High-yielding Environments Research Articles

Winter Wheat Experiments to Optimize Sowing Dates and Densities in a High-Yielding Environment in New Zealand: Field Experiments and AgMIP-Wheat Multi-Model Simulations

This paper describes the data set that was used to test the accuracy of twenty-nine crop models in simulating the effect of changing sowing dates and sowing densities on wheat productivity for a high-yielding environment in New Zealand. The data includes one winter wheat cultivar (Wakanui) grown during six consecutive years, from 2012-2013 to 2017-2018, at two farms located in Leeston and Wakanui in Canterbury, New Zealand. The simulations were carried out in the framework of the Agricultural Model Intercomparison and Improvement Project for wheat (AgMIP-Wheat). Data include local daily weather data, soil profile characteristics and initial conditions, crop measurements at maturity (grain, stem, chaff and leaf dry weight, ear number and grain number, grain unit dry weight), and at stem elongation and anthesis (total above ground dry biomass, leaf number per stem and leaf area index). Several in-season measurements of the normalized difference vegetation index (NDVI) and the fraction of intercepted photosynthetically active radiation (FIPAR) are also available. The crop model simulations include both daily in-season and end-of-season results from twenty-nine wheat models.

Soybean seed yield, protein, and oil concentration for a modern and old genotype under varying row spacings

Progress in soybean (Glycine max L.) breeding has led to a reduction in optimal seeding rates due to enhanced branching capacity over time. However, less is known about the changes in canopy architecture between old and modern soybean genotypes at varying row spacing and their impact on yield and seed quality through the main stem and branches. Therefore, this study aimed to i) evaluate yield and seed quality responses of an old and modern soybean genotype at different row spacings and ii) examine the yield and seed quality of branches and the main stem. Trials were conducted in Kansas (United States, US) during 2020 and 2021, comparing two genotypes (old, released in 1980, and modern, released in 2013) at four row spacings (0.19, 0.38, 0.76, and 1.52 m) under rainfed conditions. Seed yield and quality (protein and oil concentrations, %) were assessed at the end of each growing season. In 2021, both genotypes had low and similar yields at all row spacings (averaging 2481 kg ha−1) with 2.5 % less protein on branches compared to the main stem. However, 2022 resulted in a high-yielding environment, with the modern yielding 50 % more (3584 kg ha−1) than the old (2315 kg ha−1) genotype in narrow row spacings (<0.38 m). Additionally, the modern genotype showed a three-fold greater contribution to yield from branches (1113 kg ha−1) relative to the old genotype (379 kg ha−1). Despite the high yields observed in narrow rows, the modern genotype maintained protein levels. These results highlight the importance of row spacing as a key management practice for improving yield while maintaining protein levels in high yield conditions.

Comparative analysis of wheat and barley yield performance across temperate environments

ContextA comparative analysis of grain yield performance of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) under different environments constitutes a way to identify restrictions in yield formation between both crop species. However, most of the previous studies on these field crops have been carried out in Mediterranean environments. ObjectiveThis study aims to compare the grain yield performance of wheat and barley across a wide range of temperate environmental conditions. MethodsWheat and barley yield databases from the national network of cultivar evaluation of Argentina were assembled. The database included 191 wheat cultivars (with early-, mid- and late-flowering length cycle), 140 barley cultivars, and 44 combinations of sites and years of the Argentine wheat and barley belt region. Average heading date variation among environments and crops was no more than 10 days. Crop grain yield comparisons were carried out using a regression analysis, benchmarking within each site-year the grain yield of each cultivar against the average grain yield of all crop cultivars (i.e., environmental index). ResultsThere were no differences in grain yield between wheat and barley for all data, but the behavior between crop species changed with the length of the wheat cycle (i.e., early-, mid-, or late-flowering cultivars). Barley portrayed a greater grain yield than early-flowering wheat under low-yielding environments (< 6060 kg ha−1), but this advantage vanished as the yield environment improved. Mid-flowering wheat showed a similar grain yield to barley across temperate environments. Lastly, late-flowering wheat outperformed barley mainly in high-yielding environments (> 6138 kg ha−1). Grain number m−2 was the main numerical component that explained variability in grain yield. The relative contribution of the yield numerical components differed between species, having barley lower grain number m−2 but a greater grain weight than wheat. ConclusionsThe comparison of the grain yield performance between species represents a strategy to adjust the rotation system, being a critical factor in considering the variability in the crop growth cycle.

Effect of Fungicide and Timing of Application on Management of Phoma Black Stem of Cultivated Sunflowers in the United States.

Phoma black stem (PBS), caused by Phoma macdonaldii Boerema (teleomorph Leptosphaeria lindquistii Frezzi), is the most common stem disease of sunflower (Helianthus annuus L.) in the northern Great Plains region of the United States. However, the impact of PBS on sunflower yield in the United States is unclear, and a near complete absence of information on the impact of fungicides on disease management exists. The objectives of this study were to determine the impact of PBS on sunflower yield, the efficacy of available fungicides, the optimal fungicide application timing, and the economic viability of fungicides as a management tool. Fungicide timing efficacy was evaluated by applying single and/or sequential applications of pyraclostrobin fungicide at three sunflower growth stages in 10 field trials between 2017 and 2019. Efficacy of 10 fungicides from the Fungicide Resistance Action Committee (FRAC) groups 3, 7, and 11 were evaluated in four field trials between 2018 and 2019. The impact of treatments on PBS were evaluated by determination of incidence, severity, maximum lesion height, disease severity index (DSI), and harvested yield. Nine of the 10 fungicides evaluated and all fungicide timings that included an early bud application resulted in disease reductions when compared with the nontreated controls. The DSI was negatively correlated to sunflower yield in high-yield environments (P = 0.0004; R2 = 0.3425) but not in low- or moderate-yield environments. Although FRAC 7 fungicides were generally most efficacious, the sufficient efficacy and lower cost of FRAC 11 fungicides make them more economically viable in high-yielding environments at current market conditions.

Cultivar-specific phenotypic plasticity of yield and grain protein concentration in response to nitrogen in winter wheat

ContextOwing to the interaction between genotype and environment (G x E), identifying traits to increase wheat yield and grain protein concentration simultaneously or increasing one without affecting the other remains a challenge. Phenotypic plasticity is an insightful perspective to understand G x E. ObjectiveTo explore the relations of wheat yield and grain protein concentration in response to N input and its physiological basis from the perspective of phenotypic plasticity. MethodWe established a factorial experiment combining 14 winter wheat cultivars and four N fertilization rates (0, 45, 90 and 135 kg ha−1) in eight environments. We analyzed the interaction of cultivar and N combining a phenotypic plasticity framework and a three-phase model of grain yield and protein response to N input. The phases are: phase I, N supply limits both yield and grain protein; phase II, N supply limits grain protein but not yield; and phase III, N supply does not limit yield or grain protein concentration ResultsGrain yield plasticity was positively associated to yield in high-yielding environments without N limitations (phase II) with no cost in low yielding environments, and associated to harvest index. Grain protein plasticity was positively associated to protein in high protein environments without N limitations (phase III). Plasticity of grain protein concentration was negatively associated to grain number m −2, resulting in moderate negative association of protein plasticity and yield. Grain C:N ratio associated weakly and positively with yield plasticity and strongly and negatively for grain protein plasticity. ConclusionThis work proposes a yield-protein plasticity framework combined with a three-phase model that allows to disclose G × N interactions. Under our experimental conditions, we identified physiological mechanisms associated to yield and protein plasticity. ImplicationsYield and protein plasticity can contribute guiding grower’s cultivar selection towards high yield plasticity cultivars when aiming to high yield with acceptable protein levels or high protein plasticity cultivars to ensure high protein at the expense of lower yields. Yield plasticity brings opportunity to breed for high yielding cultivars while maintaining grain protein concentration. Accuracy of N recommendations models and mechanistic crop models can be improved by accounting for G × N interactions through plasticity of yield and grain protein.

Genetic gain of grain yield and quality in bread wheat cultivars representing 40 years of breeding in Morocco

Background. Knowledge about the genetic gain for fundamental traits over time is essential for a critical assessment and improvement of breeding programs, especially regarding staple crops like bread wheat.Materials and methods. To estimate the genetic gain in bread wheat breeding in Morocco, grain yield (GY) and grain protein content (GPC) data were collected from 12 multi-environment field trials for 20 bread wheat cultivars released between 1980 and 2022.Results and discussion. Analysis of variance highlighted a high significant variability between environments (E), cultivars (G), and a significant G × E interaction (P &lt; 0.001). Based on stability analysis, the modern cultivars released during the two last decades (2002–2012 and 2013–2022) showed the highest performances and wider stability than old ones, especially in low-yielding environments. Genetic gain (GG) for GY was 21.4 kg ha−1 yr−1 (0.75% yr–1) over 4 decades of breeding. This progress was declining when advancing in decades and ranged from 11% (from 1980–1990 to 1991–2001) to less than 7% (from 2002–2012 to 2013–2022). The GG in low and intermediate yielding environments were the most important (17.34% and 6.88% yr–1 respectively), while GG was nonsignificant in high-yielding environments (4.62% yr–1). Within the same period, GPC showed a nonsignificant negative trend of –0.007% (–0.002% yr–1), while derivative parameters from GY and GPC indicated high positive genetic progress. More efforts should be deployed to implement a good balance between yield performance and quality in the new released cultivars despite the negative correlation between these two traits (r = –0.36; P &lt; 0.001).Conclusion. Adopting advanced technologies, like genomic selection, adequate agronomic practices, and more efficient selection criteria are essential steps to further increase simultaneously grain yield and quality traits.

Continuous winter wheat response to nitrogen fertilizer rate in long‐term reduced tillage semi‐arid variable yield environments

AbstractReduced tillage (RT) increased soil water storage compared with conventional tillage, enabling an associated increase in crop performance. However, information on nitrogen (N) fertilizer rates for RT systems is limited. The objectives of this long‐term study were to determine agronomic and economical optimal N rates for a continuous winter wheat (Triticum aestivum L.) system under RT at different yield environments. This study was conducted at Kansas State University Agricultural Research Center near Hays, KS, from 1971 through 2003. There were six N fertilizer rate treatments (0, 22, 45, 67, 90, and 112 kg N ha−1) arranged in a randomized complete block design with six replications. Over the 33 years, winter wheat yields ranged from a minimum of 370 kg ha−1 to a maximum of 3948 kg ha−1 with mean yield of 2015 kg ha−1 and standard deviation of 669 kg ha−1. Agronomic optimal N rates for wheat varied from 70 in very low yield (VLY) to 79 kg N ha−1 in very high yield (VHY) environment. The economic optimal N rates estimated for continuous wheat ranged from 59 in VLY to 71 kg N ha−1 in VHY environments. However, net profits from fertilizer application ranged from $63 in VLY to $443 ha−1 in VHY environment. We concluded that applying 60–70 kg N ha−1 would optimize dryland continuous RT wheat yields and profitability, but N removal and recovery efficiency (grain N [applied N]−1) are less in lower yielding environments.

Tillage and nitrogen rate effects on winter wheat yield in a wheat–sorghum rotation

The objectives of this study were to quantify long-term tillage practice and nitrogen (N) fertilizer rate effects on yield and N use in a winter wheat ( Triticum aestivum L.)–grain sorghum ( Sorghum bicolor L. Moench)–fallow (W–S–F) rotation. The experimental design was a randomized complete block with a split–split-plot arrangement. The main plot treatments were crop rotation phases W–S–F, S–F–W, and F–W–S. The sub-plots were tillage practices, i.e., conventional tillage (CT), reduced tillage (RT), and no-tillage (NT). And the sub-sub-plot treatments were N rates of 0, 45, 90, and 134 kg ha−1. Wheat yield increased at rates of 15.6, 9.3, 22.8, and 25.7 kg ha−1 for a kg N ha−1 increase in very low-, low-, high-, and very high-yielding environments (average yields of ∼2000, 2500, 2800, and 4400 kg ha−1), respectively. On average, winter wheat yields were 7%–9% greater for CT compared with both NT and RT. Winter wheat removed about 52 kg N ha−1 from the unfertilized control treatment, but N uptake varied by N rate and growing conditions. Nitrogen use efficiency, N agronomic efficiency, and applied N recovery decreased as the N rate increased. Across environments, wheat yield increased by 16, 20, and 17 kg ha−1 for each additional kg ha−1 N applied under CT, NT, and RT, respectively, and additional 2–2.5 kg ha−1 yield increases for a mm increase in fallow precipitation. We concluded that wheat yield response to N is highly dependent on growing conditions, and NT required greater N fertilization than CT and RT for similar yields.

A high-yielding traits experiment for modeling potential production of wheat: field experiments and AgMIP-Wheat multi-model simulations

Grain production must increase by 60% in the next four decades to keep up with the expected population growth and food demand. A significant part of this increase must come from the improvement of staple crop grain yield potential. Crop growth simulation models combined with field experiments and crop physiology are powerful tools to quantify the impact of traits and trait combinations on grain yield potential which helps to guide breeding towards the most effective traits and trait combinations for future wheat crosses. The dataset reported here was created to analyze the value of physiological traits identified by the International Wheat Yield Partnership (IWYP) to improve wheat potential in high-yielding environments. This dataset consists of 11 growing seasons at three high-yielding locations in Buenos Aires (Argentina), Ciudad Obregon (Mexico), and Valdivia (Chile) with the spring wheat cultivar Bacanora and a high-yielding genotype selected from a doubled haploid (DH) population developed from the cross between the Bacanora and Weebil cultivars from the International Maize and Wheat Improvement Center (CIMMYT). This dataset was used in the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 to evaluate crop model performance when simulating high-yielding physiological traits and to determine the potential production of wheat using an ensemble of 29 wheat crop models. The field trials were managed for non-stress conditions with full irrigation, fertilizer application, and without biotic stress. Data include local daily weather, soil characteristics and initial soil conditions, cultivar information, and crop measurements (anthesis and maturity dates, total above-ground biomass, final grain yield, yield components, and photosynthetically active radiation interception). Simulations include both daily in-season and end-of-season results for 25 crop variables simulated by 29 wheat crop models.

Effect of nitrogen management on grain yield of rice grown in a high-yielding environment under flooded and non-flooded conditions

With increased cost and scarcity of irrigation water, flooded rice growing system may need to be replaced with water-saving technologies which includes part or complete removal of flooding and to be replaced with non-flooded aerobic conditions. However, to maintain high grain yield equivalent to that achieved with flooded rice, nitrogen (N) management may need to be modified. Experiments were conducted in a high-yielding environment with total N applied up to 180 ​kg ​ha−1 and three application times to determine its effect on N uptake, grain yield and grain protein content of rice grown under aerobic (AR), delayed permanent water (DPW) and flooded (FD) conditions. Grain yield increased by 3.50–4.50 ​t ha−1 with total N application rate of 180 ​kg ​ha−1 in AR and 120 ​kg ​ha−1 in both DPW and FD. Maximum yield was about 10.5, 12.0 and 13.0 ​t ​ha−1 in AR, DPW and FD, respectively, and the difference was mostly reflected in the grain yield difference obtained under 0 N application. Apparent recovery of fertilised N and agronomic N use efficiency were similar between AR and FD, but DPW took up a higher proportion of N fertiliser applied before commencement of flooding and had slightly higher grain yield response to total N application up to 120 ​kg ​ha−1. It is concluded that the limitation for grain yield for rice grown in the AR condition was the crop's inability to take up N from the soil, rather than the inability to take up N fertiliser or to convert the N uptake to grain yield.

Corn yield components can be stabilized via tillering in sub-optimal plant densities.

Crop plasticity is fundamental to sustainability discussions in production agriculture. Modern corn (Zea mays L.) genetics can compensate yield determinants to a small degree, but plasticity mechanisms have been masked by breeder selection and plant density management preferences. While tillers are a well-known source of plasticity in cereal crops, the functional trade-offs of tiller expression to the hierarchical yield formation process in corn are unknown. This investigation aimed to further dissect the consequences of tiller expression on corn yield component determination and plasticity in a range of environments from two plant fraction perspectives - i) main stalks only, considering potential functional trade-offs due to tiller expression; and ii) comprehensive (main stalk plus tillers). This multi-seasonal study considered a dataset of 17 site-years across Kansas, United States. Replicated field trials evaluated tiller presence (removed or intact) in two hybrids (P0657AM and P0805AM) at three target plant densities (25000, 42000, and 60000 plants ha-1). Record of ears and kernels per unit area and kernel weight were collected separately for both main stalks and tillers in each plot. Indicated tiller contributions impacted the plasticity of yield components in evaluated genotypes. Ear number and kernel number per area were less dependent on plant density, but kernel number remained key to yield stability. Although ear number was less related to yield stability, ear source and type were significant yield predictors, with tiller axillary ears as stronger contributors than main stalk secondary ears in high-yielding environments. Certainly, managing for the most main stalk primary ears possible - that is, optimizing the plant density (which consequently reduces tiller expression), is desirable to maximize yields. However, the demonstrated escape from the deterministic hierarchy of corn yield formation may offer avenues to reduce corn management dependence on a seasonally variable optimum plant density, which cannot be remediated mid-season.

Controlled release urea increases soybean yield without compromising symbiotic nitrogen fixation

Summary In Brazil, high-yield soybean [Glycine Max (L). Merrill] – corn (Zea mays L.) double cropping system might be nitrogen (N)-limited and additional N fertilization can be beneficial. Early application of N in soybean reduces the symbiotic N fixation (SNF) efficiency and/or establishment. One alternative to avoid SNF impairment is to apply N between the beginning pod (R3) and seed-fill (R5) stages through the use of controlled release fertilizers. In this study, N was applied at 50 kg ha−1 as common urea (CU) or controlled release urea (CRU) with different lag periods until N release starts (30 days, 60 days, or 1:1 mix of both lag times) in a randomized complete blocks design with six treatments and four replicates under tropical and subtropical conditions. CU was applied after soybean emergence (VE) or at the beginning pod (R3), and CRU only at VE. Using urea labeled with 15N isotope, we analyzed the N source used by soybean (fertilizer, soil, or SNF) and SNF parameters. On average, CRU – 30 days, CRU – 1:1 mix (30 + 60 days) and CU applied at the R3 stage increased grain yield by 9.2% (354 kg ha−1) compared to the control. N derived from all fertilizer treatment were almost 35 kg N ha−1, a high N recovery efficiency of 68%. The SNF was not impaired by CU and CRU and accounted for 71% (220 kg N ha−1) of total N uptake. In the conditions of the experiments, fertilization of 50 kg N ha−1 as CRU was shown to be effective to supply N in late soybean demand (R3 stage), increasing yield without damaging the SNF process in high-yield environments.

Low seed rate in square planting arrangement has neutral or positive effect on grain yield and improves grain nitrogen and phosphorus uptake in wheat

Wheat (Triticum aestivum) has a high capacity to compensate grain yield (GY) at lower seed rates than those commonly assumed, especially in high-yield-potential environments. Our study aimed at assessing: (i) the response of GY, biomass and harvest index of wheat under two contrasting seed rates; (ii) trade-offs among yield components in response to seed rate; and (iii) the sensitivity of grain and crop N and P content and nutrient use efficiency under conventional and low seed rates in the high-yielding environment of southern Chile. We evaluated two wheat cultivars —Bacanora (higher grain number and intermediate grain weight) and Kambara (lower grain number and higher grain weight)— at two seed rates, a farmers’ seed rate of 350 plants m −2 (CON) and low seed rate of 44 plants m −2 with square grid planting arrangement (LSR), under optimum crop management conditions during two growing seasons in southern Chile (Valdivia). We evaluated GY and its components, as well as nitrogen (N) and phosphorus (P) economies. Contrasting results were found between cultivars under LSR. Bacanora fully compensated GY components reaching the same GY under both LSR and CON treatments, while Kambara yielded 12% more under the LSR treatment, compared with that of the CON treatment. The LSR treatment decreased the plant height of both cultivars by 0.14 m (19% and 15% in Bacanora and Kambara, respectively), which improved the harvest index. Under the LSR treatment, Bacanora showed a small decrease in grain number while there was no effect in Kambara. Both cultivars reached higher (P < 0.001) average grain weight under the LSR treatment. Furthermore, Bacanora increased grain N concentration and both cultivars improved grain P concentration under the LSR treatment. P uptake and P uptake efficiency were increased (P < 0.001 and P < 0.01, respectively) under the LSR treatment in both cultivars by 18%. Low seed rate (44 pl m −2 ) with square grid planting distribution results in preserved or increased wheat GY compared with the conventional seed rate (350 pl m −2 ), mainly due to an increase in grain weight in both genotypes. The LSR treatment resulted in decreased plant height, allowing an improved harvest index. Additionally, LSR had also a positive effect on grain P concentration, and a remarkably increased of both P uptake and P uptake efficiency. Our results offer an opportunity to increase the uptake of nutrients such as P, without any GY penalty and may even increase yields, at least in high yield environments, such as southern Chile. • Low seed rate (44 plants m −2 ) with a square grid planting arrangement preserved or increased wheat grain yield. • Low seed rate treatment increased grain weight (15%) and grain nutrient concentrations (N: 13%; P: 13%). • Harvest index increased under the low seed rate treatment. • Nitrogen yield and nitrogen harvest index increased under the low seed rate treatment. • Phosphorus uptake and phosphorus uptake efficiency increased under the low seed rate treatment.

Early-season plant-to-plant spatial uniformity can affect soybean yields

Increased soybean (Glycine max L. Merril) seed costs have motivated interest in reduced seeding rates to improve profitability while maintaining or increasing yield. However, little is known about the effect of early-season plant-to-plant spatial uniformity on the yield of modern soybean varieties planted at reduced seeding rates. The objectives of this study were to (i) investigate traditional and devise new metrics for characterizing early-season plant-to-plant spatial uniformity, (ii) identify the best metrics correlating plant-to-plant spatial uniformity and soybean yield, and (iii) evaluate those metrics at different seeding rate (and achieved plant density) levels and yield environments. Soybean trials planted in 2019 and 2020 compared seeding rates of 160, 215, 270, and 321 thousand seeds ha−1 planted with two different planters, Max Emerge and Exact Emerge, in rainfed and irrigated conditions in the United States (US). In addition, trials comparing seeding rates of 100, 230, 360, and 550 thousand seeds ha−1 were conducted in Argentina (Arg) in 2019 and 2020. Achieved plant density, grain yield, and early-season plant-to-plant spacing (and calculated metrics) were measured in all trials. All site-years were separated into low- (2.7 Mg ha−1), medium- (3 Mg ha−1), and high- (4.3 Mg ha−1) yielding environments, and the tested seeding rates were separated into low (< 200 seeds m−2), medium (200–300 seeds m−2), and high (> 300 seeds m−2) levels. Out of the 13 metrics of spatial uniformity, standard deviation (sd) of spacing and of achieved versus targeted evenness index (herein termed as ATEI, observed to theoretical ratio of plant spacing) showed the greatest correlation with soybean yield in US trials (R2 = 0.26 and 0.32, respectively). However, only the ATEI sd, with increases denoting less uniform spacing, exhibited a consistent relationship with yield in both US and Arg trials. The effect of spatial uniformity (ATEI sd) on soybean yield differed by yield environment. Increases in ATEI sd (values > 1) negatively impacted soybean yields in both low- and medium-yield environments, and in achieved plant densities below 200 thousand plants ha−1. High-yielding environments were unaffected by variations in spatial uniformity and plant density levels. Our study provides new insights into the effect of early-season plant-to-plant spatial uniformity on soybean yields, as influenced by yield environments and reduced plant densities.

Modified crop rotations for a sustainable intensification? A case study in a high-yielding environment with recurrent nitrogen surplus

Agriculture is a major contributor to nitrate groundwater contamination. Hence, farmers are demanded to reduce the environmental impact but simultaneously must provide sufficient food products. One important building block for this “sustainable intensification” are appropriate cropping strategies. The potential of modified crop rotations was evaluated in a high-yielding environment in Northern Germany. Therefore, in five consecutive growing seasons (2016/2017 – 2020/2021) three crop rotations were grown in a field trial and compared with respect to agronomic (cereal unit), economic (gross margin) and environmental (N surplus) parameters. A standard crop rotation, typical for the region of the study, was compared with rearranged and augmented crop rotations. Therefore, crops with a high autumnal N uptake (winter oilseed rape and catch crops) were grown after crops with typically high soil mineral N (SMN) amounts after harvest (faba bean and winter oilseed rape). Due to the change of preceding and subsequent crops, an increased N transfer was supposed to prevent N from leaching and a lower N fertilizer demand of the subsequent crop was expected. On average, the modified crop rotations achieved significantly higher cereal units (9.3 and 10.8 t · ha−1) compared to the local crop rotation (8.5 t · ha−1). The gross margin of the local crop rotation was 1474 € · ha−1 and the other crop rotations maintained (1443 € · ha−1) or significantly increased (1572 € · ha−1) this value, respectively. The local crop rotation had a N surplus of 47 kg N · ha−1. In contrast, the N surplus of the modified crop rotations was significantly lower (10 and 28 kg N · ha−1). In summary, the results showed that a thoughtful rearrangement of crop rotations is an appropriate measure to simultaneously improve yields and gross margins with less unfavorable environmental impacts.

Optimizing water and nitrogen productivity of wheat and triticale across diverse production environments to improve the sustainability of baked products.

Wheat (Triticum aestivum L.) is a major global commodity and the primary source for baked products in agri-food supply chains. Consumers are increasingly demanding more nutritious food products with less environmental degradation, particularly related to water and fertilizer nitrogen (N) inputs. While triticale (× Triticosecale) is often referenced as having superior abiotic stress tolerance compared to wheat, few studies have compared crop productivity and resource use efficiencies under a range of N-and water-limited conditions. Because previous work has shown that blending wheat with triticale in a 40:60 ratio can yield acceptable and more nutritious baked products, we tested the hypothesis that increasing the use of triticale grain in the baking supply chain would reduce the environmental footprint for water and N fertilizer use. Using a dataset comprised of 37 site-years encompassing normal and stress-induced environments in California, we assessed yield, yield stability, and the efficiency of water and fertilizer N use for 67 and 17 commercial varieties of wheat and triticale, respectively. By identifying environments that favor one crop type over the other, we then quantified the sustainability implications of producing a mixed triticale-wheat flour at the regional scale. Results indicate that triticale outyielded wheat by 11% (p < 0.05) and 19% (p < 0.05) under average and N-limited conditions, respectively. However, wheat was 3% (p < 0.05) more productive in water-limited environments. Overall, triticale had greater yield stability and produced more grain per unit of water and N fertilizer inputs, especially in high-yielding environments. We estimate these differences could translate to regional N fertilizer savings (up to 555 Mg N or 166 CO2-eq kg ha−1) in a 40:60 blending scenario when wheat is sourced from water-limited and low-yielding fields and triticale from N-limited and high-yielding areas. Results suggest that optimizing the agronomic and environmental benefits of triticale would increase the overall resource use efficiency and sustainability of the agri-food system, although such a transition would require fundamental changes to the current system spanning producers, processors, and consumers.

Genotype by Environmental Interaction and Measurements of Stability on Eight Orange-Fleshed Sweet Potato (Ipomoea batatas) Varieties: East Gojjam Zone, North West Ethiopia

Sweet potato is grown for its nature of versatility and adaptability and is a secure food crop in southern parts of Ethiopia. Therefore, this research has been conducted to determine the magnitude of GEI for yield and yield-related traits and to evaluate the adaptability and stability of eight orange-fleshed sweet potato varieties across locations in North West Ethiopia. The experiment was conducted from 2018 to 2019 under rainfed conditions in four districts of East Gojjam Zone (Baso liben, Gozamin, Gonchasiso enesie, and Enbsie Sar mider) using eight OFSP varieties (Kulfo, Kabode, Vitea, Naspot 13, Naspot 12, Nekawango, RW-11, and Mayai). Data were collected on yield and yield-related traits. Genstat statistical software was used to deploy both combined analysis of variance and meta-analysis of the collected data. The combined ANOVA revealed that environment, varieties, and their interaction affect the tested varieties significantly across locations. Debremedhanite was the high-yielding environment (35.9 t/ha), and Kulfo was the best-performing variety (30.67 t/ha) over different environments. Based on the AMMI result, the environment contributes at large (48.49%) to the total variation of variety performance followed by variety (27.18%) and their interaction (24.23%). The testing locations fall in two mega environments that implies that variety recommendation needs to be specific for each mega environment. Hence, Kulfo and Naspot 12 are recommended for Debremedhanit, Arasma, and Degesech based on yield potential and stability of the varieties, and Naspot 13 is recommended for Yelamgej, Eneba, and Getesemani testing locations. This result is useful for breeders and nutritionists who are working on breeding of sweet potatoes and nutrition.

Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers

Diversified cropping systems, especially those including legumes, have been proposed to enhance food production with reduced inputs and environmental impacts. However, the impact of legume pre-crops on main crop yield and its drivers has never been systematically investigated in a global context. Here, we synthesize 11,768 yield observations from 462 field experiments comparing legume-based and non-legume cropping systems and show that legumes enhanced main crop yield by 20%. These yield advantages decline with increasing N fertilizer rates and crop diversity of the main cropping system. The yield benefits are consistent among main crops (e.g., rice, wheat, maize) and evident across pedo-climatic regions. Moreover, greater yield advantages (32% vs. 7%) are observed in low- vs. high-yielding environments, suggesting legumes increase crop production with low inputs (e.g., in Africa or organic agriculture). In conclusion, our study suggests that legume-based rotations offer a critical pathway for enhancing global crop production, especially when integrated into low-input and low-diversity agricultural systems.

Estimating technological quality parameters of bread wheat using sensor-based Normalized Difference Vegetation Index

This multi-environment study aimed to investigate the usability of the sensor-based Normalized Difference Vegetation Index (NDVI) for estimating bread wheat technological quality properties. The relationships between the technological quality properties and NDVI Zadoks (ZD) 31 stage readings were evaluated by grouping the trials as low and high-yielding environments (LYE and HYE). According to the results, the quality parameters and grain yield were higher in the HYE compared to the LYE group. Generally, the increase in the grain protein content (GPC), macro SDS sedimentation (MSDS) volume, and GlutoPeak aggregation energy (AGGEN) value differences became evident after 80 kg ha−1 nitrogen dose in the LYE, while, significant effects were observed after 40 kg ha−1 dose in the HYE. The equations developed in this study can be used for the estimation of GPC, and technological quality properties in the NDVI ZD31 stage. The R2s of the regression equations developed for the actual and predicted technological quality parameters of bread wheat were 0.216 for GPC, 0.295 for MSDS, and 0.226 for AGGEN values (p < 0.01; n = 240). As a result of this study, the reading value of 0.758 was found as a critical NDVI ZD31 threshold for the recommendation of nitrogen to obtain high technological quality.

Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment.

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures.