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Field Crops Research
Elsevier
Field Crops Research

Elsevier

0378-4290

Field Crops Research/Journal Field Crops ResearchSCIISTP
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    Rapeseed as a previous crop reduces rice N fertilizer input by improving soil fertility

    Zhang, ShuntaoLu, JianweiZhu, YunFang, Yating...
    8页
    查看更多>>摘要：Crop rotations play crucial roles in maintaining soil fertility and crop productivity. However, crop nitrogen (N) fertilizer management under different rotation systems has not been well assessed. A total of 194 field experi-ments with different N application rates were conducted around the Yangtze River Basin with the objective of supporting rice N fertilizer management in rapeseed-rice (RR) and wheat-rice (WR) rotations. In the present study, a soil quality index (SQI) based on soil chemical parameters was adopted to estimate the indigenous N supply under different crop rotations. The optimum N application rate for rice in the two rotations with different SQI values was also further analyzed. The results indicated that rice yields under RR rotation were significantly higher than those under WR rotation, especially in the no N (N0) and low N (LN) treatments. The RR rotation also improved the partial factor productivity of N (PFPN). The rice yield of the N0 treatment was significantly posi-tively correlated with the SQI value, indicating that the SQI value could be used to evaluate the indigenous N supply capacity of the soil. The SQI value of the RR rotation was 19.4% higher than that of the WR rotation. Principal component analysis (PCA) showed that soil organic matter, total nitrogen, and alkali-hydrolyzable nitrogen were the three most important factors affecting the SQI. Compared with the WR rotation, the soil organic matter, total nitrogen, and alkali-hydrolyzable nitrogen contents in the RR rotation were 24.1%, 16.8%, and 39.7% higher, respectively. With the increase in the SQI value, the optimum N application rate decreased. In soils with the same SQI value, the RR rotation required less N fertilizer input to achieve the same rice yield, and the optimum N application rate was 18.9 kg ha(-1) lower than that in the WR rotation, especially in low-SQI soils. Therefore, rapeseed as a previous crop in rotation could enhance soil fertility and consequently improve rice yield, ultimately reducing N fertilizer application.
      原文链接:
    • NSTL
    • Elsevier

    Monitoring rice crop and yield estimation with Sentinel-2 data

    Soriano-Gonzalez, JesusAngelats, EduardMartinez-Eixarch, MaiteAlcaraz, Carles...
    11页
    查看更多>>摘要：The future success of rice farming will lie in developing productive, sustainable, and resilient farming systems in relation to coexistent ecosystems. Thus, accurate information on agricultural practices and grain yield at optimum temporal and spatial scales is crucial. This study evaluates the potential application of Sentinel-2 (S2) to monitor the dynamics of rice fields in two consecutive seasons (2018 and 2019) in the Ebro Delta growing area. For this purpose, time series of four different spectral indices (NDVI, NDWIMF, NDWIGAO, and BSI), derived from smoothed S2 data at 20 m spatial resolution, were generated. Then, a combination of the first and second derivative analysis on the temporal profiles of spectral indices was used to automatically identify key phenology and management features from regional to field scale; and for estimating crop yield at fields. Features extracted from NDVI and NDWIGAO were used for identifying significant phenological stage dates (i.e. Tillering, Heading Date, and Maturity), and field status (i.e. hydroperiod), although the performance of the proposed method at field-scale was limited by S2 data gaps. The absolute minimum of NDWIMF showed great potential for estimating rice yield, including different cultivars (r = -0.8), and less sensibility to the number of valid images. Sentinel-2 alone cannot assure a consistent phenology monitoring at all fields but demonstrated strong capabilities for studying the performance of rice fields, thus must be considered in the development of new strategies for the management of rice-growing areas.
      原文链接:
    • NSTL
    • Elsevier

    Novel Genetic Variation Through Altered zmm28 Expression Improves Maize Performance Under Abiotic Stress

    Mo, HuaLafitte, Renee H.Coles, Nathan D.Shen, Bo...
    12页
    查看更多>>摘要：We previously reported that extended and increased expression of the native maize gene zmm28 in maize resulted in transgenic events with greater grain yields under optimum field environments. Here we report additional positive impacts of altered zmm28 expression on improving yield stability of maize in the presence of the key abiotic stresses of water deficit and low nitrogen (N). Transgenic zmm28 elite hybrids were evaluated with their wild type (WT) comparators in multiple Managed Stress Environments (MSE), where a water deficit stress was imposed at flowering (FS) or during grain fill (GFS), or where N application was restricted (LN). Across 5 years of testing (2014-2018, 1600 comparisons, 80 hybrids, 43 locations), the ZmGos2-zmm28 lead event DP202216 increased yield relative to WT an average of 479 kg ha-1 (6.6%), 345 kg ha-1 (3.4%) and 166 kg ha-1 (2.0%) in FS, GFS and LN environments, respectively. Maximum observed yield response across 6-12 transgenic hybrids in a single location x year combination was 1181 kg ha-1 (13.9%), 860 kg ha-1 (9.4%) and 834 kg ha-1 (7.0%), relative to WT, for FS, GFS and LN, respectively. Another independent event, DP382118, provided similar yield improvements in the same environments, confirming overall confidence in the performance of the construct functional gene. In a separate genetic penetration study in 2018, DP202216 increased yield an average of 487 kg ha-1 (4.4%) over a combined set of GFS and FS locations, where 6 SS Bulk F3 populations were crossed with 6 diverse NSS testers (36 hybrids), confirming consistent positive yield responses across diverse germplasm under water-limited conditions. The improved yield stability of multiple elite ZmGos2-zmm28 transgenic hybrids demonstrated over multiple years of abiotic stress exposure indicates this novel transgenic variation can contribute to the sustainable intensification of maize production that will be required to address global yield gaps.
      原文链接:
    • NSTL
    • Elsevier

    Progress in research on site-specific nutrient management for smallholder farmers in sub-Saharan Africa

    Chivenge, P.Zingore, S.Ezui, K. S.Njoroge, S....
    11页
    查看更多>>摘要：Increasing fertilizer access and use is an essential component for improving crop production and food security in sub-Saharan Africa (SSA). However, given the heterogeneous nature of smallholder farms, fertilizer application needs to be tailored to specific farming conditions to increase yield, profitability, and nutrient use efficiency. The site-specific nutrient management (SSNM) approach initially developed in the 1990 s for generating field-specific fertilizer recommendations for rice in Asia, has also been introduced to rice, maize and cassava cropping systems in SSA. The SSNM approach has been shown to increase yield, profitability, and nutrient use efficiency. Yield gains of rice and maize with SSNM in SSA were on average 24% and 69% when compared to the farmer practice, respectively, or 11% and 4% when compared to local blanket fertilizer recommendations. However, there is need for more extensive field evaluation to quantify the broader benefits of the SSNM approach in diverse farming systems and environments. Especially for rice, the SSNM approach should be expanded to rainfed systems, which are dominant in SSA and further developed to take into account soil texture and soil water availability. Digital decision support tools such as RiceAdvice and Nutrient Expert can enable wider dissemination of locally relevant SSNM recommendations to reach large numbers of farmers at scale. One of the major limitations of the currently available SSNM decision support tools is the requirement of acquiring a significant amount of farm-specific information needed to formulate SSNM recommendations. The scaling potential of SSNM will be greatly enhanced by integration with other agronomic advisory platforms and seamless integration of digital soil, climate and crop information to improve predictions of SSNM recommendations with reduced need for on-farm data collection. Uncertainty should also be included in future solutions, primarily to also better account for varying prices and economic outcomes.
      原文链接:
    • NSTL
    • Elsevier

    Effects of free-air temperature increase on grain yield and greenhouse gas emissions in a double rice cropping system

    Wang, HaiyuanYang, TaotaoChen, JiBell, Stephen M....
    9页
    查看更多>>摘要：The responses of grain yield and greenhouse gas (GHG) emissions to climate warming in rice paddies are serious concerns for both global food security and climate change mitigation. However, the impact of free-air temperature increase (FATI) on grain yield and methane (CH4) and nitrous oxide (N2O) emissions remains unclear for one of the most globally significant rice production practices: the double rice cropping system. Here, we con-ducted a two-year field experiment to examine the effect of FATI by infrared heaters on grain yield and CH4 and N2O emissions in a double rice field in subtropical China. FATI increased rice canopy temperature by 2.0 degrees C and soil temperature by 1.2 degrees C on average but had no effect on either early or late rice yield production. FATI did not affect CH4 emissions, but significantly increased N2O emissions in both the early and late rice seasons. Averaged across two years, N2O emissions increased by 0.3 kg ha(-1) and 0.7 kg ha(-1) in the warmed plots for the early and late rice seasons, respectively. Consequently, FATI enhanced the global warming potential (GWP) and GHG intensity (i.e., yield scaled GWP) in the double rice cropping system. In addition, warming increased the abundance of ammoniaoxidising bacteria, ammoniaoxidising archaea, and a nitrite reductase gene (nirS), but decreased that of a nitrous oxide reductase gene (nosZ). Our results indicate that warming by FATI does not affect grain yield and CH4 emissions but stimulates N2O emissions in the double rice cropping system and therefore promotes a potential positive feedback with future climate warming.
      原文链接:
    • NSTL
    • Elsevier

    Bayesian inference of spatially correlated random parameters for on-farm experiment

    Cao, ZhanglongStefanova, KatiaGibberd, MarkRakshit, Suman...
    16页
    查看更多>>摘要：Accounting for spatial variability is crucial while estimating treatment effects in large on-farm trials. It allows to determine the optimal treatment for every part of a paddock, resulting in a management strategy that improves sustainability and profitability of the farm. We specify a model with spatially correlated random parameters to account for the spatial variability in large on-farm trials. A Bayesian framework has been adopted to estimate the posterior distribution of these parameters. By accounting for spatial variability, this framework allows the estimation of spatially-varying treatment effects in large on-farm trials. Several approaches have been proposed in the past for assessing spatial variability. However, these approaches lack an adequate discussion of the po-tential problem of model misspecification. Often the Gaussian distribution is assumed for the response variable, and this assumption is rarely investigated. Using Bayesian post sampling tools, we show how to diagnose the problem of model misspecification. To illustrate the applicability of our proposed method, we analysed a real on -farm strip trial from Las Rosas, Argentina, with the main aim of obtaining a spatial map of locally-varying optimal nitrogen rates for the entire paddock. The analysis of these data revealed that the assumption of Gaussian distribution for the response variable is unsatisfactory; the Student -t distribution provides a more robust inference. We finish the paper by discussing the difference between the proposed Bayesian approach and geographically weighted regression, and comparing the results of these two approaches.
      原文链接:
    • NSTL
    • Elsevier

    LINTUL-Cassava-NPK: A simulation model for nutrient-limited cassava growth

    Adiele, J. G.Schut, A. G. T.Ezui, K. S.Giller, K. E....
    12页
    查看更多>>摘要：A solid understanding of the dynamics of plant nutrient requirements and uptake from the soil is needed to provide robust fertilizer recommendations, timing of applications and nutrient use efficiency. Our objective was to develop and test the ability of the crop model LINTUL-Cassava-NPK to simulate biomass growth and yield of cassava under nutrient-limited conditions. We used experimental data from six fields located in three different agro-ecologies in Nigeria: Rainforest Zone- Ogoja and Ikom (Cross River), Rainforest Transition Zone - Ekpoma (Edo) and Guinea Savanna Zone - Otukpo (Benue) over two consecutive growing seasons from 2016 to 2018. Nutrient stress in the model was implemented by combining N, P and K nutrition indices (NI) to account for the interaction of multiple nutrient limitations for crop growth. Nutrient uptake was determined by balancing demand and supply of nutrient equivalents. We parameterized and calibrated the model using observations from an experiment conducted under optimal growing conditions in Edo during the 2016 planting season. The model was then tested with data from experiments conducted in the 2017 season in Edo, Cross River and Benue. The model captured the uptake patterns of N, P and K well. Uptakes of N, P and K, and storage root yield were predicted with a small root mean squared error of 5.1 g N m(-2), 0.8 g P m(-2), 3.3 g K m(-2) and 308 g DM roots m(-2), with an R-2 of 0.7 - 0.8 for linear relationships between simulated and observed values. The time course of development of nutrient-limited yield of green leaves, stems and storage roots were simulated reasonably well. In general, the model responded aptly to both nutrient omissions and varying amounts of NPK. These findings increase our understanding of nutrient limitations and N, P and K interactions on cassava growth and yield. The model provided insight into surplus amounts of nutrients in the soil at the end of the season and, specifically, the need to balance the supply of N and K for cassava. To our knowledge, this is the first tested cassava process-based model that includes the three macro-nutrients.
      原文链接:
    • NSTL
    • Elsevier

    Global analysis of yield benefits and risks from integrating trees with rice and implications for agroforestry research in Africa

    Rodenburg, JonneMollee, EefkeCoe, RichardSinclair, Fergus...
    18页
    查看更多>>摘要：While agroforestry is a well-established approach for agroecological intensification, rice is less often integrated with trees than other annual staple crops. The benefits and risks from rice agroforestry practices have not been systematically explored. Considering the need for strategies that may address low fertility and high degradation of arable soils and contribute to smallholder farm productivity, livelihoods and climate resilience, such explo-ration would both be timely and relevant. This study, therefore, reviews the published literature on integrating trees in rice production worldwide and provides perspectives for future research, with special attention to Africa, where the potential for sustainable productivity enhancement is deemed highest. Worldwide, six improved rice agroforestry practices are distinguished: hedgerow alley-cropping, short-term (0.5-4 years) improved fallows, pre-rice green manuring, biomass transfer, systematically arranged rice - tree intercropping and irregularly dispersed trees in fields. The rice agroforestry practices in the 87 publications reviewed were associated with 204 woody perennial species world-wide. Rice agroforestry practices provide a range of products and services to farmers but rice yield is the only quantitative performance indicator reported widely enough to enable meta-analysis. Frequently reported comparative or additional effects of fertilizer application, made it possible to include this aspect in the analyses. Across all types of agroforestry practices enumerated, the average effect of adding trees compared to a no-fertilizer and no-tree control is + 38%. The most beneficial practices in terms of enhancing rice yield were biomass transfer, pre-rice green manuring (100% of data points showing positive responses for both practices) and hedgerow alley-cropping (21% positive cases overall but 64% where fertilizer was not applied). Yield reductions occurred with fertilized intercropping compared to a fertilized mono-crop (in 95% of cases) and with the unfertilized short fallow practice (50% of data points showed yield reduction due to competition in the relay intercropping stage). Tree species that combined rice yield enhancements (alongside other products and services) with wide environmental adaptability across the African continent, include Sesbania rostrata, Aeschynomene afraspera, Acacia auriculiformis, Gliricidia sepium and Gmelia arborea. Yield benefits and risks from integrating trees with smallholder rice cropping depend on the type of agroforestry practice used and how each practice interacts with fertilizer application. Further research is needed to investigate the impact of different ways of integrating trees with rice cropping on wider environmental, social and economic sustainability aspects, that are driving increasing interest in rice agroforestry.
      原文链接:
    • NSTL
    • Elsevier

    Delayed sowing date improves the quality of mechanically transplanted rice by optimizing temperature conditions during growth season

    Deng, FeiZhang, ChiHe, LianhuaLiao, Shuang...
    8页
    查看更多>>摘要：Given the expected increase in global warming, rice production has been predicted to face increased frequency and intensity of high temperature (HT) stress in the future. Adjusting the sowing date is a low-cost and helpful strategy for overcoming the negative impact of HT; however, the effect of delayed sowing on rice quality is not well understood. In this study, field experiments with two varieties were conducted at Nanbu, Shehong, Anzhou, and Dayi in Sichuan Province in 2018 and 2019. Seeds were sown at conventional sowing date 1 (CS1), conventional sowing date 2 (sowing 10 days after CS1), delayed sowing date 1 (sowing 30 days after CS1), and delayed sowing date 2 (sowing 40 days after CS1). The amylose content (AC), protein content (PC), and temperature conditions during the rice growth season could explain 74.5% and 74.6% of the total variation in rice chalk grain rate (CGR) and chalkiness degree (CD), respectively. Delayed sowing date treatment markedly increased the daily mean (MT), maximum (MaT), minimum (MiT), and effective accumulated temperatures before heading but decreased these temperatures (including temperature difference) after heading. These changes contributed to an increase in AC and a decrease in PC, CGR, and CD of rice. The findings demonstrated that MT, MaT, and MiT values greater than 23.1 degrees C, 28.3 degrees C, and 19.4 degrees C before heading, and lower than 25.7 degrees C, 31.1 degrees C, and 22.2 degrees C after heading are necessary for improving the quality of mechanically transplanted rice. The study suggests that attaining optimal temperature conditions to improve the grain quality of mechanically transplanted rice in southwest China can be achieved by delaying the sowing date.
      原文链接:
    • NSTL
    • Elsevier

    Quantification and dynamic monitoring of nitrogen utilization efficiency in summer maize with hyperspectral technique considering a non-uniform vertical distribution at whole growth stage

    Li, LantaoChang, LuyiJi, YanruQin, Ding...
    17页
    查看更多>>摘要：As one of the most mobile indicators, nitrogen utilization (assimilation) efficiency (NUtE) exhibits a pronounced heterogeneity in its vertical distribution in summer maize canopies. Although the vertical heterogeneity of summer maize NUtE has been recognized, the vertical NUtE gradient in canopies has not been considered in canopy hyperspectral remote sensing (CHRS) so far. The main goal of this study was to quantitatively define the effects of the interactive changes in N nutrition and growth stages on the vertical distribution of NUtE, identify the sensitive leaf layers and effective wavelengths, and develop a monitoring model considering the vertical NUtE distribution using canopy hyperspectral data. Four field experiments were conducted for three consecutive years (2018-2020) to demonstrate how the maize canopies influences the CHRS estimation of NUtE distribution in the vertical canopy at different growth stages. Canopies of each treatment were divided into three layers of equal vertical at elongation stage (V6) and flare opening stage (V12) (i.e., 1st layer, 2nd layer and 3rd layer), and four layers at silking stage (R1), filling stage (R2) and milk stage (R3) (i.e., 1st layer, 2nd layer, 3rd layer and 4th layer). Continuous wavelet transform (CWT) was ufsed to process the collected spectral reflectance; partial least square (PLS) and lambda-lambda r(2) (LL r(2)) models were applied to analyze the relationships between NUtE in different layer and the spectral reflectance. Results showed that a vertical distribution pattern of NUtE existed, presenting an evident increase characteristics from the upper to lower layer. CWT technique can significantly improve the monitoring accuracy of summer maize NUtE in different layers among various growth stages, and the best decomposition scales are CWT-4, CWT-5, and CWT-6. The PLS model for NUtE prediction in the three decomposition scales yielded a relatively higher accuracy compared to the canopy raw spectra based on the full range hyperspectra, however, the prediction accuracy varied greatly in different layers and growth stages, the effect of the 2nd layer and 3rd layer and earlier stages were the best. The effective wavelengths for NUtE estimation were exhibited significant differences among the different layers and growing stages. Compared with the upper layer and V6-V12 stage, a strong "red shift" phenomenon towards the longer wavelengths was observed at lower layer and R1-R3 stage. Additionally, the newly developed PLS model using the effective wavelengths at different growth stages for NUtE prediction in various leaf layers also performed well (RPD>1.40). These findings will provide theoretical basis and effective methods for applying CHRS technology to real-time detection of NUtE and high yield and high efficiency of crop precision management for summer maize.
      原文链接:
    • NSTL
    • Elsevier