Hyperspectral technology has enabled rapid and efficient nitrogen monitoring in crops. However, most approaches involve direct monitoring of nitrogen content or physiological and biochemical indicators directly related to nitrogen, which cannot reflect the overall plant nutritional status. Two important photosynthetic traits, the fraction of absorbed photosynthetically active radiation (FAPAR) and the net photosynthetic rate (Pn), were previously shown to respond positively to nitrogen changes. Here, Pn and FAPAR were used for correlation analysis with hyperspectral data to establish a relationship between nitrogen status and hyperspectral characteristics through photosynthetic traits. Using principal component and band autocorrelation analyses of the original spectral reflectance, two band positions (350–450 and 600–750 nm) sensitive to nitrogen changes were obtained. The performances of four machine learning algorithm models based on six forms of hyperspectral transformations showed that the light gradient boosting machine (LightGBM) model based on the hyperspectral first derivative could better invert the Pn of function–leaves in cotton, and the random forest (RF) model based on hyperspectral first derivative could better invert the FAPAR of the cotton canopy. These results provide advanced metrics for non–destructive tracking of cotton nitrogen status, which can be used to diagnose nitrogen nutrition and cotton growth status in large farms.

The use of industrial waste as an agricultural resource is important for clean and sustainable agriculture. We assumed that industrial organic wastewater coupled with chemical fertilizer would increase cotton yield by enhancing nutrients absorption and utilization. To test this hypothesis, a two-year (2019–2020) field trial was conducted to assess the impacts of CK (0 kg ha⁻¹), chemical fertilizer (CF) (N-P2O5-K2O: 228-131-95 kg ha⁻¹), chemical fertilizer + organic wastewater (F0.6 (60%CF + OW: 1329 kg ha⁻¹), F0.8 (80%CF + OW), F1.0 (CF + OW), F1.2 (120%CF + OW) and F1.4 (140%CF + OW)) on nutrient absorption and distribution, fertilizer use efficiency and cotton yield under drip irrigation system. Compared with CF, the soil organic matter, NH4+-N and AV-K increased significantly after F0.8-F1.4 treatments. The absorption of nitrogen (N), phosphorus (P) and potassium (K) by plants after dripping organic wastewater (F0.8-F1.4) increased by 1.1–11.2% as compared with CF (F0.6, CF < F0.8, F1.0 < F1.2, F1.4). Under F0.8, treatment resulted in a higher distribution rate of N, P and K in reproductive organs compared with other counterparts. In addition, drip application of organic wastewater promoted the absorption of magnesium (Mg) and zinc (Zn) in leaves and Fe in roots with higher translocation of Zn and boron (B) to reproductive organs compared with other treatments. The absorption of N, P and K was positively correlated with Mg, negatively correlated with calcium (Ca) and sulfur (S), and positively correlated with manganese (Mn) and iron (Fe). The yield and fertilizer utilization rate of cotton were higher at F0.8. Conclusively, the use of 1329 kg ha⁻¹ organic wastewater (organic mattered ≥ 20%, humic acid ≥ 20 g L⁻¹, Bacillus subtilis ≥ 2 × 108 L⁻¹) combined with chemical fertilizer (N-P2O5-K2O) at (182-104-76 kg ha⁻¹) reduces the application of chemical fertilizer and can increase utilization efficiency of chemical fertilizer with a high cotton yield under mulch drip irrigation in arid regions.

With the promotion and popularization of machine cotton-picking, more and more attention has been paid to the selection of early-maturity varieties with compact plant architecture. The type of fruit branch is one of the most important factors affecting plant architecture and early maturity of cotton. Heredity analysis of the cotton fruit branch is beneficial to the breeding of machine-picked cotton. Phenotype analysis showed that the types of fruit branches in cotton are controlled by a single recessive gene. Using an F₂ population crossed with Huaxin102 (normal branch) and 04N-11 (nulliplex branch), BSA (Bulked Segregant Analysis) resequencing analysis and GhNB gene cloning in 04N-11, and allelic testing, showed that fruit branch type was controlled by the GhNB gene, located on chromosome D07. Ghnb5, a new recessive genotype of GhNB, was found in 04N-11. Through candidate gene association analysis, SNP 20_15811516_SNV was found to be associated with plant architecture and early maturity in the Xinjiang natural population. The GhNB gene, which is related to early maturity and the plant architecture of cotton, is a branch-type gene of cotton. The 20_15811516_SNV marker, obtained from the Xinjiang natural population, was used for the assisted breeding of machine-picked cotton varieties.