Linear-plateau Model Research Articles

Climate change induced heat and drought stress hamper climate change mitigation in German cereal production

ContextAgricultural production and climate change strongly influence each other and there are significant efforts to minimize negative impacts in both directions. In particular, breeding progress has succeeded in reducing the carbon footprint (CFP) of cereals over time. However, there is widespread certainty that climate change-related weather extremes have led to stagnation of cereal yields in many global production regions. Research questionWe assume that climate change-related yield stagnation is also evident in variety trials in Germany, which has to date only been shown for on-farm yields. Furthermore, we expect that the stagnation in yields also leads to a stagnation in the downward trend of CFP, and that heat and drought stress in particular increase the CFP of cereals. In addition, we hypothesize that the site-specific soil quality largely determines stress induced increases in CFP. MethodsWe conduct a partial life cycle assessment (LCA) with German variety trial data from 1993 to 2021 and determine the greenhouse gas emissions per unit of land (GHGL), as well as the CFP of winter wheat, winter rye, and winter barley. Further, we evaluate the time trends of yield, GHGL, and CFP using linear and quadratic plateau models. In addition, we calculate spatio-dynamic weather indices (WIs) for moderate, severe and extreme heat and drought stress. Using mixed models, we estimate the explanatory power and effect size of heat and drought WIs on the CFP. Finally, we present the spatial differences of heat and drought on the CFP at different soil qualities. ResultsWe show yield plateaus in all crops and stagnating GHGL trends, resulting in a stagnation of the downward trend of CFP, especially for rye and barley. We highlight that heat and drought increase the CFP of all crops. However, the impact of heat and drought on the CFP varies greatly with soil quality across all crops. ConclusionsWe conclude that climate change-induced weather extremes are major challenges not only for cereal production and food security but also for climate change mitigation in the agricultural sector, highlighting the importance of high-yield locations, alongside variety selection and resource-efficient management, for climate change mitigation. SignificanceThis study is the first that proves significant yield stagnation in German variety trials. Moreover, this study is the first to analyze the impact of heat and drought stress on cereal CFP, with novel results that proof that climate adaptation will become a crucial aspect of climate change mitigation in field crops.

Lysine requirement of weaned piglets

Lysine, often referred to as the ‘first limiting amino acid’ in pig nutrition, plays a pivotal role in growth performance. Variability in lysine requirements arises due to factors such as age, sex and environmental conditions. Optimising pig health and production efficiency and minimising nitrogen excretion require accurate knowledge of estimated lysine requirements accounting for factors such as genetics, feeding practices, scientific advancements, and environmental considerations. This study aimed to determine standardised ileal digestible (SID) lysine requirements of weaned piglets (5–30 kg) based on a literature review using meta-analytical approaches. The literature review yielded 344 studies that were screened for title and abstract. In total, 41 experiments met the inclusion criteria, resulting in a dataset of 206 treatment means. Linear, quadratic and linear-plateau models were used to gain insight into the effect of SID lysine addition on average daily gain and feed efficiency for the combined dataset and separately for the individual experiments. Regression analysis showed a predominant linear increase in average daily gain and feed efficiency as an overall response to increasing lysine levels across both the combined dataset and individual experiments. Breakpoint estimation from the linear-plateau models was inconclusive, indicating that the optimal SID lysine requirement to maximise piglet growth performance likely exceeded the upper lysine levels tested in most studies, thus surpassing 1.3 g SID lysine per MJ net energy. This review indicates high values for the lysine requirement to achieve maximum growth performance. Results may suggest that piglet feed formulation should focus on an optimal dietary SID lysine to CP ratio, rather than SID lysine per kg of diet or unit of net energy. However, more research is needed to investigate this suggestion.

Potassium Availability in Tropical Sandy Soils and Cassava Response to Three-Year K Fertilization

ABSTRACT Potassium (K) is the primary limiting nutrient for cassava, being essential to achieve sustainably satisfactory cassava yields in low K reserve sandy soils that require proper K fertilization to avoid depleting the soil K reserve. Soil K dynamics, the growth, and yield responses of cassava were investigated using varying K fertilizer rates (0, 25, 50, 75, 100, and 125 kg K2O/ha). Four on-farm experiments were conducted in major cassava-producing areas, Northeast Thailand during 2019–2021 year. Cassava responded positively to K, producing yield increases up to 132%, with the highest tuber yield obtained being in the range 100–125 kg K2O/ha. Mineral K was the main K source for cassava grown without K fertilization, which resulted in the poorest growth and yield quantities. Potassium fertilization significantly promoted the uptake of K by cassava, especially in the tuber, causing a negative K balance due to the large removal from the soil, even when the K fertilizer compensated to some degree. Potassium use efficiency of cassava was low, particularly with K fertilization at the highest rate, which reflected intense leaching of the soil. The critical level of soil-available K, identified using a linear-plateau model, was 40.55 mg/kg for 90% relative yield, suggesting the potential to increase K use efficiency through better fertilization guidelines. Our findings suggested that K fertilization of cassava annually is advisable for better yields and to avoid progressive depletion of the soil K capital, even though the residual K from K fertilizer contributed to available K in soils.

Models and sufficiency interpretation for estimating critical soil test values for the Fertilizer Recommendation Support Tool

AbstractSoil test correlation determines whether a soil test can be used to predict the need for fertilization based on the critical soil test value (CSTV). Our objectives were to compare the CSTV estimated from five combinations of correlation models and yield sufficiency interpretations and to select one method for soil test correlation performed with the Fertilizer Recommendation Support Tool (FRST). Four models were fit to three datasets with strong (Mehlich‐1 K), moderate (Mehlich‐3 K), or weak (Olsen P) correlations between soil test P or K and crop relative yield. We tested the arcsine‐log calibration curve (ALCC), exponential (EXP), linear plateau (LP), and quadratic plateau (QP) models. The CSTV was defined as 95% of the maximum predicted yield for the ALCC and EXP methods, the join point for LP, and both the join point and 95% of the maximum for the QP providing five CSTV predictions. The five CSTVs ranged from 46 to 66 mg kg−1 for the Mehlich‐1 K dataset, 115 to 165 mg kg−1 for the Mehlich‐3 K dataset, and 7 to 16 mg kg−1 for the Olsen P dataset. Ten pairwise comparisons showed the estimated CSTV was numerically and sometimes statistically influenced by the model and sufficiency level interpretation. Despite differences among CSTVs, the frequency of significant yield responses above and below the predicted CSTV was generally comparable among the methods, with false‐negative errors occurring at 0%–18% of sites for a given dataset. The QP model with a CSTV at 95% of the predicted maximum was selected as the modeling approach for FRST.

Soil biological and physical measurements did not improve the predictability of corn response to phosphorus fertilization

AbstractIncluding soil health and physical measurements with traditional soil fertility measurements has the potential to improve corn (Zea mays L.) P fertilizer recommendations. The objectives for this study were to (1) evaluate the accuracy of current South Dakota corn P recommendations in predicting yield increases and (2) determine if the predictability of yield response to P fertilization improves by including selected soil biological, physical, and chemical measurements. This project was conducted in central and eastern South Dakota from 2019 to 2022 at 117 experimental sites that varied in management, landform, and soil type. A treatment of 48.9 kg P2O5‐P ha−1 was compared to a control with no P fertilizer. Soil samples (0–15 cm) collected before fertilization were analyzed for selected soil physical, chemical, and biological parameters. Analysis suggested that the current critical P value of 16 mg Olsen‐P kg−1 was still accurate as it was still within the 68% confidence interval for the linear (12–19 mg kg−1) and quadratic plateau (16–26 mg kg−1) models. Using the critical value of 16 mg Olsen‐P kg−1, we correctly predicted P responsiveness 70% of the time. The accuracy of predicting P responsiveness was not further improved by considering selected enzymes, permanganate oxidizable C, soil respiration, total C, or total N, but was improved by considering pH, soil organic matter, and apparent cation exchange capacity. Therefore, the use of typical soil fertility measurements without soil physical and biological measurements is currently the best option for predicting the responsiveness of corn to P fertilization in South Dakota.

Maize//Soybean Intercropping Improves Yield Stability and Sustainability in Red Soil under Different Phosphate Application Rates in Southwest China

Studying the effects of maize and soybean intercropping for improving the maize yield and sustaining stability of the maize yield under different phosphate (P) application rates in red soil is crucial for promoting maize productivity, improving soil fertility and optimizing P nutrient management in southwest China. The objective of this study was to evaluate the dynamic changes in maize yield, yield stability and soil fertility under monoculture and intercropping maize with different P application rates. A six-year field experiment was conducted from 2017 to 2022 to investigate the effects of maize intercropping with soybean on the yield stability and sustainability of maize according to the changes in the maize yield, biomass, partial land equivalent ratio of yield (pLERY), actual yield loss index (AYL), contribution rate of soil capacity and fertilizer (SCR, SFCR) over time, as well as the differences in the coefficient of variation (CV) and sustainable yield index (SYI) at four P application rates (0 kg P2O5 ha−1, P0; 60 kg P2O5 ha−1, P1; 90 kg P2O5 ha−1, P2; and 120 kg P2O5 ha−1, P3) based on the two-factor randomized block design. The linear-platform model was utilized to simulate the relationship between the grain yield, the SYI and the amount of P fertilizer under different P application rates. The maize yield in intercropping was significantly superior to the maize yield in monoculture throughout the entire six-year experiment. For all planting years, the yield and biomass of the intercropping were higher than those of the matched monoculture average by 56.0% and 56.1%, respectively. Intercropping had an advantage of pLERY and AYL for maize. Otherwise, intercropping reduced the CV by 30.8% and 39.1% and increased the SYI by 39.4% and 23.0% in P0 and P3 compared with the matched monoculture, respectively. For all planting years, the average SFCR in intercropping treatment was higher than that in monoculture treatment. The linear-plateau model fitted showed that intercropping increased the yield and SYI by 19.8% and 40.7% on the platform and reduced the P application rate by 37.8% and 11.9% at the inflection point, respectively. These results demonstrate that maize and soybean intercropping could achieve a higher yield, a higher yield stability and an SYI with a lower P input than monoculture. Maize and soybean intercropping could be a sustainable practice for promoting the maize productivity and the yield sustainability in the red soil of southwest China.

The Evaluation of a Long-Term Experiment on the Relationships between Weather, Nitrogen Fertilization, Preceding Crop, and Winter Wheat Grain Yield on Cambisol

In this paper, a sequence (1979–2022) of a long-term trial established in Lukavec in 1956 (Czech Republic) focusing on the effect of weather, various nitrogen (N) fertilization methods (control, PK, N1PK, N2PK, and N3PK) and preceding crops (cereals, legumes, and oil plants) on winter wheat grain yield is presented. The weather significantly changed at the site of the long-term trial. While the trend in the mean temperature significantly increased, precipitation did not change significantly over the long term. Four relationships between weather and grain yield were evaluated to be significant: (a) the mean temperature in February (r = −0.4) and the precipitation in (b) February (r = −0.4), (c) March (r = −0.4), and (d) May (r = 0.5). The yield trends for all the fertilizer treatments increased, including the unfertilized control. The N3PK treatment provided the highest mean grain yields, while the unfertilized control had the lowest yields. Comparing the preceding crops, the highest yields were harvested when the wheat followed the legumes. On the other hand, the cereals were evaluated as the least suitable preceding crop in terms of grain yield. According to the linear-plateau model, the optimal nitrogen (N) dose for modern wheat varieties, following legumes and under the trial’s soil climate conditions, was 131 kg ha−1 N, corresponding to a mean grain yield of 8.2 t ha−1.

Using Data from Uniform Rate Applications for Site-Specific Nitrogen Recommendations

AbstractMuch historical yield-monitor data is from fields where a uniform rate of nitrogen was applied. A new approach is proposed using this data to get site-specific nitrogen recommendations. Bayesian methods are used to estimate a linear plateau model where only the plateau is spatially varying. The model is then illustrated by using it to make site-specific nitrogen recommendations for corn production in Mississippi. The in-sample recommendations generated by this approach return an estimated $9/acre on the example field. The long-term goal is to combine this information with other information such as remote sensing measurements.

Optimal treatment placement for on-farm experiments: pseudo-Bayesian optimal designs with a linear response plateau model

Optimal treatment placement for on-farm experiments: pseudo-Bayesian optimal designs with a linear response plateau model

Responses of Crop and Soil Phosphorus Fractions to Long-Term Fertilization Regimes in a Loess Soil in Northwest China

Contrasting fertilization modifies soil phosphorus (P) transformation and bioavailability, which impact crop P uptake and P migration in the soil profile. A long-term (25-year) fertilizer experiment was employed to investigate crop yield, P uptake and changes in sequentially extracted P fractions in the soil profile, and their relationships on a calcareous soil derived from loess material under a winter wheat and summer maize double-cropping system. The experiment involved seven nutrient management treatments: control (CK, no nutrient input), N, NK, NP, and NPK, representing various combinations of synthetic nitrogen (N), phosphate (P), and potassium (K) applications, as well as combinations of NPK fertilizers with either crop residues (SNPK, where S refers to maize stalk or wheat straw) or manure (MNPK, where M refers to dairy manure). Wheat and maize yields were significantly higher with P input fertilizer relative to the P-omitted treatments. Long-term application of P-containing fertilizers markedly raised the contents of inorganic (Pi) and organic (Po) P fractions at 0–20 cm depth compared with the P-omitted treatments. Moreover, both Pi and Po fractions were markedly higher under MNPK than under NPK and SNPK treatments. For achieving high yield for wheat and maize, the critical contents of labile P were 54 and 63 mg kg−1, and those of moderately labile P were 48 and 49 mg kg−1, respectively, defined by the linear plateau model. In addition, the change points of labile P and moderately labile P were 99 and 70 mg kg−1, above which CaCl2-P content significantly increased. Moreover, long-term P input significantly accumulated different P fractions in the deeper soil layers up to 100 cm, with large portions of organic P being a composite of labile and moderately labile P, especially in MNPK treatment. Our results suggest that excessive P supply with organic manure resulted in massive P accumulation in the topsoil and promoted soil P fraction transformation and availability in the deep soil layers, especially in an organic P form that has often been neglected.

Nitrogen fertilizer and pronitridine rates for corn production in the Midwest U.S.

ContextReducing nitrogen (N) losses can be accomplished by applying recommended N rates and using nitrification inhibitors (NI). In some agricultural systems, managing N application rate or using a NI could improve N use efficiency and increase crop yields. ObjectiveThe objectives of this 13 site-year study were to determine the agronomic optimum N rate (AONR) application rate using linear plateau and quadratic plateau models, determine the optimum pronitridine rate when applied with 70 % of the recommended N amount, and evaluate the effect of nitrapyrin and pronitridine on corn (Zea mays L.) yield. MethodsIn this experiment, pronitridine and nitrapyrin were used as NIs and were applied in the fall and spring. This research was conducted in the US in Illinois (IL), Missouri (MO), and Nebraska (NE) from 2016 to 2019. ResultsThe AONR varied from 176 to 291 kg ha-1 in different site-years. The optimal pronitridine rate was predicted using the generalized additive model (GAM) for each site. A pronitridine rate of 5.6 g kg-1 N and 8.2 g kg-1 N was recommended for well drained (NE) and poorly drained (MO and IL) sites, respectively. The pronitridine application at an average rate of 5.6 g kg-1 N increased corn grain yield 4 % compared to the non-treated control. Economic analysis showed an increase in gross margin returns of 32–67 $ ha-1 in poorly drained soils (MO & IL) when applied at 8 g kg-1 with fall and spring N application. Whereas 10–30 $ ha-1 higher gross margins were observed in well-drained soils (NE) with an application of 4 g kg-1 of pronitridine for fall and spring application timings. ConclusionThe differences in AONR and pronitridine rate prediction observed in this study emphasize the variability caused by factors such as the soil, environment, and their interaction with the N cycle. When we evaluated pronitridine and nitrapyrin with all site years combined, no differences between the two NIs were observed in terms of corn yield production. SignificanceOur findings are the first to quantify corn yield response for pronitridine applications at different locations and multiple rates in the Midwest U.S. The results of this study highlight the optimum pronitridine optimum rate for improved corn yield in poorly drained and well-drained soils in the Midwest U.S. Profitability of pronitridine can be improved by applying an optimum rate based on N requirements and soil conditions.

Fully Bayesian economically optimal design for a spatially varying coefficient linear stochastic plateau model over multiple years

Fully Bayesian economically optimal design for a spatially varying coefficient linear stochastic plateau model over multiple years

Using post‐season tissue nitrogen concentrations to predict adequacy of in‐season nitrogen management

AbstractHigh‐yielding mechanized rice production requires large amounts of nitrogen (N) fertilizer, which can be particularly costly to producers when applied in excess. The development of a tissue test to detect overapplication of N to rice is needed. Nitrogen response trials arranged in a randomized complete block design were established to identify a critical concentration threshold for a tissue test to detect excess N availability. Rice stalk samples were collected from 0 to 20 cm above the soil within 5 days of harvest and analyzed for NO3−‐N concentration. Two models were fit to the data to represent rice grain yield as a function of N concentration: the linear plateau model and the quadratic plateau model. The data were well represented by both models; however, the linear plateau model more accurately described the data with a normalized root mean square error of 0.128 for linear plateau and 0.131 for quadratic plateau and a significant F‐test (p < 0.0001). The join point of the linear response region and the plateau region of the model serves as a critical value that separates the responsive (N deficient) and non‐responsive (N optimum or excessive) regions. The 95% confidence interval of the join point (2.1 mg NO3−‐N kg−1) was selected as a practical, agronomic critical concentration threshold to reduce false positive errors. The data presented here further supports the use of a post‐season tissue test in rice to detect overfertilization and establish a critical concentration threshold for this tissue test.

Toward potential applications of the nitrogen nutrition index in Sweet basil (Ocimum basilicum L.) production under greenhouse conditions

The nitrogen nutrition index (NNI) as an effective indicator for monitoring crop nitrogen (N) status has multiple applications in agriculture, such as estimating in-season crop N requirement (NR), predicting crop biomass/yield, and improving N use efficiency. The present study was aimed to develop basil (Ocimum basilicum L.) NR and relative biomass (RB) prediction models based on the concept of critical N concentration. Two experiments were carried out with different N application rates in the research greenhouse of University of Tehran, Iran. Basil NNI values were calculated using the previously developed critical N dilution curve. Subsequently, the in-season basil NR estimation model was developed as a function of NNI, N recovery efficiency (NRE) and plant age. Additionally, basil RB was simulated as a function of the averaged and integrated NNI based on a linear-plateau model. Moreover, a theoretical relationship between N utilization efficiency (NUtE) and the NNI was established. The validation results of the developed NR-NNI model demonstrated a good performance with a root mean square error (RMSE) and a normalized root mean square error (NRMSE) less than 5.28 kg ha−1 and 4.72%, respectively. The results showed that crop biomass and NNI were the most significant explanatory factors for the variations in basil NUtE. Therefore, the crop NNI can serve as a practical in-season diagnostic tool for basil NR and RB prediction, while also contributing to the design of decision support systems and sustainable agro-ecosystems.

Coccidiosis infection and growth performance of broilers in experimental trials: insights from a meta-analysis including modulating factors

An infection by protozoa Eimeria spp. can cause coccidiosis, which negatively affects broiler chicken performance and causes economic and production losses. To understand the effect of coccidiosis on broilers' performance, we evaluated the independent variables and their interactions on the severity of coccidiosis in broilers that cause variation (Δ) of average daily feed intake (ADFI), average daily gain (ADG), and gain per feed (G:F) of broiler chicks using a meta-analysis approach. A database of 55 papers describing 63 experiments was gathered; broilers were challenged by Eimeria species (E. acervulina, E. maxima, E. tenella, and mixed) and at least 2 variables among ADFI, ADG, and feed conversion ratio (FCR) were studied. The variation induced by the challenge was calculated relative to the control group of each experiment. The indirect factors evaluated were days postinfection (DPI), Eimeria type and dose, infection age (IA), bird's mean age in the analyzed period, genetic line, sex, and whether they were raised in a cage or a pen. Graphical, correlation, and variance analyses were performed to evaluate the form of the responses. Then, a linear plateau model was adjusted for each response variable as a function of DPI to determine the consequences of the disease on the variation of performance over time after infection. The impact of the infection challenge on the variation of performance vs. nonchallenge broilers was only impacted by DPI (P < 0.05). The adjustment of the data with the linear plateau model allows us to determine the host response to the coccidiosis disease at different stages. At 5 DPI (acute phase), ΔADFI, ΔADG, ΔG:F were of -19.0; -39.8, and -25.5, respectively. After almost 13 DPI birds achieved the recovery phase for all variables with Δ varying from -19 to -3.75% for ADFI, from -39.8 to -10.5% for ADG, and from -25.5 to -7.24% for G:F. The Eimeria impact was higher in ADG than ADFI in all periods due to Eimeria aggressive action form causing lesions in gut epithelial reducing the use of nutrients and energy. The results can be used as a quantitative approach to determine the consequences of Eimeria spp. on broiler performance.

Use of statistical models to determine the optimal concentration of metabolizable energy for growth performance of broiler chickens

The formulation of diets that adequately meet energy requirements in the different phases of broiler chicken production is of the utmost importance. The objective of this study was to determine the optimal content of metabolizable energy (ME) for broiler chickens in various production phases using different statistical models. A total of 900 broiler chickens were assigned to 5 treatments with 9 replicates of 20 broiler chickens each from 21 to 42 d of age in a completely randomized design. Experimental diets were based on corn and soybean meal and formulated to meet the nutritional requirements of broiler chickens, except for ME requirements. Dietary treatments consisted of 5 pelleted/crushed diets with increasing levels of ME: T1 to T5 (2,850 to 3,250 kcal/kg), divided into grower (21 to 35 d) and finisher (35 to 42 d) phases. Feed intake (FI), body weight gain (BWG), feed conversion ratio (FCR), total energy intake, efficiency of energy use for BWG, and carcass and cuts yields were determined. The ideal ME content for best FCR was determined with the use of quadratic polynomial (QP), segmented, and linear response plateau models (LRP). In all evaluated periods, BWG was not influenced by ME, whereas FI and FCR decreased linearly with increasing ME. Total energy intake increased and the energy use efficiency for BWG decreased with greater ME (P < 0.05). Neither carcass nor cuts yields were influenced by dietary ME. The ideal dietary ME content differed between statistical models. In conclusion, based on FCR results, the QP regression model presented the best fit of the data in the grower phase, indicating an optimal content of metabolizable energy for feed conversion of 3,264 kcal/kg, whereas LRP presented the best data adjustment in the finisher phase, indicating 3,224 kcal/kg of ME as optimal.

Optimized Nitrogen Fertilizer Rate Can Increase Yield and Nitrogen Use Efficiency for Open-Field Chinese Cabbage in Southwest China

Intensive vegetable production has been characterized by high nitrogen (N) fertilizer input in southwest China. Optimizing the N fertilizer rate is the basis for the optimal management of regional N fertilizer. A two-year field experiment with five N fertilizer rates was conducted during 2019–2021 in southwest China, and the aim of this study was to identify the effects of different N application rates on yield, dry matter biomass (DMB), N uptake, N use efficiency (NUE) and soil mineral N (Nmin) residues for Chinese cabbage (Brassica chinensis L.) and further determine the critical plant N concentration and root-zone soil Nmin residues required to reach the maximum DMB of Chinese cabbage. Five N treatments were established: control without N input (CK); optimal N fertilizer rate decreased by 30% (70% OPT, 175 kg N ha−1), optimized N fertilizer rate (OPT, 250 kg N ha−1), optimal N fertilizer rate increased by 30% (130% OPT, 325 kg N ha−1) and farmers’ N fertilizer practice (FP, 450 kg N ha−1). The N source in all treatments was conventional urea (N ≥ 46.2%). The results showed that the total yield of Chinese cabbage followed a “linear-plateau” trend with an increasing N fertilizer rate. There was no significant difference in yield between the OPT, 130% OPT and FP treatments. The aboveground plant DMB and N uptake showed a ‘slow-fast-slow’ pattern with the growth period. There was no significant difference in aboveground plant DMB and N uptake between the OPT, 130% OPT and FP treatments. Moreover, the OPT treatment significantly increased the aboveground plant DMB and N accumulation by 29.6% and 40.5%, respectively, compared with the 70% OPT treatment. The OPT treatment significantly increased the NUE by 23.8%, 31.2% and 43.1% compared with that in the 70% OPT, 130% OPT and FP treatments, respectively. The linear-plateau model provided the best fit for the relationship among aboveground DMB of Chinese cabbage, plant N concentration and root-zone soil Nmin content. The critical root-zone soil Nmin and plant N concentrations were 94.1, 63.4 and 68.3 kg ha−1 and 34.4, 33.5 and 32.9 g kg−1 during the rosette, heading and harvest periods, respectively. In summary, compared to the FP treatment, the optimized N fertilizer rate (250 kg N ha−1) could significantly reduce the N application rate, maintain yield, increase aboveground plant DMB and N uptake, and improve NUE. Moreover, the study has great significance for guiding the green utilization of vegetable N fertilizer in southwest China.

Early bone reformation after cranial vault remodelling for sagittal craniosynostosis: A retrospective 3D analysis

This study aims to measure postoperative bone reformation percentage, rates and patterns after cranial vault remodelling (CVR) in isolated non-syndromic sagittal craniosynostosis. Volumetric bone measurements were performed starting from the DICOM files of previously available postoperative CT scans. The 3D images were then resampled into the master box, and ‘Skull 3D models’ were derived. The percentage of bone reformation was investigated using automated 3D analysis software. The intra-rater reliability analysis revealed high reliability (Intraclass correlation coefficient = 0.99, p < 0.001). The median bone reformation volume and rate were 11.2 ml and 1.98 ml/week, respectively. The median percentage of bone reformation was 56.7% when the median postoperative CT timing was 6.1 weeks. As a statistic model, the linear plateau showed the highest Pseudo R2 in both volume and percentage of bone reformation predicting patterns. By using the calculated model at 9 weeks postoperatively, the re-osteogenesis reaches 80% of the total cranial defect. After CVR, the early bone reformation pattern was demonstrated as a linear plateau model rather than logarithmic. This study gives a better understanding of the pattern and quantity of re-osteogenesis at cranial defects after CVR. The statistic model can facilitate healthcare practitioners to predict bone reformation and improve postoperative care protocol in sagittal craniosynostosis management.

Spring Wheat–Summer Maize Annual Crop System Grain Yield and Nitrogen Utilization Response to Nitrogen Application Rate in the Thermal–Resource–Limited Region of the North China Plain

Spring wheat–summer maize (SWSM) annual crop systems were formed to satisfy the maize grain mechanized harvest thermal requirement in the thermal–resource–limited region of the North China Plain. However, the nitrogen (N) application rate effect on SWSM annual yield formation, N accumulation and utilization were barely evaluated. Two–year field experiments were conducted to evaluate the effects of the N application rate on the annual yield of SWSM, observe N accumulation and utilization, and identify the optimized N application. The experiments were conducted under 5 N levels of 0 (N0), 180 (N180), 240 (N240), 300 (N300), and 360 (N360) kg ha−1. The results showed that spring wheat, summer maize and annual cereal yield under the N240 and N480 treatments obtained the highest grain yield (GY) of 5038, 1282 and 16,320 kg ha−1, respectively, and the optimal N application rate was estimated using a linear–plateau model to be 231–307, 222–337 and 463–571 kg ha−1 with maximum GY of 4654–5317, 11,727–12,003 and 16,349–16,658 kg ha−1, respectively. With the increase in the N application rate, the dry matter accumulation (DM) were significantly increased by 16.9–173.5% for spring wheat and 11.1≈–76.8% for summer maize, respectively; and the annual cereal DM was 15.1–179.7% greater than that with N0 treatment, respectively. Spring wheat, summer maize and the annual cereal total N accumulation (TN) under N360 and N720 treatments were significantly increased by 5.4–19.1%, 16.6–32.3% and 11.5–26.2%, respectively, compared to the other treatments; however, N use efficiency for biomass and grain production (NUEbms and NUEg) were decreased significantly by 10.9–13.6% and 8.9–20.7%, 6.8–13.8% and 12.2–15.6%, and 5.5–11.7% and 10.0–16.0%, respectively. Meanwhile, the N partial factor productivity (PFPN), N agronomy use efficiency (ANUE), N recovery efficiency (NRE) and N uptake efficiency (NEupk) under the N240 treatment for spring wheat and summer maize obtained high levels of 20.99 and 47.01 kg−1, 9.27 and 16.35 kg−1, 32.53% and 32.44%, and 0.85 and 0.72 kg−1, respectively. Correlation analysis showed that the N application rate, TN and NEupk played significantly positive roles on GY, spring wheat spilke grain number, summer maize ear grain number and 1000–grain weight, DM LAImax and SPADmax, while NUEbms, NUEg, PFPN and ANUE always played negative effects. These results demonstrate that spring wheat, summer maize and annual cereal obtained the highest GY being 4654–5317, 11,727–12,003 and 16,349–16,658 kg ha−1 with the optimal N application rate 231–307, 222–337 and 463–571 kg ha−1, respectively, which provide N application guidance to farmer for spring wheat–summer maize crop systems to achieve annual mechanical harvesting in the thermal–resource–limited region of the North China Plain.

Discrepancy between the crop yield goal rate and the optimum nitrogen rates for maize production in Mississippi

AbstractThe varying influence of the environment on N supply and demand dictates the need for annually updated fertilizer N recommendations. Currently, crop yield goal (CYG) methods are used by 34 land grant universities, including Mississippi State University, these do not consider environmental variations. This research tested the efficacy of CYG by determining the agronomic optimum N rate (AONR) and the economic optimum N rate for Mississippi corn (Zea mays L.) production. In total, 12 treatments in 2020 and 11 in 2021 were replicated four times over four locations in a randomized complete block design. The optimum N rates were calculated by fitting linear, quadratic, linear plateau, and quadratic plateau models by means of three different goodness of fit measures. Furthermore, differences between the CYG rate calculated from the Mississippi yield goal equation and AONR were compared at different management levels (14 comparisons) (all data combined, both years combined, sites combined by year, and individual sites). Overall, AONR varied from 134 to 301 kg N ha–1 at different management levels. When we compared the AONR to the CYG rate, the CYG rate over‐recommended N in 12 of the 14 possible comparisons, with differences ranging from 69 kg N ha–1 less to 110 kg N ha–1 greater than the AONR. These differences between AONR values highlight variability caused by factors such as the soil, environment, and their interaction with N supply and demand, which are unaccounted for by the CYG method.