Leaf photosynthetic pigments play a crucial role in evaluating nutritional elements and physiological states. In facility agriculture, it is vital to rapidly and accurately obtain the pigment content and distribution of leaves to ensure precise water and fertilizer management. In our research, we utilized chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophylls (Chls) and total carotenoids (Cars) as indicators to study the variations in the leaf positions of Lycopersicon esculentum Mill. Under 10 nitrogen concentration applications, a total of 2610 leaves (435 samples) were collected using visible-near infrared hyperspectral imaging (VNIR–HSI). In this study, a “coarse–fine” screening strategy was proposed using competitive adaptive reweighted sampling (CARS) and the iteratively retained informative variable (IRIV) algorithm to extract the characteristic wavelengths. Finally, simultaneous and quantitative models were established using partial least squares regression (PLSR). The CARS–IRIV–PLSR was used to create models to achieve a better prediction effect. The coefficient determination (R²), root mean square error (RMSE) and ratio performance deviation (RPD) were predicted to be 0.8240, 1.43 and 2.38 for Chla; 0.8391, 0.53 and 2.49 for Chlb; 0.7899, 2.24 and 2.18 for Chls; and 0.7577, 0.27 and 2.03 for Cars, respectively. The combination of these models with the pseudo-color image allowed for a visual inversion of the content and distribution of the pigment. These findings have important implications for guiding pigment distribution, nutrient diagnosis and fertilization decisions in plant growth management.

Grain development of foxtail millet (Setaria italica L.) is essential for yield and quality. However, its transcriptional dynamics molecular mechanisms and morphological analyses remain scarcely described. Thus, we conducted detailed daily morphological analyses of foxtail millet grain development throughout the 30 d post-fertilization development period. On the basis of the morphological analyses, we used RNA-sequencing (RNA-seq) to examine the transcript dynamics involved in foxtail millet grain development at four stages. These genes included those associated with transcriptional regulation, hormone signaling, sucrose and starch metabolism, zein family members, amino acid metabolism, carotenoid metabolism, flavonoid biosynthesis, and folate synthesis. We have validated the accuracy of the transcriptome data by means of reverse transcription quantitative polymerase chain reaction (RT-qPCR). This study provides precious genetic resources for understanding grain developmental process in the future. These results expand our understanding of the molecular mechanisms of grain development in foxtail millet and contribute to the functional studies of genes related to grain development in the future.

Conventional fertilizer management can destroy the structure of soil. Replacing chemical fertilizers with organic fertilizers can improve soil quality and nitrogen use efficiency. We aimed to study the effects of organic fertilizer substitutions for chemical nitrogen fertilizer on soil fertility and nitrogen use efficiency in order to clarify the effectiveness of the available nutrient management measures in improving soil quality and increasing foxtail millet yield. A field experiment was carried out over two consecutive years, and a total of six treatments were set up: no fertilizer (CK), chemical nitrogen fertilizer alone (N), the substitution of 25% of chemical nitrogen fertilizer with bio-organic fertilizer (N25A1), the substitution of 25% of chemical nitrogen fertilizer with fermented mealworm manure (N25B1), the substitution of 50% of chemical nitrogen fertilizer with bio-organic fertilizer (N50A2), and the substitution of 50% of chemical nitrogen fertilizer with fermented mealworm manure (N50B2). The results of this study show the following: (1) Compared with chemical nitrogen fertilizer, the substitution of organic fertilizer for nitrogen fertilizer reduced the bulk density and solid phase of the soil, and it increased the total porosity, water content, liquid phase, and gas phase of the soil. (2) Compared with nitrogen fertilizer, the use of an organic fertilizer increased the contents of nitrate nitrogen, ammonium nitrogen, and total nitrogen in the soil by 13.59~52.56%, 4.47~18.27%, and 4.40~12.09%, respectively. The content of alkaline nitrogen increased by 1.70~32.37%, and the contents of soil available potassium, available phosphorus, and organic matter also increased. (3) The activities of sucrase, urease, glutaminase, and asparaginase were improved by replacing chemical nitrogen fertilizer with organic fertilizer. The N25 treatments performed better than the N50 treatments, and fermented mealworm manure performed better than biological organic fertilizer. (4) A moderate application of organic fertilizer (N25) can increase the grain yield, ear weight, grain weight, and 1000-grain weight of foxtail millet, whereas excessive application of organic fertilizer (N50) can reduce foxtail millet yield. (5) Replacing chemical nitrogen fertilizer with organic fertilizer can improve the agronomic use efficiency, physiological efficiency, biased productivity, harvest index, and apparent use efficiency of nitrogen fertilizer. In this study, the substitution of 25% of chemical nitrogen fertilizer with fermented mealworm manure was the best combination for restoring crop productivity and soil quality.

In the process of agricultural production in solar greenhouses, the key to the healthy growth of greenhouse crops lies in accurately predicting environmental conditions. However, there are complex couplings and nonlinear relationships among greenhouse environmental parameters. This study independently developed a greenhouse environmental acquisition system to achieve a comprehensive method for the monitoring of the greenhouse environment. Additionally, it proposed a multi-parameter and multi-node environmental prediction model for solar greenhouses based on the Golden Jackal Optimization-Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Self-Attention Mechanism (GCBS). The GCBS model successfully captures the complex nonlinear relationships in the greenhouse environment and accurately predicts changes in carbon dioxide concentration, air temperature and humidity, and soil temperature at different location nodes. To validate the performance of this model, we employed multiple evaluation metrics and conducted a comparative analysis with four baseline models. The results indicate that, while the GCBS model exhibits slightly higher computational time compared to the traditional Long Short-Term Memory (LSTM) network for time series prediction, it significantly outperforms the LSTM in terms of prediction accuracy for four key parameters, achieving improvements of 76.89%, 69.37%, 59.83%, and 56.72%, respectively, as measured by the Mean Absolute Error (MAE) metric.

The effects of balanced fertilization with nitrogen, phosphorus, and potassium (NPK) on foxtail millet productivity and the soil environment under the same conditions of total nutrients have received limited research attention. Therefore, in this study, three balanced fertilization patterns of 27-14-10 (T1), 27-17-7 (T2), and 30-10-11 (T3), and one no fertilization treatment (CK), a total of four treatments, were set up through a two-year field experiment to study the effects of balanced fertilization patterns on foxtail millet yield and soil environment. Mantel analysis was conducted to reveal the correlation between soil environmental factors and the community and their contribution to productivity. The results showed that: (1) all balanced fertilization treatments significantly increased foxtail millet yield, with the highest yield in the T1 treatment. (2) The contents of EC, available K, available P, and alkaline-hydrolyzable nitrogen in the soil of the two-year TI treatments were higher than those of the other treatments and increased by 7.20–9.36%, 24.87–52.35%, 55.83–56.38%, and 21.05–43.95%, respectively, compared with CK. (3) Soil urease activity in the T1 treatment increased significantly by 26.67% and 9.00% compared with the control over the two years. Sucrase activity increased by 36.27% and 23.88% in the T1 treatment compared to CK, and glutaminase activity increased by 33.33% and 19.23% in the T1 treatment compared to CK. (4) T1 treatment significantly increased the OUT number and diversity index of the soil bacterial community. (5) Mantel analysis and principal component analysis showed that available soil nutrients and soil enzymes were positively correlated, and soil enzymes and soil nutrients contributed more to foxtail millet productivity. In this study, the 27-14-10 balanced fertilization pattern was more effective, providing a theoretical basis for the research and development of special fertilizers for foxtail millet and offering technical guidance for realizing the light simplified cultivation of foxtail millet and sustainable development of cost–saving and increased efficiency.