Methylocella predominated in those from RP rotation. Active rhizospheric methanotrophic communities at flowering detected by 13CH4 DNA-SIP were dominated by distinct Methylocystis-affiliated ASVs in both cropping systems. However, other active genera were differentially enriched in the two contrasting cropping systems. These results suggest aerobic methanotrophs could be a microbial guild sensitive to crop intensification.

Understanding the long‐term impacts of crop rotation systems on rice ( Oryza sativa L.) yield and stability is key to redesigning agroecosystems, optimizing management, and refining sustainable intensification strategies. This study evaluated the impacts of the rotation system and the previous crops on irrigated rice yield and its stability over 9 years, using an RCB design experiment in Uruguay. Rotations were (1) Rice1‐Rice2‐Perennial Pasture (R‐PP); (2) Rice‐Biannual Pasture (R‐BP); (3) Rice1‐Soybean1‐Soybean2‐Rice2‐Perennial Pasture (R‐Sy‐PP); (4) Rice1‐Soybean‐Rice2‐Sorghum (R‐Crops); (5) Rice‐Soybean (R‐Sy); and (6) continuous rice (CR), all with winter cover crops between grain crops. The highest yields were obtained in rotations including soybean (R‐Sy, R‐Sy‐PP, R‐Crops: 11.03 Mg ha ⁻¹ ), which were 7% and 15% higher than those including only pastures (R‐BP and R‐PP) and CR, respectively. However, the highest effect on yield and yield stability was observed by previous crops. Independently of rotation, rice following soybean had the greatest productivity (11.33 Mg ha ⁻¹ ), followed by rice after pastures (10.60 Mg ha ⁻¹ ), and rice after rice (9.46 Mg ha ⁻¹ ). These differences were amplified in high‐yielding years, with rice after soybean (12.72 Mg ha ⁻¹ ) yielding 5%, 17%, and 22% more than after perennial pastures, biannual pastures, and rice, respectively. Soybean as a previous crop increased rice yield in all rotations but decreased yield stability as demonstrated by an environmental index combining four parameters. For rice‐pasture systems in temperate climates, rotation intensification integrating soybean offers a viable strategy for increasing rice productivity, particularly in high‐yielding years, despite lower yield stability.

Se evaluó el estado estructural del suelo en distintos sistemas agrícolas y agrícola-pastoriles mediante la metodología del Perfil Cultural. Se consideraron las estructuras de origen antrópico relacionadas al uso y manejo del suelo y a la actividad biológica en el perfil. La evaluación abarcó la proporción de dichas estructuras y sus características principales, así como la descripción del origen de los macroporos generados por raíces y fauna. Al mismo tiempo, se midió la resistencia al corte para cada estructura, la densidad aparente y las porosidades estructural y textural. Los resultados mostraron diferencias significativas entre los sistemas con pasturas y aquellos con cultivos continuos. En los primeros predominó la macroporosidad atribuida a la actividad biológica, mientras que en cultivos continuos se relacionó mayormente con procesos físicos de expansión y contracción. Las estructuras más cohesionadas y con menor porosidad estuvieron presentes en todos los tratamientos, probablemente relacionadas con el tráfico de maquinaria. Los sistemas con pasturas revelaron mayor generación de porosidad biológica en suelos con estructuras altamente cohesivas, con formación de poros redondeados y galerías con excrementos, mientras que en suelos agrícolas continuos surgió una estructura laminar incipiente. La resistencia al corte evidenció variaciones significativas entre estructuras, mostrando alta dependencia del contenido hídrico. Finalmente, el sistema radicular fue más desarrollado en sistemas pastoriles, en contraste con una mayor densidad aparente en cultivos continuos.

One of the main objectives of agronomic experimentation is to obtain reliable data to establish comparisons between treatments and test working hypotheses. To meet this objective, it is essential to have well-designed and planned experiments, as well as a data analysis strategy that takes into account the design factors and additional relevant information, mainly in large field scale trials evaluated for several years which generate correlations in space and/or time. The purpose of this research was to evaluate the efficiency of experimental designs with different degrees of complexity and the adjustment of spatial, temporal and spatio-temporal models in experiments with different crops, seeking to avoid biases in the variance estimates, and an adequate control of the empirical type 1 error rate. The most relevant results of this work show that with high experimental field heterogeneity and large experiment size, the choice of the experimental design becomes essential to obtain accurate and precise treatment effect estimates. Once the appropriate experimental design has been chosen, spatial modeling of the correlation between experimental units further improves the design performance. These improvements can be accompanied by unbiased standard errors and a correct control of the type 1 empirical error rate if the model used to estimate the spatial correlation of the response variable is adequate. Additionally, with high number of replicates, reliable results can be obtained beyond the preferred spatial model. On the other hand, when intra-plot spatial correlations are included, the advantage of spatial modeling is not as clear. In the case of forest tillage experiments, the inclusion of spatial correlation between trees in the same plot increased the precision of comparisons between treatment means, achieving reductions in the standard error of the mean difference of up to 40 %. However, in trials conducted on permanent grasslands with large plot sizes, the advantages were not clear. These differences between trials may be due to the scale at which these spatial correlations are manifested, the number of subsamples per plot and the effect of treatments on the spatial distribution of the variables of interest.

Rice (Oryza sativa L.) systems rotated with perennial pastures have intensified in South America to increase annual grain productivity, but the effects on rice yield and soil quality remain poorly understood. We evaluated rice grain yield, crop and pasture biomass production, and soil organic carbon (SOC) and total nitrogen stocks (0–15‐cm depth) in three rice‐based rotations over 8 yr in Uruguay. Treatments were: (a) rice–pasture [a 5 yr rotation of rice–ryegrass (Lolium multiflorum Lam.)–rice, then 3.5 yr of a perennial mixture of tall fescue (Festuca arundinacea Schreb.), white clover (Trifolium repens L.), and birdsfoot trefoil (Lotus corniculatus L.)], (b) rice–soybean [a 2‐yr rotation of rice–ryegrass–soybean (Glycine max [L.] Merr.)–Egyptian clover (Trifolium alexandrinum L.)], and (c) rice–cover crop (an annual rotation of rice–Egyptian clover). Rice after soybean or pasture achieved the highest yield (9.8 Mg ha^–1), 9% higher than rice after rice in the rice–pasture and rice–cover crop systems. Estimated belowground biomass under rice–pasture (2.7 Mg ha^–1) was 12 and 42% greater than under rice–cover crop and rice–soybean rotations, respectively. Rice–pasture showed an increase of 0.6 Mg ha^–1 yr^–1 of SOC; no changes were observed in the intensified rotations replacing pasture with additional rice or soybean. All systems sustained soil total N. These results provide insights for implementing sustainable rice‐based rotations, with rice–pasture being the only system that increased SOC while achieving high rice yields and belowground biomass productivity.