Establishment of an NPK nutrient monitor system in yield-graded cotton petioles under drip irrigation.

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.

Effect of different NPK fertilization timing sequences management on soil-petiole system nutrient uptake and fertilizer utilization efficiency of drip irrigation cotton.

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.

Electrolyte Salts and Additives Regulation Enables High Performance Aqueous Zinc Ion Batteries: A Mini Review.

Aqueous zinc ion batteries (ZIBs) are regarded as one of the most ideally suited candidates for large-scale energy storage applications owning to their obvious advantages, that is, low cost, high safety, high ionic conductivity, abundant raw material resources, and eco-friendliness. Much effort has been devoted to the exploration of cathode materials design, cathode storage mechanisms, anode protection as well as failure mechanisms, while inadequate attentions are paid on the performance enhancement through modifying the electrolyte salts and additives. Herein, to fulfill a comprehensive aqueous ZIBs research database, a range of recently published electrolyte salts and additives research is reviewed and discussed. Furthermore, the remaining challenges and future directions of electrolytes in aqueous ZIBs are also suggested, which can provide insights to push ZIBs' commercialization.

Estimation of nitrate nitrogen content in cotton petioles under drip irrigation based on wavelet neural network approach using spectral indices.

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.

[Dynamics simulation on plant growth, N accumulation and utilization of processing tomato at different N fertilization rates].

Three field experiments were conducted to simulate the dynamics of aboveground biomass, N accumulation and utilization of drip-irrigated processing tomatoes at different N fertilization rates (0, 75, 150, 300, 450, or 600 kg x hm(-2)). The results showed that Logistic models best described the changes in aboveground biomass, N accumulation, and utilization of accumulated N efficiency with the physiological development time (PDT). Rapid accumulation of N began about 4-6 d (PDT) earlier than the rapid accumulation of aboveground biomass. The momentary utilization rate of N (NMUR) increased after emergence, reached a single peak, and then decreased. The N accumulation, aboveground biomass and yield were highest in the 300 kg x hm(-2) treatment. The quadratic model indicated that application rate of 349 to 382 kg N x hm(-2) was optimum for drip-irrigated processing tomatoes in northern Xinjiang.

Use of a digital camera to monitor the growth and nitrogen status of cotton.

The main objective of this study was to develop a nondestructive method for monitoring cotton growth and N status using a digital camera. Digital images were taken of the cotton canopies between emergence and full bloom. The green and red values were extracted from the digital images and then used to calculate canopy cover. The values of canopy cover were closely correlated with the normalized difference vegetation index and the ratio vegetation index and were measured using a GreenSeeker handheld sensor. Models were calibrated to describe the relationship between canopy cover and three growth properties of the cotton crop (i.e., aboveground total N content, LAI, and aboveground biomass). There were close, exponential relationships between canopy cover and three growth properties. And the relationships for estimating cotton aboveground total N content were most precise, the coefficients of determination (R(2)) value was 0.978, and the root mean square error (RMSE) value was 1.479 g m(-2). Moreover, the models were validated in three fields of high-yield cotton. The result indicated that the best relationship between canopy cover and aboveground total N content had an R(2) value of 0.926 and an RMSE value of 1.631 g m(-2). In conclusion, as a near-ground remote assessment tool, digital cameras have good potential for monitoring cotton growth and N status.

Rice photosynthetic productivity and PSII photochemistry under nonflooded irrigation.

Nonflooded irrigation is an important water-saving rice cultivation technology, but little is known on its photosynthetic mechanism. The aims of this work were to investigate photosynthetic characteristics of rice during grain filling stage under three nonflooded irrigation treatments: furrow irrigation with plastic mulching (FIM), furrow irrigation with nonmulching (FIN), and drip irrigation with plastic mulching (DI). Compared with the conventional flooding (CF) treatment, those grown in the nonflooded irrigation treatments showed lower net photosynthetic rate (PN), lower maximum quantum yield (Fv/Fm), and lower effective quantum yield of PSII photochemistry (ΦPSII). And the poor photosynthetic characteristics in the nonflooded irrigation treatments were mainly attributed to the low total nitrogen content (TNC). Under non-flooded irrigation, the PN, Fv/Fm, and ΦPSII significantly decreased with a reduction in the soil water potential, but these parameters were rapidly recovered in the DI and FIM treatments when supplementary irrigation was applied. Moreover, The DI treatment always had higher photosynthetic productivity than the FIM and FIN treatments. Grain yield, matter translocation, and dry matter post-anthesis (DMPA) were the highest in the CF treatment, followed by the DI, FIM, and FIN treatments in turn. In conclusion, increasing nitrogen content in leaf of rice plants could be a key factor to improve photosynthetic capacity in nonflooded irrigation.

Rice performance and water use efficiency under plastic mulching with drip irrigation.

Plastic mulching with drip irrigation is a new water-saving rice cultivation technology, but little is known on its productivity and water-saving capacity. This study aimed to assess the production potential, performance, and water use efficiency (WUE) of rice under plastic mulching with drip irrigation. Field experiments were conducted over 2 years with two rice cultivars under different cultivation systems: conventional flooding (CF), non-flooded irrigation incorporating plastic mulching with furrow irrigation (FIM), non-mulching with furrow irrigation (FIN), and plastic mulching with drip irrigation (DI). Compared with the CF treatment, grain yields were reduced by 31.76-52.19% under the DI treatment, by 57.16-61.02% under the FIM treatment, by 74.40-75.73% under the FIN treatment, which were mainly from source limitation, especially a low dry matter accumulation during post-anthesis, in non-flooded irrigation. WUE was the highest in the DI treatment, being 1.52-2.12 times higher than with the CF treatment, 1.35-1.89 times higher than with the FIM treatment, and 2.37-3.78 times higher than with the FIN treatment. The yield contribution from tillers (YCFTs) was 50.65-62.47% for the CF treatment and 12.07-20.62% for the non-flooded irrigation treatments. These low YCFTs values were attributed to the poor performance in tiller panicles rather than the total tiller number. Under non-flooded irrigation, root length was significantly reduced with more roots distributed in deep soil layers compared with the CF treatment; the DI treatment had more roots in the topsoil layer than the FIM and FIN treatments. The experiment demonstrates that the DI treatment has greater water saving capacity and lower yield and economic benefit gaps than the FIM and FIN treatments compared with the CF treatment, and would therefore be a better water-saving technology in areas of water scarcity.

[Simulation model for the development stages of processing tomato based on physiological development time].

After the comprehensive consideration of the effects of temperature and light on the development physiology of processing tomato, the intrinsic development factor (IDF) was introduced, and, through the analysis of the dynamic relationships between the development stages of different type processing tomato and related environmental factors, the simulation model for the development stages of processing tomato was constructed, based on the concept of physiological development time (PDTv). Different years' experimental data about ecological zones, varieties, and planting modes were used to validate the model. The simulated results about the number of days from sowing to seedling emergence, flowering, fruit-setting, maturing, and ending accorded well with the observed ones, the root mean squared error (RMSE) being 1.09, 2.03, 2.05, 2.77 and 2.53 days, respectively, and the prediction accuracy of this model was significantly higher than that of the growth degree day (GDD)-based model, with the corresponding RMSE being 1.90, 6.63, 6.33, 9.36 and 6.84 days, respectively.

[A physiological development time-based simulation model for cotton development stages and square- and boll formation].

In this study, three cotton varieties (CRI 36, CRI 35 and CRI 41) were planted in Nanjing, Anyang, Baoding and Shihezi, respectively, in 2002, and the dynamic relationships between their development and environmental factors were analyzed. Based on this, a simulation model for cotton development stages and square-and boll development was built in terms of physiological development time (PDT). In calculating relative thermal effectiveness, the effect of diurnal temperature differences in different regions on cotton development was incorporated, and the enhancement of plastic mulching on air temperature was quantified. To simulate development stages, the initial fruiting node index (IFIN), sunlight duration factor (FSH), and solar radiation index on fruiting branch (IFBR) were introduced, besides earliness factor of a given genotype. The validation of the model with the data obtained from different years, ecological zones, genotypes, and cultivation practices indicated a high goodness of fitness between the simulated results and observed values. The root mean square error (RMSE) between simulated and observed days from sowing to emergence, emergence to squaring, anthesis to boll opening, and sowing to boll opening was 0.9, 2.2, 1.7, and 2.1 d, respectively, with a mean of 2.1 d, and in all plant sites, the RMSE between simulated and observed days from squaring to boll opening was 1.8-3.7 d, and that from squaring to opening was 4.6-5.8 d.

[Quantitative analysis on the relationships between cotton fiber quality and meteorological factors].

With the method of planting cotton by stages at the sites from Yangtze valley to north Xinjiang, this paper studied the effects of air temperature and sunlight on cotton fiber quality in 2002 approximately 2003. The results showed that with increasing latitude, fiber length increased, while micronaire value and soluble sugar content (SSC) decreased. An ecological model describing the relationships of fiber strength, micronaire value and SSC with air temperature and sunlight was built to determine the optimal range and critical value of air temperature during boll development period. If a high quality fiber (length > or = 27 mm) was targeted, the daily mean temperature (DMT) and minimum temperature (Tmin) during this period should be 21.3 approximately 29.7 and 10.7 approximately 21.3 degrees C, respectively, and the daily temperature difference (DTD) should not be > 15.2 degrees C. Fiber length was the longest when the DMT was 25.4 degrees C. If the lowest fiber length was > or = 25 mm, DMT and Tmin should not be lower than 15.5 and 10.7 degrees C, respectively, and DTD should not be over 17.9 degrees C during boll development period.

[Principle of "multiple ecological niche of one-species (variety)" and its application in high yield cotton cultivation].

The multiple ecological niche of one-species (variety) (MENOS) population is formed by one species (variety), but the ecological units have different temporal, spatial, nutritional, temperature, or water ecological niche. The formation of MENOS population is characterized by its specific object, one species (variety), multiple layer canopy, human being's active adjustment, specific niche breadth, and overlap and separation of ecological units. This paper analyzed the characteristics of the super high yield cotton population with dual ecological niche of one-species (variety) (DENOS). As for the yield components, MENOS has the characteristics of high yield canopy and different yield plants.