Influence of semi-arid environment on radiation use efficiency and other growth attributes of lentil crop.

Solar radiation (SR) is essential for yield improvement in lentil, which is a crop of marginal environments. Herein, experiments were conducted over 2 years under a semi-arid environment to study the radiation interception (RI), efficiency, growth, and development of three lentil genotypes (Punjab Masoor-2009 (PM-2009), NIAB Masoor-2006 (NM-2006), and NIAB Masoor-2002 (NM-2002)) in relation to three nitrogen rates (13, 19, and 25 kg ha-1). Seasonal dynamics of intercepted photoactive radiation (IPAR) and cumulated photosynthetic photon flux density were highly associated with seasonal dynamics of leaf area index (LAI), with a high value of R2 (0.93 and 0.89) across all nitrogen rates and genotypes in both years. Nitrogen application promoted growth, and maximum LAI (3.97 and 3.57) and RI (324 and 301 MJ m-2) were attained for the first and second years of study, respectively. Biomass and yield were positively associated with IPAR. Variation in radiation absorption (RA) among genotypes was due to different patterns of LAI development. In both years, yield (23% and 25%) and radiation use efficiency (RUE) for grain yield (0.44 and 0.37 g MJ-1) were respectively higher for PM-2009 than for the other genotypes. Genotype PM-2009 had 15 days shorter crop cycle than others while 14% higher GDDs accumulated in the first year compared with the second due to the higher temperature. High nitrogen (25 kg ha-1) application resulted in higher dry matter (DM), and grain yield (GY), while RUE and PAR were not statistically different under 19 kg N ha-1 application across years. Genotypes PM-2009 and NM-2006 may perform reasonably well under arid to semi-arid regions at farmer field. These findings may assist researchers and crop modelers to optimize the lentil ideotype for efficient light utilization.

Copper-induced oxidative stress, initiation of antioxidants and phytoremediation potential of flax (Linum usitatissimum L.) seedlings grown under the mixing of two different soils of China.

Flax (Linum usitatissimum L.), one of the oldest cultivated crops, continues to be widely grown for oil, fiber and food. Furthermore, the plants show a metal tolerance dependent on species so is ideal for research. Present study was conducted to find out the influence of copper (Cu) toxicity on plant biomass, growth, chlorophyll content, malondialdehyde (MDA) contents, proline production, antioxidative enzymes and metal up taken by L. usitatissimum from the soil grown under mixing of Cu-contaminated soil with natural soil by 0:1 (control), 1:0, 1:1, 1:2 and 1:4. Results revealed that, high concentration of Cu in the soil affected plant growth and development by reducing plant height, plant diameter and plant fresh and dry biomass and chlorophyll contents in the leaves compared with the control. Furthermore, Cu in excess causes generation of reactive oxygen species (ROS) such as superoxide radical (O-) and hydroxyl radicals (OH), which is manifested by high malondialdehyde (MDA) and proline contents also. The increasing activities of superoxidase dismutase (SOD) and peroxidase (POD) in the roots and leaves of L. usitatissimum are involved in the scavenging of ROS. Results also showed that L. usitatissimum also has capability to revoke large amount of Cu from the contaminated soil. As Cu concentration in the soil increases, the final uptake of Cu concentration by L. usitatissimum increases. Furthermore, the soil chemical parameters (pH, electrical conductivity and cation exchange capacity) were increasing to highest levels as the ratio of Cu concentration to the natural soil increases. Thus, Cu-contaminated soil is amended with the addition of natural soil significantly reduced plant growth and biomass, while L. usitatissimum is able to revoke large amount of Cu from the soil and could be grown as flaxseed and a potential candidate for phytoremediation of Cu.

Alteration in yield and oil quality traits of winter rapeseed by lodging at different planting density and nitrogen rates.

Lodging is a factor that negatively affects yield, seed quality, and harvest ability in winter rapeseed (Brassica napus L.). In this study, we quantified the lodging-induced yield losses, changes in fatty acid composition, and oil quality in rapeseed under different nitrogen application rates and planting densities. Field experiments were conducted in 2014-2017 for studying the effect of manually-induced lodging angles (0°, 30°, 60°, and 90°), 10, 20 and 30 d post-flowering at different densities and nitrogen application rates. The fertilization/planting density combination N270D45 produced the maximum observed yield and seed quality. Timing and angle of lodging had significant effects on yield. Lodging at 90° induced at 10 d post-flowering caused the maximum reduction in yield, biomass, and silique photosynthesis. Seed yield losses were higher at high N application rates, the maximum being at N360D45. Lodging decreased seed oil content and altered its fatty acid composition by increasing stearic and palmitic acid content, while decreasing linoleic and linolenic acid content, and deteriorating oil quality by increasing erucic acid and glucosinolate content. Therefore, lodging-induced yield loss and reduction in oil content might be reduced by selecting optimum N level and planting density.

Estimation of Dynamic Canopy Variables Using Hyperspectral Derived Vegetation Indices Under Varying N Rates at Diverse Phenological Stages of Rice.

Non-destructive and rapid estimation of canopy variables is imperative for predicting crop growth and managing nitrogen (N) application. Hyperspectral remote sensing can be used for timely and accurate estimation of canopy physical and chemical properties; however, discrepancies associated with soil and water backgrounds complicate the estimation of crop N status using canopy spectral reflectance (CSR). This study established the quantitative relationships between dynamic canopy nitrogen (CN) status indicators, leaf dry weight (LDW), leaf N concentration (LNC), leaf N accumulation (LNA), and CSR-derived new hyperspectral vegetation indices (HVIs), and to access the plausibility of using these relationships to make in-season estimations of CN variables at the elongation (EL), booting (BT), and heading (HD) stages of rice crop growth. Two-year multi-N rate field experiments were conducted in 2015 and 2016 in Hubei Province, China, using the rice cultivar Japonica. The results showed that the sensitive spectral regions were negatively correlated with CN variables in the visible (400-720 nm and 560-710 nm) regions, and positively correlated (r > 0.50, r > 0.60) with red and NIR (720-900 nm) regions. These sensitive regions are used to formulate the new (SR777/759, SR768/750) HVIs to predict CN variables at the EL, BT, and HD stages. The newly developed stepwise multiple linear regression (SMLR) models could efficiently estimate the dynamic LDW at the BT stage and LNC and LNA at the HD stage. The SMLR models performed accurately and robustly when used with a validation data set. The projected results offer a suitable approach for rapid and accurate estimation of canopy N-indices for the precise management of N application during the rice growth period.

Evaluating Hyperspectral Vegetation Indices for Leaf Area Index Estimation of Oryza sativa L. at Diverse Phenological Stages.

Hyperspectral reflectance derived vegetation indices (VIs) are used for non-destructive leaf area index (LAI) monitoring for precise and efficient N nutrition management. This study tested the hypothesis that there is potential for using various hyperspectral VIs for estimating LAI at different growth stages of rice under varying N rates. Hyperspectral reflectance and crop canopy LAI measurements were carried out over 2 years (2015 and 2016) in Meichuan, Hubei, China. Different N fertilization, 0, 45, 82, 127, 165, 210, 247, and 292 kg ha-1, were applied to generate various scales of VIs and LAI values. Regression models were used to perform quantitative analyses between spectral VIs and LAI measured under different phenological stages. In addition, the coefficient of determination and RMSE were employed to evaluate these models. Among the nine VIs, the ratio vegetation index, normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), modified triangular vegetation index (MTVI2) and exhibited strong and significant relationships with the LAI estimation at different phenological stages. The enhanced vegetation index performed moderately. However, the green normalized vegetation index and blue normalized vegetation index confirmed that there is potential for crop LAI estimation at early phenological stages; the soil-adjusted vegetation index and optimized soil-adjusted vegetation index were more related to the soil optical properties, which were predicted to be the least accurate for LAI estimation. The noise equivalent accounted for the sensitivity of the VIs and MSAVI, MTVI2, and NDVI for the LAI estimation at phenological stages. The results note that LAI at different crop phenological stages has a significant influence on the potential of hyperspectral derived VIs under different N management practices.