In order to screen the suitable mowing period with high forage yield, good quality and good silage fermentation quality of triticale in Northern Henan. Triticale varieties ʻYounengʼ and ʻLeishenʼ were used as experimental materials, and four mowing periods were set up to determine the dry matter yield, nutritional quality and silage fermentation quality. The results showed that from the heading stage to the milk stage, the dry matter yield of triticale gradually increased, with Youneng and Leishen reaching the highest of 15.64 and 16.67 t/ha, respectively. The whole plant moisture content, crude protein and crude ash contents all decreased with the delay of mowing period, the neutral detergent fiber and acid detergent fiber contents increased first and then decreased, and the principal component analysis of nutritional indicators indicated that the nutritional quality score peaked at the heading stage. The pH of silage was 4.05-4.50, the lactic acid content was 2.11%-4.00%, with no detection of butyric acid. Youneng and Leishen had better fermentation quality when mowed from flowering to filling stage, from heading to filling stage, respectively. In summary, Youneng and Leishen are suitable for mowing at the flowering and heading stages, respectively. At these stages, both varieties achieve high dry matter yields along with excellent nutritional and silage fermentation quality.

In order to accurately simulate the initiation process of tobacco leaves and provided reference for precise management and control of tobacco production, field comparison experiments of different transplanting date treatments were carried out for two consecutive years from 2022 to 2023 to establish dynamic models of tobacco leaf changes based on different scales, and the simulation accuracy of different models was analyzed. The results showed that the rate of leaf initiation accelerated with the delay of the transplanting date, and the time to reach the maximum number of leaves was shortened. The final number of leaves (A value) in different transplanting dates was basically the same. The leaf initiation models of tobacco was an atypical “S” type growth curve with no stable growth period. The accuracy of the growing degree days model was higher than that of the growing day model, which had better practicality when the temperature changed in the appropriate range. The accuracy of the thermal-photo effectiveness model was higher than the growing degree days model, however, the prediction accuracy fluctuated across different years. The accuracy of the physiological development time model was higher than other models. The time for the tobacco leaves number to reach the maximum value was 37.63- 46.62, the growing degree days was 440.06-483.04, the thermal-photo effectiveness value was 30.17-34.36, and the physiological development time was 29.13-31.80, in the transplanting date from late April to late May in Shandong tobacco area. The simulation model of tobacco leaf initiation based on physiological development time had higher reliability and universality, which could accurately characterize the process of plant development and provide support for the precise management of tobacco production.

To explore the optimal nitrogen application rate for different wheat varieties in various environments and provide a scientific basis for enhancing the mineral element content in wheat grains, this study used 15CA73, Jimai 22, Zhongmai 255, and Zhongmai 578 as experimental materials. Five nitrogen application treatments were established across four environments: Anyang (Henan), Hefei (Anhui), Weifang (Shandong), and Liaocheng (Shandong). These treatments included no nitrogen application (N₀), basal application of 45 kg/ha pure nitrogen + topdressing of 45 kg/ha pure nitrogen at the jointing stage (N₄₅₊₄₅), basal application of 90 kg/ha pure nitrogen + topdressing of 90 kg/ha pure nitrogen at the jointing stage (N₉₀₊₉₀), basal application of 135 kg/ha pure nitrogen + topdressing of 135 kg/ha pure nitrogen at the jointing stage (N_135+135), and basal application of 180 kg/ha pure nitrogen + topdressing of 180 kg/ha pure nitrogen at the jointing stage (N_180+180). The results showed highly and extremely significant correlation coefficients (P < 0.01) between the contents of elements such as K and P (r = 0.72), and Zn and Cu (r = 0.69) in grains. Compared with the N₀ treatment, the N_180+180 treatment resulted in the highest contents of Ca, Cu, Mg, and S in wheat grains at the Weifang site across all environments, with increases of 11.06%, 10.78%, 0.15%, and 7.83%, respectively. The Zn content at the Weifang experimental site was highest under the N_135+135 treatment, showing a 46.01% increase compared to the N₀ treatment. Furthermore, compared with the N₀ treatment, the N_180+180 treatment led to the highest contents of Cu, Fe, Mg, Mn, and S in Zhongmai 255 grains among all tested varieties, with increases of 2.42%, 3.50%, 1.65%, 4.23%, and 16.10%, respectively. The Zn content in Zhongmai 255 grains was the highest under the N_135+135 treatment, increasing by 13.26% compared to N₀ treatment. In summary, increased nitrogen application enhanced the contents of Ca, Cu, Fe, Mn, S, Mg, and Zn in wheat grains. K content was less affected by nitrogen application, while P content showed a declining trend. Concurrently, the P/Mg, P/Fe, and P/Zn ratios decreased, further improving the bioavailability of Mg, Fe, and Zn in the grains. Therefore, the recommended optimal nitrogen fertilizer treatments for wheat cultivation at the experimental sites are N_135+135 for Anyang, N₀ for Hefei, N_180+180 for Liaocheng, and N_180+180 for Weifang. Moreover, N₀ is determined to be the optimal nitrogen fertilizer treatment for 15CA73 and Jimai 22, whereas N_180+180 is optimal for Zhongmai 255 and Zhongmai 578.

A field experiment was conducted to investigate the effects of planting densities and nitrogen application levels on the growth, biomass allocation and yields of Salvia prionitis Hance. Three planting density levels, high density (666 666 plant/ha), medium density (200 000 plant/ha), and low density (95 238 plant/ha); and three fertilization levels [no nitrogen application, low nitrogen (22.5 g/m²) and high nitrogen (45 g/m²)] were set. The results showed that both the density and nitrogen level significantly affected plant size, biomass allocation and yield of S.prionitis. However, the interaction effect only extremely significantly affected the parameters related to biomass allocation. In general, nitrogen application increased the plant height, number of flower stalks, and number of primary branches flower stalks of S.prionitis under all planting densities, and leaf length, leaf width, and plant height of the two low density treatment were greater than those of the high density treatment under all nitrogen levels. Nitrogen level did not significantly affect the root biomass ratio and root- shoot ratio of S.prionitis at medium density treatment, while the root biomass ratio and root-shoot ratio at low and high densities were significantly reduced with the increasing of nitrogen application. Under each densities, the root biomass, supporting structure biomass, total biomass, whole plant yield and root yield of S.prionitis were the greatest in the low nitrogen treatment, then followed by the high nitrogen treatment. under every nitrogen application levels, the root biomass, supporting structure biomass and total biomass of S.prionitis increased significantly with the decreasing of density, However, the whole plant yield and root yield increased significantly with the decreasing of density. In all treatments, whole plant yield and root yield of S.prionitis were the greatest at high density (666 666 plant/ha) with low nitrogen level (22.5 g/m² pure nitrogen, urea).

This study used 17 selected quinoa lines as experimental materials and established three sowing dates: November 10, 2022 (T1), December 15, 2022 (T2), and January 5, 2023 (T3), to analyze the effects of sowing date on quinoa agronomic traits and yield. The results showed that delaying the sowing date shortened the average growth period from 191.7 d (T1) to 148.1 d (T3), a reduction of 44.0 d for late sowing compared to early sowing. Under T3 treatment, quinoa exhibited the highest average plant height but the lowest 1000-grain weight. Under T2 treatment, the average stem diameter, number of effective branches, and yield per plant were all the highest. Under T1 treatment, the average main panicle length was the shortest. Correlation analysis showed that the yield per plant had a highly significantly positive correlation with stem diameter, number of effective branches, and 1000-grain weight. Two-way ANOVA showed that plant height, main panicle length, 1000-grain weight, and growth period were most strongly affected by sowing date. In contrast, number of effective branches and yield per plant were only significantly affected by the line and the interaction between line and sowing date. In conclusion, the most suitable winter sowing date for quinoa in the low-heat valley area of the Jinsha River in northwest Yunnan is mid-December (T2). Under this sowing date, lines Q201909, Q201807, and Q201913 exhibited the best comprehensive performance in agronomic traits and yield, making them suitable for winter cultivation in the low-heat valley areas of Yunnan and similar climatic regions.

In order to clarify the pathogenicity and the potential risk of major corn pathogens to soybean root rot in corn-soybean inter planting, this study artificially inoculated non-co-occurring pathogens onto soybean roots and observed the symptoms in pots, and identified the infection grades of pathogens on soybean root rot. The results showed that Curvularia lunata causing corn curvularia leaf spot, Bipolaris maydis causing southern corn leaf blight, and Exserohilum turcicum causing northern corn leaf blight were non-co-occurring pathogens and could cause soybean root rot. Isolation and identification confirmed that the isolated strains were identical to the inoculated pathogens; C.lunata could cause soybean root rot up to Grade 5, B.maydis and E.turcicum could lead to soybean root rot up to Grade 3. The above results indicated that all three pathogens were causal agents of soybean root rot, and there was a potential risk of causing soybean root rot.