Mulch film mulching cultivation technology not only increases agricultural production and income, but also causes serious pollution problems because of the long-term use of polyolefin mulch film and low recovery rates. In areas with serious mulch film residue, the soil structure is seriously damaged, the quality of cultivated land is reduced, agricultural operations are blocked, and crop emergence, nutrient absorption and root growth and development are restricted. Biodegradable mulch film can be degraded by microorganisms such as bacteria, fungi and actinomycetes in the natural environment, and finally decomposed into CO₂ and H₂O, which not only has no pollution to soil but also promotes the growth and development of crops, and has become one of the effective ways to solve the problem of white pollution. With the deepening of the research on biodegradable mulch film, people found that biodegradable mulch film has different effects on soil environment and crop yield, and these effects are quite different in different regions and crops. It is not possible to directly draw the conclusion that biodegradable mulch film is better than PE mulch film through one or several experiments. In this paper, the effects of biodegradable mulch film on soil environment, crop growth and yield in recent years were summarized, and the experimental effects of biodegradable mulch film (BM) and mulch mulch film (PE) were compared, and their advantages and disadvantages were analyzed, and suggestions were put forward to improve the performance of biodegradable mulch film, so as to continuously improve the performance of biodegradable mulch film and realize the sustainable development of agricultural science and technology. Summary and analysis show that: (1) Biodegradable mulch film can increase soil temperature and humidity, meet the needs of crops in the early stage of growth, accelerate the emergence of seedlings, shorten the growth cycle, and have beneficial effects on soil organic matter, available nitrogen and soil enzyme activity, and improve soil nutrient content. In terms of microorganisms, biodegradable mulch film can promote the growth of soil microbial content and soil respiration rate. At the same time, biodegradable mulch film has better weed control ability than PE mulch film, among which black biodegradable mulch film has the best effect, which can effectively reduce the number of weeds in the field and ensure the supply of nutrients needed by crops. (2) In terms of crops, biodegradable mulch film can promote corn growth, shorten the growth period and increase the yield in the early and middle stages of corn growth. There was no significant difference between the yield of cotton seed cotton covered with biodegradable mulch film and PE mulch film, and the yield of cotton seed cotton covered with mulch film is significantly higher than that of bare land. The potato treated with biodegradable mulch film germinated faster in the early growth stage because of the increase of soil temperature, which significantly shortened the growth cycle and brought it to market earlier, and significantly increased the yield compared with PE mulch film and bare land, among which the black biodegradable mulch film had the most obvious effect. For millet crops, there was no significant difference in yield between the treatment with biodegradable mulch film and the treatment with PE mulch film, and the yield of the treatment with mulch film was significantly improved compared with the treatment with bare land. For vegetable crops such as tomato, eggplant and beet with short growth cycle, biodegradable mulch film can play the role of heat preservation and moisture increase for a long time, and promote the rapid growth of crops. The final yield is not significantly different from that of PE mulch film mulching treatment, even slightly improved, and significantly improved compared with bare land treatment. (3) Put forward the influence of different components of biodegradable mulch film on soil and crops, controllable degradation and cost problems, such as the difficult control of degradation speed, environmental problems caused by incomplete degradation of biodegradable mulch film, low technical maturity and high price, and put forward suggestions for future research and development, so as to modify and innovate biodegradable raw materials, reduce costs and regulate the degradation mechanism of biodegradable mulch film. Strengthen the research on raw materials, formula and production technology of biodegradable mulch film, and develop new biodegradable mulch film with high performance and multifunction, which can meet the regional applicability and crop applicability at the same time, and lay a theoretical foundation for the popularization and application of biodegradable mulch film to more regions and more crop varieties.

In the research, various chemical regulators and appropriate application dates would be tested, based on the physiological responses of winter wheat to dry hot wind stress that contains different efficient components. A field experiment was conducted in Huang-Huai-Hai plain from 2020 to 2021, where dry hot wind disasters were frequently. Six treatments (foliar spraying with tap water (CK) and KH₂PO₄ (CKP) both at jointing and flowing stage as controls; foliar spraying with phosphorus-A preparation at jointing stage (BA) and flowering stage (HA); foliar spraying with phosphorus-E preparation at jointing stage (BZ) and flowering stage (HZ)) were conducted, and leaf area index (LAI), leaf fluorescence parameters, key enzyme activities of starch synthesis, and starch accumulations, dynamics of grain filling in superior and inferior grains, yield and its components of damaged wheat were compared. The winter wheat experienced two mild dry-hot wind stresses on 24 and 26 days after flowering (DAF). Compared with CK treatment, BA (6341.35kg∙ha−1) and HZ (6454.23kg∙ha−1) treatments significantly increased grain yield by 9.82% and 11.78%. Moreover, these two treatments also performed better than CKP treatment, significantly increased by 8.11% and 10.03%, respectively. BA treatment had the highest grain number per panicle, and could significantly increase LAI over CKP by 47.67% on 30 DAF. While HZ treatment performed better on thousand grains weight, and the maximum photochemical efficiency (Fv/Fm), and photochemical quenching coefficiency (qP). Additionally, HA treatment made the non-photochemical quenching (NPQ) at relative low level during the period of grain filling stage. After undergoing two dry hot wind processes, compared with CKP treatment at 26 DAF, the activities of ADP-glc pyrophosphorylase (AGPase) increased by 19.26% under BZ treatment, and the activities of granule-bound starch synthase (GBSS) and soluble starch synthase (SSS) rose 2.11% and 15.92% under HZ treatment. At 30 DAF, HZ treatment elevated amylose and total starch contents by 9.75% and 3.74% than CKP treatment, respectively. The curve fitting with Richards equation showed that foliar-applications of various chemical regulators had a positive impact on wheat resistance and alleviated dry hot wind damage, through delaying the occurrence of the maximum grain-filling rate (T_max∙G) and rising grain-filling rates. Moreover, HA treatment could increase the maximum grain-filling rate (G_max) of inferior and superior grains by 22.71% and 18.30%, and the mean grain-filling rate (G_mean) of the two grain positions performed the increase of 19.27% and 12.72% compared to CKP treatment. Above all, varieties of regulators and application dates ultimately led to varied physiological regulation pathways on leaves and grains of wheat. When separately spraying at the jointing and flowering dates, the optimal regulation benefits of phosphorus-A and phosphorus-E could be stimulated to alleviate the damage of dry hot wind on winter wheat, and HZ treatment was recommended as the most effective method to prevent wheat from the detriment of dry hot wind stress.

Based on statistical data on grain acreage, yields and agricultural disasters from 1961 to 2020, the variability characteristics of grain yields and disasters in China and five northern provinces were compared and analyzed. Disaster yield assessment models for Hebei, Shandong and Henan provinces were used to estimate the loss of grain production due to disasters and grain yields by inputting data on disasters from 2008 to 2020. The sensitivity and stability of the disaster-yield assessment model were examined. Based on the statistical modeling method, the model of grain crop disaster-yield evaluation in Shanxi and Shaanxi was constructed, and the universality of the model construction method was evaluated. The results showed that: (1) the grain planting area and total output of the five northern provinces accounted for 28% and 25% of the national total from 1961 to 2020, respectively. In the five northern provinces, the planting area of summer harvest grain and autumn harvest grain decreased significantly at rates of 3.39ha·a⁻¹ and 106.3ha·y⁻¹(P<0.01) respectively, while the total output increased significantly at rates of 137.3×10⁴t·y⁻¹ and 119.9×10⁴t·y⁻¹(P<0.01), respectively. From 2008 to 2020, the grain planting area and grain yield in the five northern provinces increased significantly at the rates of 209.42ha·y⁻¹ and 258.06×104t·y⁻¹(P<0.01), respectively. (2) From 1961 to 2020, the areas of covered, affected and destroyed disaster in the five northern provinces accounted for 28%, 28% and 23% of the national average, respectively, while the disaster situations in the five northern provinces and the whole country showed a significant trend of first increasing and then decreasing. After reaching historically high values in 2008, 2000 and 2000, the covered disaster, affected disaster and destroyed disaster area had declined year on year. The corresponding disaster situations in the five northern provinces showed a downward turning point in 1990, 1989 and 2004, respectively. Drought and flooding are the main causes of crop disasters in China, with 76 percent of the total area affected by drought and flooding. The disaster in the five northern provinces was mainly caused by drought. The areas affected by drought accounted for 66%, 61% and 58% of the disaster statistics, respectively. From 2008 to 2020, the area affected by drought in Shandong was the largest. The area of drought disaster in Hebei and Shanxi was relatively high. Hebei province has the highest area of flooding and hail. (3) When the data series is extended to 2020, the simulated value of grain yield is significantly correlated with the actual value(R²=0.95, P < 0.01), the simulation accuracy of the model was high. In the past 60 years, the grain loss rates of Hebei, Shandong, Henan, Shanxi and Shaanxi provinces were 8.99%, 18.02%, 9.79%, 12.84% and 20.04%, respectively. In the last 12 years, the grain loss rates of Hebei, Henan, Shanxi and Shaanxi provinces had recorded by 4.4%, 17.4%, 9.65%, 8.14% and 17.9%, respectively, influenced by the reduction of disaster zones and advantage in agricultural science and technology. They all went down. With the verification and construction of the model, the modeling statistical method performs well in evaluating the loss of grain yield due to meteorological disasters, had a promising performance in predicting grain yield, and is feasible for commercial applications. As the five northern provinces account for a high proportion of the country's grain output, it is important to prevent the risk of regional hydrometeorological disasters to ensure the country's food security in the new period.

Spring maize is the primary food crop in Northeast China. Researching and analyzing the spatial difference in yield under diverse climate and soil models holds immense significance in guiding agricultural production and ensuring food security. In this study, a total of 13 key influencing factors were selected from the three aspects of soil, topography and climate, and a multivariate stepwise linear regression model was constructed for spring maize per unit yield and 13 influencing factors by using multivariate stepwise regression analysis. Then the spatial distribution of spring maize per unit area yield in Northeast China was analyzed by using ArcGIS software to rasterize the spring maize yield per unit area. The results showed that: (1) the spatialized data (with a spatial resolution of 1km) calculated by the multiple linear regression model are basically consistent with the statistical data of spring maize yield per unit area. The spring maize yield in Northeast China is between 2482.49-10147.10kg·ha⁻¹. (2) The spatial distribution map of spring maize yield objectively reflects that the spatial distribution trend of spring maize yield, which generally shows a pattern of decreasing from the central to the surrounding areas. This study accurately obtained the grid-scale simulation results of spring maize yield per unit area spatialization in Northeast China (the average relative error is 1.45%), which provides a method reference for the optimization of agricultural production layout and decision-making in Northeast China.

To clarify how different contents of nitrogen effect the fruit performance after the short-term high temperature during the blossom and fruit period, taking tomato ‘Kaisa’ as the experimental material, the temperature-controlled experiment was conducted from March to August, 2022 with the artificial climate chamber(PGC-FLEX, Canada). The fruit setting characteristics, endogenous hormone content of young fruit, fruit appearance quality and the yield of fruit were studied to comprehend the mechanism how different nitrogen levels effect tomato during the blossom and fruit period, and then find out the optimal content of nitrogen which can effectively alleviate the high temperature damage, improve the fruit quality and yield and give guidance for agricultural activities. Five nitrogen levels i.e.N0 (0.00gplant⁻¹), N1 (3.55gplant⁻¹), N2 (5.32gplant⁻¹), N3 (7.09gplant⁻¹) and N4 (8.87gplant⁻¹), and 3 temperature treatments i.e. T1(the max. temperature/ min. temperature is 28℃/18℃), T2(35℃/25℃) and T3(40℃/30℃) were set in this study. Fifteen treatments were performed with the combination of temperature and nitrogen. The relative humidity was set at 50% to 80%, and the light intensity was 1000μmolm⁻²s⁻¹ from 6：00 to 18：00 in the daytime, and 0μmolm⁻²·s⁻¹ during the rest of the day. The results showed that: (1) with no nitrogen applied, the tomato stepped into the rapid fruiting period in advance after the high temperature stress, while the duration of rapid growth period was significantly shortened. With different nitrogen levels applied, the advent of the rapid fruiting period after the high temperature stress was significantly delayed, while the duration of rapid growth period shortened with the increase of temperature. (2) After exerting 5-day-long high temperature, the content of ZT and IAA in tomato young fruit decreased, while the content of GA increased. Appropriate nitrogen level could increase the contents of endogenous hormones (3) With no nitrogen applied, the quality of tomato fruit decreased significantly after a short period of high temperature, as well as the average yield per plant. Appropriate nitrogen levels may promote the growth of young fruit, polish up the fruiting quality and boost yield when the tomato encountered the short-term temperature stress during the blossom and fruit period. However, excess nitrogen would take a toll instead. This study provides the optimal nitrogen level for each temperature: 3.55-5.32gplant⁻¹ for T1 and T2, 3.55-7.09gplant⁻¹ for T3.

Taking the main highland barley growing areas in Tibet as study region, a comprehensive risk assessment model of drought disasters was established based on hazard index of disaster-causing factors, exposure index of disaster-bearing body, vulnerability index of disaster-bearing body and disaster prevention and reduction ability of disaster-bearing body. The pure insurance premium rate of highland barley was determined by non-parametric method, and the pure insurance rate was revised based on the results of risk regionalization, the modified GM (1,1) model and R/S method were combined to predict the future revised pure insurance premium rate. The results show that: (1) based on the risk index of drought hazard factor and vulnerability index of disaster-bearing body, risk grade shows a trend of high on both sides of the middle low, the risk grade based on the exposure index, the ability of disaster prevention and mitigation, and the comprehensive risk index of drought disaster has a tendency to increase gradually from east to west. (2) The pure insurance premium rate of highland barley insurance in each station has little difference (between 1.07%-9.79%), but the modified pure insurance premium rate has a big difference (between 1.86%-17.02%). (3) Based on the risk index, exposure index, and vulnerability index of drought, the spatial distribution of pure insurance premium rate shows the characteristics of high middle, low two sides, however, the pure insurance premium rate based on the drought disaster prevention and mitigation capability correction and the drought disaster comprehensive risk index shows the characteristics of middle high, local high and both sides low. This showed that the scientific and reasonable determination of pure insurance rates should consider the combined effects of multiple drought indices. (4) For the first time, the modified GM (1,1) model and R/S method were used to predict the future revised pure insurance rate of highland barley in Tibet (the rate of increase was 0.21 percent points·10y⁻¹). The comprehensive risk index can objectively reflect the drought risk level of highland barley in Tibet, and the result of regionalization can provide basic support for revising the pure insurance premium rate, and then to improve the precision of highland barley agricultural insurance services to provide a scientific basis.

Machine learning, as a new technique combining statistics and computer science, has been widely used in crop information acquisition tasks in recent years. Traditional methods for obtaining crop information mainly rely on chemical detection methods, which is time-consuming and labor-intensive. Based on machine learning algorithms and hyperspectral remote sensing techniques, crop appearance and internal physical and chemical parameters can be quickly sensed in a non-destructive way, which has obvious application advantages and development prospects. First, the researches related to the hyperspectral remote sensing of crop information were systematically reviewed in this paper. Second, the application, advantages and disadvantages and uncertainties of different machine learning algorithms in hyperspectral sensing crop information were summarized. Finally, it was pointed out that the future development trends of hyperspectral sensing crop information were as follows: (1) complementary crop information acquisition methods could be realized through multi-source remote sensing collaborative observations. (2) The assimilation technologies of hyperspectral remote sensing and crop model as well as the deep integration technologies of hyperspectral remote sensing and artificial intelligence could be developed. (3) The intelligent acquisition of key information oriented to the whole growth period of crops and decision-making could be realized.