Víctor Oscar Sadras

Context: Intercropping can improve resource-use efficiency, yield stability, and profitability, but pulse–pulse intercrops remain poorly studied in mechanised dryland systems. Aims: To determine whether functional complementarity among pulse–pulse and pulse–oilseed crops improves yield, nutrient uptake, phenological risk buffering, and profitability under rainfed conditions. Methods: Field experiments conducted in southern Australia from 2019 to 2024 compared monocultures with pulse–pulse (lentil–faba bean; faba bean–field pea) and oilseed–pulse (canola–field pea, canola–faba bean, linseed–chickpea) intercrops across locations and sowing dates. Key results: Functionally divergent intercrops such as canola–field pea recorded land equivalent ratios (LER) of >1 and nutrient uptake LERs for nitrogen, phosphorus, and sulfur that exceeded unity. By contrast, chickpea–linseed and lentil–faba bean intercrops underperformed with LERs of <1. Faba bean–field pea mixtures yielded similarly to or better than sole crops across environments, with mean LERs near or above 1. Field pea performed better in low-rainfall environments, whereas faba bean performed better in favourable conditions. These complementary responses reflected phenological divergence, with faba bean flowering earlier and field pea maturing sooner. Grain protein concentration remained stable across faba bean–field pea mixtures and was environment-driven. Gross margins were competitive and stable, with some mixtures outperforming monocultures in both yield and profitability. Conclusions: Pulse–pulse intercropping offers a low-barrier diversification strategy for mechanised dryland systems. Functional complementarity underpinned agronomic and economic benefits, with nutrient uptake advantages greatest in functionally distinct oilseed–pulse intercrops. Implications: Intercropping can improve productivity, profitability, and resilience in low-input dryland systems, although benefits depend strongly on species selection and functional contrast.

Concurrent exposure to heat and drought stress compromises legume productivity, yet their combined effects are rarely quantified systematically. We compiled a database of 18 studies covering seven legume species. From these, we extracted 929 physiological, biochemical, and yield-related traits and calculated actual-to-additive ratios to classify heat–drought interactions as antagonistic (ratio < 1), additive (ratio = 1), or synergistic (ratio > 1). Additive heat-drought relationships accounted for 59 % of all classifiable observations, 37% relationships were antagonistic, and 4% synergistic. The relationship varied with species, genotype, trait, and experimental conditions highlighting the complexity of combined abiotic stress effects. The results challenge the common assumption that concurrent stresses invariably exacerbate damage and underscore the need for more realistic, quantitatively defined stress treatments as well as frameworks that integrate trait-level responses into predictive models of crop growth and development. Our synthesis provides a quantitative foundation to understand legume phenotypes under the increasingly frequent co-occurrence of heat and drought stress and identifies research areas where further work is needed to improve insight into combined stress responses. Highlights: Combined heat and drought responses were mainly additive or antagonistic. Evidence is biased toward few legumes and controlled environments. Field-based, multi-species studies are needed to identify adaptive traits.

In the context of advocacy for yield stability, trade-offs between yield and yield stability, the frequent lack of definitions, and the variation in methods when they are explicit, this essay connects two perspectives: phenotypic plasticity and factor analytics. Phenotypic plasticity brings over a century of research in developmental biology, ecology and evolution, and is gaining traction in crop science. Factor analytics is an advanced linear mixed model of multi-environment data with factor analytic variance structures for the genotype-by-environment interaction effect. We (1) review phenotypic plasticity, define agronomically adaptive plasticity where varieties (or practices) consistently return superior yield (or other traits) across environments with no trade-off, and describe percentile-plasticity plots to assess the agronomic value of plasticity; (2) outline factor analytic models, and (3) link phenotypic plasticity and factor analytic models mathematically and empirically. We show that phenotypic plasticity of cereal yield correlates positively with overall performance obtained from factor analytic models when plasticity is adaptive and negatively when it is maladaptive. We conclude that phenotypic plasticity contributes biological meaning to opaque analytical approaches, and that biologically grounded statistics are needed to challenge weak agronomic narratives, such as advocacy for stability that might reflect decision biases rather than critical consideration of its benefits.

Within-field yield heterogeneity is common in maize production systems, yet its economic relevance at the field scale remains insufficiently quantified, particularly under conditions where productivity zones are delineated and managed differentially. While yield difference between zones are often used to justify site-specific management, their economic implications may depend not only on their magnitude but also on environmental productivity and production system. In this study, we evaluated how yield differences between contrasting productivity zones influence field-level gross margin and profitability using commercial fields with delineated zones managed under differential input strategies. We accounted for both the relative area of each zone and environmental productivity, and compared responses in early- and the late-sown system. We also assessed whether economic gains arise from capturing high-yield opportunities or reducing input use in low-productivity zones. Grain yield was, on average, 29% higher in high- than in low-productivity zones, but economic differences were smaller and less consistent. Across systems, gross margin and profitability increased strongly with the yield-environment index (defined as the yield of the high-productivity zone in each field–season), and were weakly correlated with difference in yield between zones. Yield-related factors accounted for 89-96% of the variation in economic outcomes, whereas cost-related factors contributed marginally. The proportion of area occupied by contrasting zones had minor or inconsistent effects. We conclude that, in our systems, environmental productivity is the economic relevance of spatial yield heterogeneity is primarily driven by rather than on yield differences or spatial configuration alone. Economic gains were mainly associated with capturing yield potential in high-productivity zones rather than reducing input use in low-productivity areas. This study provides an empirical framework to support decision-making in precision agriculture.

Delayed sowing can reduce winter wheat ( Triticum aestivum L.) yield and increasing seeding rate is commonly proposed to compensate for some of the negative effects, but tillering plasticity, shortening of critical period, and environmental conditions make the yield response uncertain. We analyzed worldwide published data from 40 experiments that factorially combined sowing dates and seeding rates to (i) evaluate whether the relationship between seeding rate and delayed sowing in winter wheat was additive, synergistic, or antagonistic and (ii) evaluate the impact of sowing date on the critical seeding rate, that is, the rate to achieve 95% of peak yield. The compiled database contained 658 mean yields from 0.3 to 10.5 Mg ha ⁻¹ . The relationships between sowing date and seeding rate were classified as either positive or negative additive, antagonistic, or synergistic. Out of 169 sowing date × seeding rate relationships, 40% were negative additive and 25% were negative antagonistic, independent of the yielding environment. Negative additivity suggests that in many environments, the usual seeding rate was already close to or above the critical seeding rate required to maximize yield at delayed sowing. Negative antagonistic relationships indicate that higher seeding rates partially compensated for the yield reduction with late sowing. The remaining relationships were mostly positive additive or antagonistic, with synergistic effects being rare. Michaelis–Menten models were fitted to estimate critical seeding rate, which increased from 292 seeds m ⁻² under the usual sowing date to 463 seeds m ⁻² for ≥30‐day sowing delay. In environments where yield was reduced due late sowing, higher seeding rates partially offset yield losses. Our results reinforce that site‐specific seeding rate recommendations should account for the time of sowing.

Pulse-pulse intercrops have been largely unexplored. We evaluated rainfed intercrops in southern Australia to test whether functional complementarity between pulses and between oil-seeds and pulses can improve phenological risk buffering and system-level yield and nutrient use efficiency. Experiments conducted from 2019 to 2024 compared monocultures with intercrops including pulse-pulse (lentil–faba bean; faba bean–field pea) and oilseed-pulse (canola–field pea, canola–faba bean, linseed-chickpea) across locations and sowing dates.Functionally divergent intercrops such as canola–field pea often recorded land equivalent ratios (LER) > 1, supported by positive partial LER and nutrient uptake advantages. Nutrient uptake LER for nitrogen, phosphorus and sulfur frequently exceeded unity in canola–pulse intercrops, indicating improved resource capture beyond yield advantages, whereas pulse–pulse intercrops rarely exceeded 1, suggesting limited facilitation. In contrast, combinations of species with less compatible growth habits and resource use—such as chickpea–linseed and lentil–faba bean—frequently underperformed, with LER < 1 and evidence of mutual suppression. Mixtures of species with more compatible growth habit, faba bean–field pea, yielded similarly to or better than sole crops in several environments, with mean LER near or slightly above 1. Field pea dominated yield in intercrop mixes in low-rainfall environments; faba bean performed better in favourable conditions. These complementary yield responses reflected phenological divergence—faba bean flowered earlier, field pea matured sooner—distributing exposure to frost, heat and terminal drought. Grain protein concentration remained stable across faba bean–field pea mixtures and was primarily environment-driven. Yield and its component were orthogonal to phenology, highlighting independence between yield and development across environments. Gross margins for faba bean–field pea mixtures were competitive with sole crops and stable across environments, with some configurations outperforming monocultures in both yield and profitability. We conclude that pulse–pulse intercropping offers a low-barrier diversification strategy for mechanised dryland systems. Functional complementarity improved agronomic and economic performance in variable, low-input environments, whereas higher pulse productivity reduced subsequent wheat yield, indicating a trade-off between pulse and cereal performance in diversified rotations.

Summary: Growth rate, a fundamental trait associated with plant resource use, scales with plant mass, following consistent allometric power laws shaped by biophysical constraints and natural selection captured in metabolic scaling theory (MST). Although well‐established in wild plants, MST has been overlooked in crop improvement. We quantified the relationship between individual plant mass and growth rate in 195 European winter wheat cultivars under glasshouse conditions and examined how variation in growth allometry relates to stand‐level grain yield across eight field environments and to its underlying genetic, developmental, and physiological mechanisms. Variation in allometry was linked to plant size, in which increased leaf allocation and faster development elevated allometric exponents. Phenotypic and genetic analyses revealed adaptive strategies, ranging from large, slow‐developing genotypes that support reproductive initiation to small, fast‐developing genotypes that enhance floret survival and reproductive effort. A shared genetic basis associated with Photoperiod‐1 linked growth allometry in the glasshouse to genotype‐by‐environment interactions for grain yield in the field. Our findings demonstrate that growth allometry is biologically robust and agronomically relevant. While phenology is associated with adaptive variation in allometry, the allometric framework integrates developmental and physiological processes that jointly shape cultivar performance across environments, providing a basis for environment‐specific crop improvement.

Plants in typical agricultural stands inevitably experience mutual shading. As the canopy develops, neighbor cues progressively reduce the activity of photo-sensory receptors, de-repressing shade-avoidance responses (SARs) that drastically reshape plant architecture. This review synthesizes recent molecular advances in understanding the signaling mechanisms underlying SARs. We specifically delve into the photoreceptors, the complex transcriptional networks they regulate, and the signaling molecules that operate downstream or in parallel. A central focus is the dynamic features of the SAR network, which drive signal amplification initiated by brief interruptions of shade from direct sunlight, and the epigenetic memory that allows plants to recall and respond to previous shade events. Recent progress also reveals key similarities and differences in SAR mechanisms between Arabidopsis and major crop species. Ultimately, we consolidate information demonstrating that SARs can be either beneficial or detrimental to crop productivity, depending on the genetic material, environmental context, and specific management practices.