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Relationships between crop evapotranspiration (ET) and soil water content (SWC) have been studied worldwide. However, traditional data processing has drawbacks in modeling the contribution of SWC to ET on a layer-to-layer basis. To address this issue, large-scale weighing lysimeters were used to monitor the real-time ET along with Insentek sensors to monitor daily SWC dynamics of summer maize at Xuchang Experimental Irrigation Station, North China Plain, in 2016 and 2017. At the vegetative stage of maize (V6 and V12), roots reached 70 cm deep, with an average root length density (RLD) of 0.55 cm cm−3. Mean RLD at reproductive stage (VT and R3) was 1.13 cm cm−3, and the roots reached 100 cm deep. Cumulative percentage of ETi to ET in topsoil (0–30 cm) was from 66% (V6) to 77% (R3), with the lowest proportion of 62% at maturity (R6), indicating > 2/3 of root mass distributed in the 0–30 cm soil layer. Principal component analysis was conducted to extract principal components of SWC. Soil moisture in the top (0–30 cm), middle (30–60 cm), and deep (60–100 cm) soil layers explained 8%, 14%, and 31% of the variances in ET (P

The non-destructive estimation of plant nitrogen (N) status is imperative for timely and in-season crop N management. The objectives of this study were to use canopy cover (CC) to establish the empirical relations between plant growth indices [shoot dry matter (SDM), leaf area index (LAI), shoot N accumulation (SNA), shoot nitrogen concentration (SNC)], and CC as well as to test the feasibility of using CC to assess N nutrition index (NNI) from Feekes 3 to Feekes 6 stages of winter wheat. Four multi-locational (2 sites), multi-cultivars (four cultivars), and multi-N rates (0–300 kg N ha–1) field experiments were carried out during 2016 to 2018 seasons. The digital images of the canopy were captured by a digital camera from Feekes 3 to Feekes 6 stages of winter wheat, while SDM, LAI, SNA, and SNC were measured by destructive plant sampling. CC was calculated from digital images developed by self-programmed software. CC showed significant correlations with growth indices (SDM, LAI, and SNA) across the different cultivars and N treatments, except for SNC. However, the stability of these empirical models was affected by cultivar characteristics and N application rates. Plant N status of winter wheat was assessed using CC through two methods (direct and indirect methods). The direct and indirect methods failed to develop a unified linear regression to estimate NNI owing to the high dispersion of winter wheat SNC during its early growth stages. The relationships of CC with SDM, SNC and NNI developed at individual growth stages of winter wheat using both methods were highly significant. The relationships developed at individual growth stages did not need to consider the effect of N dilution process, yet their stability is influenced by cultivar characteristics. This study revealed that CC has larger limitation to be used as a proxy to manage the crop growth and N nutrition during the early growth period of winter wheat despite it is an easily measured index.

Injudicious nitrogen (N) fertilizer application has increased the risk of environmental pollution and decreased grain yields, farm profits, and N use efficiency. The plant based N diagnostic tools can be used to optimize N management of summer maize production. This study was designed to develop and validate a leaf area index (LAI) based critical N (Nc) dilution curve and to establish a theoretical framework to link the relationship of LAI and plant dry matter (DM) based curves, as well as to compare the differences between LAI, plant DM and growth stage-based Nc curves. Six field experiments were set with a range of N application rates (0–320 kg N ha−1) and plant densities (6 to 8 × 104 plants ha-1) using four summer maize cultivars (Zhengdan958, Denghai605, Xundan20, and Denghai661) in Henan province of China. LAI and plant N concentration (PNC) were determined from V6 to R1 stages in each experiment for the development of the Nc curve. LAI and PNC ranged from 1.28 to 6.12 and 1.34% to 3.31% under different N levels, respectively. Allometric relationships between LAI, plant DM, and critical N uptake (Nuc) were developed under non-N-limiting treatments. The relationship between Nc and LAI during vegetative growth period was described by a power function (Nc = 3.84LAI−0.45). N nutrition index (NNI) increased with the increasing N application rate and ranged from 0.56 and 1.23 across different N treatments. Our results validated that plant N uptake was proportional with LAI, and the allometric parameter between LAI and plant DM of summer maize was close to the theoretical value 2/3. The newly developed LAI-based Nc curve could identify plant N status (N-limiting and non-N-limiting) during key N requirement period of summer maize and can be used for precision N management for summer maize grown in China.

Accurate diagnosis of nitrogen (N) fertilizer required for crop growth can serve as a guide for N management by improving N use efficiency and grain yields. The critical N concentration (Nc), the minimum N required for maximal crop growth has been widely used to determine crop N status. Nc dilution curves have been determined in several crops including summer maize on plant dry matter (DM) basis, yet no attempt has been made to determine the Nc dilution curve on the basis of leaf dry matter (LDM) in summer maize. The present study aimed to determine a Nc dilution curve based on LDM for in-season assessment of crop N status in summer maize. Six field experiments were performed with four summer maize cultivars using varied N fertilizer rates ranging from 0 to 320 kg N ha−1. The leaf Nc curve was described by the equation: Nc = 3.45LDM−0.22, when LDM ranged from 1.18 to 3.45 t ha−1. For LDM

Rapid, accurate and dynamic diagnosis of nitrogen (N) status is essential for evaluating plant vigor, predicting crop production and optimizing N management in winter barley (Hordeum vulgare L.). The objectives of this study were to determine the correlations between N nutrition index (NNI), leaf N gradient and chlorophyll meter (CM) readings gradient for different leaf positions and to compare the stability of the relationships between NNI and CM readings as well as between NNI and positional differences chlorophyll measurements index (PDCMI) in different cultivars and environments. Four multi-locational field experiments using five winter barley cultivars (Supi6, Yangpi4, Yangnongpi8, Supi2, Dan2) and varied N rates (0–300 kg ha−1) were conducted in this study. NNI, leaf N gradient, CM readings, CM readings gradient and PDCMI were determined for growth analyses from Feekes 6 to Feekes 10.51. Our results represented that the NNI and CM readings increased with increasing N application rates. In contrast, the PDCMI decreased with increasing N application rates. Further, the leaf N gradient of the canopy was not uniform, the lower leaf position could better reflect N status in winter barley plants, and the CM readings gradient was a good proxy of leaf N gradient. The CM readings at different leaf positions showed a significantly positive relatation to NNI, yet the relationship varied among cultivars and seasons. In contrast, the PDCMI of different leaves showed significantly negative relation to NNI, with the exception of PDCMI12 and PDCMI13. The strongest correlation between NNI and PDCMI was found for PDCMI14 (NNI = −1.927 × PDCMI14 + 1.17, R = –0.838**), which was stable across the cultivars and seasons. Validation of the relationships with independent data produced a root mean squared error (RMSE) of 0.13 between the predicted and observed NNI values. This robust and stable relationship between PDCMI14 and NNI could be used as a reliable tool to diagnose plant N status of winter barley in eastern China.

Silicon (Si) enhances maize resistance to drought. While previous studies have mainly focused on the seedling stage, the mediation of drought stress by Si imposed at the vegetative and reproductive stages has been rarely investigated. A soil-column experiment was thus conducted under a rainproof shelter to quantify the effect s of Si application on the physiological and agronomic responses of maize to drought stress imposed at the 6-leaf (D-V6), 12-leaf (D-V12), and blister (D-R2) stages. The observed parameters included plant growth, photosynthesis, osmolytes, antioxidant activity, and grain yield. The results showed that drought stress strongly decreased the leaf area, leaf water content, photosynthetic rate, chlorophyll content, and antioxidant activity (superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT)) and markedly increased lipid peroxidation. D-V6, D-V12, and D-R2 decreased grain yields by 12.9%, 28.9%, and 44.8%, respectively, compared to the well-watered treatment (CK). However, Si application markedly increased leaf area, chlorophyll content, photosynthetic rate, osmolyte content, and enzymatic antioxidant activities (SOD, POD, and CAT), and decreased malondialdehyde (MDA) and superoxide radical accumulation, ultimately improving maize yields by 12.4%, 69.8%, and 80.8%, respectively, compared to the non-Si treated plants under drought stress at the V6, V12, and R2 stages. Furthermore, maize yields had a significant positive correlation with chlorophyll content and SOD and POD activity during the three stages. Our findings suggest that Si-induced changes in chlorophyll content and antioxidant activity might constitute important mechanisms for mitigating drought stress. In conclusion, this study provides physico-biochemical evidence for the beneficial role of Si in alleviating drought-induced yield reduction in maize, particularly during the late vegetative or early reproductive stages. Thus, Si application constitutes an effective approach for improving maize yield in rain-fed agricultural systems.

Crop evapotranspiration (ETc) simulation is important to modeling hydrological process in agro-ecosystem. In this study, ETc was monitored using a large-scale weighing lysimeter system, along with Insentek soil moisture probes at Xuchang Irrigation Experiment Station in 2015 and 2016. Relationships among daily ETc, leaf area index (LAI) and soil water content (SWC) were determined using the Levenberg–Marquardt Algorithm. Our results showed that ETc was significantly correlated with SWC in 0-40 cm soil layers, but not correlated with SWC below 40 cm soil layer. ETc was related to SWC in an exponential function combined with a quadratic function. Effects of SWC in 0-30 cm soil layers accounted for 32-53% variations of ETc. Averaging SWC across the 0-30 cm soil depth, it contributed 46% variations of ETc. Moreover, ETc was correlated with LAI in a negative linear manner, but its correlation coefficient is not significant (P>0.05). We concluded that SWC at top soil layer can be adopted to calibrate Insentek ETc simulation for maize plants.

Rapid and non-destructive diagnostic tools to accurately assess crop nitrogen nutrition index (NNI) are imperative for improving crop nitrogen (N) diagnosis and sustaining crop production. This study was aimed to develop the relationships among NNI, leaf N gradient, chlorophyll meter (CM) readings gradient, and positional differences chlorophyll meter index [PDCMI, the ratio of CM readings between different leaf layers (LLs) of crop canopy] and to validate the accuracy and stability of these relationships across the different LLs, years, sites, and cultivars. Six multi-N rates (0–320 kg ha−1) field experiments were conducted with four summer maize cultivars (Zhengdan958, Denghai605, Xundan20, and Denghai661) at two different sites located in China. Six summer maize plants per plot were harvested at each sampling stage to assess NNI, leaf N concentration and CM readings of different LLs during the vegetative growth period. The results showed that the leaf N gradient, CM readings gradient and PDCMI of different LLs decreased, while the NNI values increased with increasing N supply. The leaf N gradient and CM readings gradient increased gradually from top to bottom of the canopy and CM readings of the bottom LL were more sensitive to changes in plant N concentration. The significantly positive relationship between NNI and CM readings of different LLs (LL1 to LL3) was observed, yet these relationships varied across the years. In contrast, the relationships between NNI and PDCMI of different LLs (LL1 to LL3) were significantly negative. The strongest relationship between PDCMI and NNI which was stable across the cultivars and years was observed for PDCMI1−3 (NNI = −5.74 × PDCMI1−3+1.5, R2 = 0.76**). Additionally, the models developed in this study were validated with the data acquired from two independent experiments to assess their accuracy of prediction. The root mean square error value of 0.1 indicated that the most accurate and robust relationship was observed between PDCMI1–3 and NNI. The projected results would help to develop a simple, non-destructive and reliable approach to accurately assess the crop N status for precisely managing N application during the growth period of summer maize crop.

A sustainable management strategy of soil fertility and cropping system is critical to guaranteeing food security. However, little is known about the effects of soil amendment strategies on crop growth via regulating soil moisture and photosynthesis in a ridge and furrow cropping system. Here, field experiments were carried out in 2017 and 2018 in semi-arid areas of Loess Plateau, northwest China to investigate the effects of integrated use of ridge and furrow planting and manure amendment on grain yields of maize. Four treatments were designed: CK (flat planting with 100% chemical fertilizer), RFC (ridge and furrow planting with 100% chemical fertilizer), RFR (ridge and furrow planting with 100% control-released fertilizer), and RFM (ridge and furrow planting with 50% manure fertilizer + 50% N fertilizer). On average, RFM increased photosynthetic rates (Pn) by 74%, followed by RFR by 47%, and RFC by 26%, compared to CK. Also, stomatal conductance (Cd), transpiration rates (Tr), and intercellular CO2 concentration (Ci) were highest with RFM, followed by RFR and RFC. Averaged across the two years, RFM conserved 10% more soil water storage (SWS) than CK did at harvest, followed by RFR with an increment by 8%. However, RFC consumed more soil water than CK did, with its ETc 8% higher than CK. Consequently, spring maize treated with RFM suffered less drought stress, especially in 2017 when precipitation was insufficient. On average, grain yields and water use efficiency of RFM were increased by 18% and 27%, compared to CK. Structural equation modeling analysis showed that there existed significant positive correlation between SWS in top layers and grain yields, while SWS in deep layers had negative effects on grain yields. In conclusion, the incorporation of manure into ridge and furrow planting system can be an efficient agronomic practice to improve plant photosynthesis, optimize soil moisture, and boost grain yields in semi-arid areas of Loess Plateau, northwest China.