ABSTRACT
BACKGROUND: The determination of nutrient content in the petiole is one of the important methods for achieving cotton fertilization management. The establishment of a monitoring system for the nutrient content of cotton petioles during important growth periods under drip irrigation is of great significance for achieving precise fertilization and environmental protection. METHODS: A total of 100 cotton fields with an annual yield of 4500-7500 kg/ha were selected among the main cotton-growing areas of Northern Xinjiang. The nitrate nitrogen (NO3--N), inorganic phosphorus (PO43--P) and inorganic potassium (K+-K) content and yield of cotton petioles were recorded. Based on a yield of 6000 kg/ha as the dividing line, a two-level and yield-graded monitoring system for NO3--N, PO43--P and K+-K in cotton petioles during important growth periods was established, and predictive yield models for NO3--N, PO43--P and K+-K in petioles during important growth periods were established. RESULTS: The results showed found that the yields of the 100 cotton fields surveyed were normally distributed. Therefore, two yield grades were classified using 6000 kg/ha as a criterion. Under different yield-graded, the NO3--N, PO43--P and K+-K content of petiole at important growth stages was significantly positively correlated with yield. Further, the variation range of NO3--N, PO43--P and K+-K content in petioles could be used as a standard for yield-graded. In addition, a yield prediction model for the NO3--N, PO43--P and K+-K content of petioles was developed. The SSO-BP validation model performed the best (R2 = 0.96, RMSE = 0.06 t/ha, MAE = 0.05 t/ha) in the full bud stage, which was 12.9% higher than the BP validation model. However, the RMSE and MAE were decreased by 86.7% and 88.1%, respectively. CONCLUSION: The establishment of NPK nutrition monitor system of cotton petioles under drip irrigation based on yield-graded provides an important basis for nutrition monitor of cotton petiole under drip irrigation in Xinjiang. It also provides a new method for cotton yield prediction.
ABSTRACT
In order to elucidate the effects of different nitrogen (N), phosphorus (P), and potassium (K) fertilization timing sequences management on nutrient absorption and utilization in drip irrigation cotton, field experiments were conducted from 2020 to 2021. There are six timing sequences management methods for NPK fertilization (S1-S6: 1/3Time N-1/3Time PK-1/3Time W, 1/3Time PK-1/3Time N-1/3Time W, 1/2Time NPK-1/2Time W, 1/4Time W-1/4Time N-1/4Time PK-1/4Time W, 1/3Time W-1/3Time NPK-1/3Time W), among which S6 is the current management method for field fertilization timing sequences, and S7 is the non N. The results showed that during the main growth stage, S5 accumulated more nitrate nitrogen (NO3--N) and ammonium nitrogen (NH4+-N) content in soil between 20 and 40 cm, and accumulated more available phosphorus content in soil between 5-15 cm and 15-25 cm, S5 reducing N leaching and increasing P mobility. It is recommended to change the timing sequences management method of NPK fertilization for drip irrigation cotton to 1/4Time W-1/4Time PK-1/4Time N-1/4Time W, which is beneficial for plant nutrient absorption and utilization while reducing environmental pollution.
ABSTRACT
BACKGROUND: Estimation of nitrate nitrogen (NO3--N) content in petioles is one of the key approaches for monitoring nitrogen (N) nutrition in crops. Rapid, non-destructive, and accurate evaluation of NO3--N contents in cotton petioles under drip irrigation is of great significance. METHODS: In this study, we discussed the use of hyperspectral data to estimate NO3--N contents in cotton petioles under drip irrigation at different N treatments and growth stages. The correlations among trilateral parameters and six vegetation indices and petiole NO3--N contents were first investigated, after which a traditional regression model for petioles NO3--N content was established. A wavelet neural network (WNN) model for estimating petiole NO3--N content was also established. In addition, the performance of WNN was compared to those of random forest (RF), radial basis function neural network (RBF) and back propagation neural network (BP). RESULTS: Between the blue edge amplitude (Db) and blue edge area (SDb) of the blue edge parameters was the optimal index for the estimation model of petiole NO3--N content. We found that the prediction results of the blue edge parameters and WNN were 7.3% higher than the coefficient of determination (R2) of the first derivative vegetation index and WNN. Root mean square error (RMSE) and mean absolute error (MAE) were 25.2% and 30.9% lower than first derivative vegetation, respectively, and the performance was better than that of RF, RBF and BP. CONCLUSIONS: An inexpensive approach consisting of the WNN algorithm and blue edge parameters can be used to enhance the accuracy of NO3--N content estimation in cotton petioles under drip irrigation.
ABSTRACT
Recent reports exposed an astonishing factor of high hardness that the connection between transition-metal (TM) atoms could enhance hardness, which is in contrast to the usual understanding that TM-TM will weaken hardness as the source of metallicity. It is surprising that there are two opposite mechanical characteristics in the one TM-TM bond. To uncover the intrinsic reason, we studied two appropriate mononitrides, CrN and WN, with the same light-element (LE) content and valence electron concentration. The two high-quality compounds were synthesized by a new metathesis under high pressure, and the Vickers hardness is 13.0 GPa for CrN and 20.0 GPa for WN. Combined with theoretical calculations, we found that the strong correlation of d electrons in TM-TM could seriously affect hardness. Thus, we make the complementary suggestions of the previous hardness factors that the antibonding d-electron state in TM-TM near the Fermi level should be avoided and a strong d covalent coupling in TM-TM is very beneficial for high hardness. Our results are very important for the further design of high-hardness and multifunctional TM and LE compounds.
ABSTRACT
Amorphous carbon (a-C) films are attracting considerable attention to due their large optical band gap (Eopt) range of 1-4 eV. But the hopping conducting mechanism of boron doping a-C (a-C:B) is still mysterious. To exploring the intrinsic reasons behind the semiconductor properties of a-C:B, in this work, the boron doping a-C (a-C:B) nano-film was prepared, and the growth rate and Eopt changing were analyzed by controlling the different experimental conditions of magnetron sputtering. A rapid deposition rate of 10.55 nm/min was obtained. The Eopt is reduced from 3.19 eV to 2.78 eV by improving the substrate temperature and sputtering power. The proportion of sp2/sp3 increasing was uncovered with narrowing the Eopt. The shrinking Eopt can be attributed to the fact that boron atoms act as a fluxing agent to promote carbon atoms to form sp2 hybridization at low energy. Furthermore, boron atoms can impede the formation of σ bonds in carbon atom sp3 hybridization by forming B-C bonds with high energy, and induce the sp3 hybridization transfer to sp2 hybridization. This work is significant to further study of amorphous semiconductor films.
ABSTRACT
The D7b-type structure Mn3B4 was fabricated by high-temperature and high-pressure (HPHT) methods. Hardness examination yielded an asymptotic Vickers hardness of 16.3 GPa, which is much higher than that of Mn2B and MnB2. First principle calculations and XPS results demonstrated that double zigzag boron chains form a strong covalent skeletons, which enhances this structure's integrity with high hardness. Considering that the hardensses of MnB and Mn3B4 are higher than those of Mn2B and MnB2, zigzag and double zigzag boron backbones are superior to isolated boron and graphite-like boron layer backbones for achieving higher hardness. This situation also states that a higher boron content is not the sole factor for the higher hardness in the low boron content transition metal borides. Futhermore, the co-presence of metallic manganese bilayers contribute to the high d-electron mobility and generate electrical conductivity and antiferromagnetism in Mn3B4 which provide us with a new structure prototype to design general-purpose high hardness materials.
ABSTRACT
We report a robust honeycomb boron layers sandwiching manganese layers compound, MnB2, synthesized by high pressure and high temperature. First-principle calculation combined with X-ray photoelectron spectrum unravel that the honeycomb boron structure was stabilized by filling the empty π-band via grabbing electrons from manganese layers. Honeycomb boron layers sandwiching manganese layers is an extraordinary prototype of this type of sandwiched structure exhibiting electronic conductivity and ferromagnetism. Hydrostatic compression of the crystal structure, thermal expansion, and the hardness testing reveal that the crystal structure is of strong anisotropy. The strong anisotropy and first-principle calculation suggests that B-B bonds in the honeycomb boron structure are a strong directional covalent feature, while the Mn-B bonds are soft ionic nature. Sandwiching honeycomb boron layers with manganese layers that combine p-block elements with magnetic transition metal elements could endow its novel physical and chemical properties.
