This research assessed the quantitative and qualitative reactions of commercially grown sugar beets to four different harvest dates and their yield stability. The study followed a split-plot design within a randomized complete block design over 3 years. The main plot involved 10 sugar beet cultivars, while the subplot involved four harvest dates: August 13 (HD1), September 7 (HD2), October 3 (HD3), and November 12 (HD4). The study found that environmental conditions, genotypes, and harvest dates significantly affected various traits of sugar beet. Yearly environmental variations and their interactions with genotypes and harvest dates had substantial impacts on all measured traits at the 1% probability level. Additive main effect and multiplicative interaction analysis based on white sugar yield indicated that genotype and environment\'s additive effects, as well as the genotype-environment interaction, were significant at 1% probability level. Shokoufa and Arya, which exhibit high white sugar yield (WSY) and low first interaction principal component (IPC1) values, are identified as desirable due to their stability across different environments. Among the harvest dates in different years, the fourth and third dates showed a higher yield than the total average. Perfekta and Ekbatan exhibited high specific adaptability. According to the multi-trait stability index, Arta, Arya and Sina were recognized as stable and superior across all measured traits.

Growth period determination and color coordinates prediction are essential for comparing postharvest fruit quality. This paper proposes a tomato growth period judgment and color coordinates prediction model based on hyperspectral imaging technology. It utilizes the most effective color coordinates prediction model to obtain a color visual image. Firstly, hyperspectral images were taken of tomatoes at different growth periods (green-ripe, color-changing, half-ripe, and full-ripe), and color coordinates (L*, a*, b*, c, h) were obtained using a colorimeter. The sample set was divided by the sample set partitioning based on joint X-Y distances (SPXY). The support vector machine (SVM), K-nearest neighbors (KNN), and linear discriminant analysis (LDA) were used to discriminate growth period. Results show that the LDA model has the best prediction effect with a prediction set accuracy of 93.1%. In addition, effective wavelengths were selected using competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA), and chromaticity prediction models were established using partial least squares regression (PLSR), multiple linear regression (MLR), principal component regression (PCR) and support vector machine regression (SVR) Finally, the color of each pixel of the tomato is calculated using the optimal model, generating a visual distribution image of the color coordinate. The results showed that hyperspectral imaging can non-destructively detect tomatoes\' growth stage and color coordinates, providing great significance for designing a tomato quality grading system.

The significant increase in cadmium (Cd) and lead (Pb) pollution in agricultural soil has greatly heightened environmental contamination issues and the risk of human diseases. However, the mechanisms underlying the transformation of Cd and Pb in soil as well as the influencing factors during their accumulation in crop grains remain unclear. Based on the analysis of the distribution trend of Cd and Pb in soil during the growth and development stages of wheat (tillering, filling, and maturity) in alkaline heavy metal-polluted farmland in northern China, this study investigated the response mechanism of soil heavy metal form transformation to soil physicochemical properties, and elucidated the main determining periods and influencing factors for Cd and Pb enrichment in wheat grains. The results showed that an increase in CEC and SOM levels, along with a decrease in pH level, contributed to enhancing the bioavailability of Cd in the soil. This effect was particularly evident during the tillering stage and grain filling stage of wheat. Nevertheless, the effects of soil physicochemical properties on bioavailable Pb was opposite to that on bioavailable Cd. The enrichment of Cd and Pb in grain was significantly influenced by soil pH (r = -0.786, p < 0.01), SOM (r = 0.807, p < 0.01), K (r = -0.730, p < 0.01), AK (r = 0.474, p = 0.019), and AP (r = -0.487, p = 0.016). The reducible form of Cd in soil during the wheat tillering stage was identified as the primary factor contributing to the accumulation of Cd and Pb in wheat grains, with a significant contribution rate of 84.5%. This study provides a greater scientific evidence for the management and risk control of heavy metal pollution in alkaline farmland.

Biogas slurry, a by-product of the anaerobic digestion of biomass waste, predominantly consisting of livestock and poultry manure, is widely acclaimed as a sustainable organic fertilizer owing to its abundant reserves of essential nutrients. Its distinctive liquid composition, when tactfully integrated with a drip irrigation system, unveils immense potential, offering unparalleled convenience in application. In this study, we investigated the impact of biogas slurry topdressing as a replacement for chemical fertilizer (BSTR) on soil total organic carbon (TOC) fractions and carbon (C)-degrading enzyme activities across different soil depths (surface, sub-surface, and deep) during the tasseling (VT) and full maturity stage (R6) of maize. BSTR increased the TOC content within each soil layer during both VT and R6 periods, inducing alterations in the content and proportion of individual C component, particularly in the topsoil. Notably, the pure biogas slurry topdressing treatment (100%BS) compared with the pure chemical fertilizer topdressing treatment (CF), exhibited a 38.9% increase in the labile organic carbon of the topsoil during VT, and a 30.3% increase in the recalcitrant organic carbon during R6, facilitating microbial nutrient utilization and post-harvest C storage during the vigorous growth period of maize. Furthermore, BSTR treatment stimulated the activity of oxidative and hydrolytic C-degrading enzymes, with the 100%BS treatment showcasing the most significant enhancements, with its average geometric enzyme activity surpassing that of CF treatment by 27.9% and 27.4%, respectively. This enhancement facilitated ongoing and efficient degradation and transformation of C. Additionally, we screened for C components and C-degrading enzymes that are relatively sensitive to BSTR. The study highlight the advantages of employing pure biogas slurry topdressing, which enhances C component and C-degrading enzyme activity, thereby reducing the risk of soil degradation. This research lays a solid theoretical foundation for the rational recycling of biogas slurry.

The evolution of the starch fine structure during growth and its impact on the gelatinization behavior of cassava starch (CS) was investigated by isolating starch from South China 6068 (SC6068) cassava harvested from the 4th to 9th growth period. During growth, the short-range ordered structure, crystallinity as well as particle size distribution of starch were increased. Meanwhile, the starch molecular size and amylopectin (AP) proportion increased, while the proportion of amylose (AM) exhibited a decreasing tendency. The chains of short-AM (X ~ 100-1000) were mainly significantly reduced, whereas the short and medium-AP chains (X ~ 6-24) had the most increment in AP. The solubility, thermal stability, shear resistance, and retrogradation resistance of starch were enhanced after gelatinized under the influence of the results mentioned above. This study presented a deeper insight into the variation of starch fine structure during growth and its influence on gelatinization behavior, which would provide a theoretical basis for starch industrial applications.

Crop water stress index (CWSI) has been widely used in soil moisture monitoring. However, the influence of the time lag effect between canopy temperature and air temperature on the accuracy of soil moisture monitoring with different CWSI models has not been further investigated. Therefore, based on the continuous record of canopy temperature and air temperature, this study explored the influence of canopy-air temperature hysteresis on the diagnosis of soil moisture with three CWSI models (CWSIT-theoretical, CWSIE-empirical, CWSIH-hybrid). The results show (1) the peak time of canopy temperature was ahead of that of air temperature, and the lag time varied under different soil moisture conditions. When the soil moisture was seriously deficient, the lag time decreased. However, from jointing-heading period to filling-ripening period, the lag time became longer. (2) The values of CWSIT, CWSIE, and CWSIH decreased when the time lag effect was considered. In jointing-heading period, heading-filling period, and filling-ripening period, CWSIT had the highest accuracy in soil moisture monitoring without the consideration of the time lag effect. When the time lag effect was considered, the monitoring accuracy of CWSIE and CWSIH was greatly improved and higher than that of CWSIT, while that of CWSIT was reduced. The findings provided a basis for further improving the accuracy of soil moisture monitoring with CWSI models.

The J-protein family comprises molecular chaperones involved in plant growth, development, and stress responses. Little is known about this gene family in soybean. Hence, we characterized J-protein genes in soybean, with the most highly expressed and responsive during flower and seed development. We also revealed their phylogeny, structure, motif analysis, chromosome location, and expression. Based on their evolutionary links, we divided the 111 potential soybean J-proteins into 12 main clades (I-XII). Gene-structure estimation revealed that each clade had an exon-intron structure resembling or comparable to others. Most soybean J-protein genes lacked introns in Clades I, III, and XII. Moreover, transcriptome data obtained from a publicly accessible soybean database and RT-qPCR were used to examine the differential expression of DnaJ genes in various soybean tissues and organs. The expression level of DnaJ genes indicated that, among 14 tissues, at least one tissue expressed the 91 soybean genes. The findings suggest that J-protein genes could be involved in the soybean growth period and offer a baseline for further functional research into J-proteins\' role in soybean. One important application is the identification of J-proteins that are highly expressed and responsive during flower and seed development in soybean. These genes likely play crucial roles in these processes, and their identification can contribute to breeding programs to improve soybean yield and quality.

Selections on emergence time might be conflicting, suggesting the existence of the optimal emergence time for plants. However, we know little about this and how morphological plasticity contributes to the strategies of plants in response to emergence timing. To better understand this issue from a dynamic perspective, we conducted a field experiment by subjecting plants of Abutilon theophrasti to four emergence treatments (ET1 ~ ET4) and measuring a number of mass and morphological traits on them at different growth stages (I ~ IV). On day 50, 70, and/or final harvest, among all ET treatments, plants germinated in late spring (ET2) performed the best in total mass, spring germinants (ET1) and ET2 performed better in stem allocation, stem, and root diameters than later germinants (ET3 and ET4); summer germinants (ET3) had the highest reproductive mass and allocation, while late-summer germinants (ET4) had the greatest leaf mass allocation, with greater or canalized leaf number, and root length traits than others. Plants that emerged in late spring can maximize their growth potential, while those with either advanced or delayed emergence are still capable of adaptation via allocation and morphological plasticity. Early germinants (ET1 and ET2) preferred stem growth to leaf and reproductive growth, due to sufficient time for reproduction in the growth season. With limited time for growth, plants that emerged late may prefer to quicken leaf growth (indicated by increased leaf mass allocation and leaf number) at the cost of stem or root growth for the complete life cycle, reflecting both positive and negative effects of delayed emergence.

In this study, the triterpenoids in the leaves of Lactuca indica L.cv. Mengzao (LIM) were extracted via microwave-assisted ethanol extraction, and the optimum extraction conditions for triterpenoids were determined through single-factor experiments and the Box-Behnken method. The effects of three factors (solid-liquid ratio, microwave power and extraction time) on the total triterpenoids content (TTC) were evaluated. The TTC of different parts (roots, stems, leaves and flowers) of LIM in different growth stages was studied, and the scavenging effects of the highest TTC parts on DPPH, ABTS and hydroxyl free radicals were investigated. The results showed that the optimum extraction conditions for microwave-assisted extraction of total triterpenoids from LIM leaves were as follows: solid-liquid ratio of 1:20 g/mL; microwave power of 400 W; and extraction time of 60 min. Under these conditions, the TTC was 29.17 mg/g. Compared with the fresh raw materials, the TTC of the materials increased after freeze drying. The leaves of LIM had the highest TTC, and the flowering stage was the best time. The triterpenoids from the leaves had a strong ability to eliminate DPPH and ABTS free radicals, and the elimination effect of dried leaves was better than that of fresh leaves, while the elimination effect of hydroxyl free radicals was not obvious. The tested method was used to extract total triterpenoids from LIM using a simple process at low cost, which provides a reference for developing intensive processing methods for L. indica.

The yield of winter wheat in Shandong Province is of great significance for ensuring regional and national food security. To reduce the risk of production loss, the WOFOST model was used to simulate the winter wheat growth to obtain the quantitative and dynamic information. Based on the observational data, a moisture control experiment and the trial and error method, the applicability and drought simulation of the WOFOST model were evaluated for winter wheat growth. For the simulation of the seedling period, flowering period, and maturity period of winter wheat in Shandong Province, the R2 were 0.95, 0.69, and 0.68 respectively. The D-index were 0.99, 0.89, and 0.86 respectively. The mean absolute error (mAE) were 1.3, 4.3, and 4.1 respectively. And the nRMSE were 0.65%, 4.3%, and 3.2%, respectively. For the yield simulation, the R2, D-index, mean relative error (mRE), and nRMSE were 0.48, 0.82, 10.5% and 12.8%, respectively. For the yield simulation under drought stress, the R2, D-index, mRE, and nRMSE were 0.77, 0.93, 7.1%, and 7.4%, respectively. An evaluation index system was built through four different degrees of drought treatment between the jointing period and the flowering period. With the aggravation of drought, the growth indicators about the total above ground production (TAGP), maximum leaf area index (MAXLAI), total dry weight of leaves (TWLV), and total dry weight of stems (TWST) decreasing by 13.6-41.0%, 37.8-56.5%, 19.4-42.1%, and 20.3-51.2%, respectively. The results showed that this model could adequately simulate the formation process of yield under both normal and drought conditions.