Search

Situated at middle-to-high latitudes with limited thermal resources, Northeast China is the primary maize-producing region in China. It is also one of the regions most significantly impacted by climate change. Given the persistent impact of climate change, it is crucial to elucidate the effects of the varying thermal conditions and low temperatures for different sowing dates on the growth, development, and grain maturity of spring maize. To ensure secure maize production and disaster prevention, choosing the optimal sowing time for spring maize holds significant implications for the judicious utilization of climatic resources, risk mitigation, and the provision of meteorological guidance. Moreover, it can serve as a technical reference for relevant departments to conduct climate evaluation, disaster monitoring, prediction, and assessment, as well as impact analysis of corn production safety. Additionally, it can provide meteorological evidence to ensure food security and promote the sustainable development of modern agriculture. An interval sowing experiment of spring maize was conducted in Harbin in the north of Northeast China. Two varieties were used in the experiment. Four sowing dates were set, and the interval between adjacent sowing dates was 10 days. The local perennial sowing time, 5 May, was set as the second sowing date, with one date set later and two dates set earlier. During the experiment, the growth process, grain dry matter, seed moisture content, yield components, and temperature of spring maize were observed. The impact of temperature conditions on maize growth and yield formation was analyzed in this paper through mathematical statistics, which further led to the establishment of a monitoring and evaluation model for assessing the effect of thermal conditions and temperature on maize. The results showed that the growth rate of spring maize was closely related to temperature. When the average temperature, minimum temperature, and maximum temperature increased by 1 °C, the average emergence rate increased by 1.05%, 0.99%, and 1.07%, respectively, and the average vegetative growth rate increased by 0.16%, 0.16%, and 0.09%, respectively. The change rate of ≥10 °C active accumulated temperature was significantly correlated with the change rate of the dry weight of the grain kernel, which conformed to the quadratic equation of one variable. The temperature influence coefficients of different sowing dates varied from 1.0% to 1.7%. The relationship between the accumulated values of 10 ℃ active accumulated temperature and the grain moisture content of spring maize was a logarithmic function. From 10 to 50 days after anthesis, the effect of temperature can explain about 95% of the change in grain moisture content. After physiological maturity, the effect of thermal conditions can only explain 56–83%. The temperature influence coefficient ranges from 1.3% to 13.8%. Comparatively speaking, the second sowing date is the most suitable sowing date. Early sowing is prone to encounter low temperatures, resulting in underutilization of the early heat, while late sowing is prone to less heat. Both conditions are not conducive to better improve the yield of spring maize. [ABSTRACT FROM AUTHOR]

Northeast China plays a pivotal role in producing commodity grains. The precipitation and temperature distribution during the growth season is impacted by geographical and climate factors, rendering the region vulnerable to drought. However, relying on a single index does not reflect the severity and extent of drought in different regions. This research utilised the random forest (RF) model for screening remote sensing indices. Relative soil moisture (RSM) was employed to compare seven commonly used indices: the temperature vegetation dryness index (TVDI), vegetation supply water index (VSWI), vegetation condition index (VCI), temperature condition index (TCI), vegetation health index (VHI), multi-band drought index (MBDI), and normalised difference drought index (NDDI). The effectiveness of these indices for monitoring drought during different developmental stages of spring maize was evaluated. Trend rates were employed to investigate the temporal changes in drought patterns of spring maize from 2003 to 2020, and the Sen + Mann–Kendall test was used to analyse spatial variations. The results showed the following: (1) The seven remote sensing indices could accurately track drought during critical growth stages with the TVDI demonstrating higher applicability than the other six indices. (2) The application periods of two TVDIs with different parameters differed for the drought monitoring of spring maize in different developmental periods. The consistency and accuracy of the normalised difference vegetation index (NDVI)-based TVDI (TVDIN) were 5.77% and 34.62% higher than those of the enhanced vegetation index (EVI)-based TVDI (TVDIE), respectively, in the early stage. In contrast, the TVDIE exhibited 13.46% higher consistency than the TVDIN in the middle stage, and the accuracy was the same. During the later stage, the TVDIE showed significantly higher consistency and accuracy than the TVDIN with consistency increases of 9.61% and 38.64%, respectively. (3) The drought trend in northeast China increased from 2003 to 2020, exhibiting severe spring drought and a weakening of the drought in summer. The southern, southwestern, and northwestern parts of northeast China showed an upward drought trend; the drought-affected areas accounted for 37.91% of the study area. This paper identified the most suitable remote sensing indices for monitoring drought in different developmental stages of spring maize. The results provide a comprehensive understanding of the spatial–temporal patterns of drought during the past 18 years. These findings can be used to develop a dynamic agricultural drought monitoring model to ensure food security. [ABSTRACT FROM AUTHOR]

Water and fertilizer play an important role in crop growth in dryland areas. It is a necessity to improve the water use efficiency (WUE) of the crop once the water resource is limited. In northern China, where there is a wide shortage of water resources, it is therefore necessary to investigate how fertilization affects the WUE of spring maize and to quantify the effects. A total of 33 published peer-reviewed papers were collected, and a meta-analysis and random forest model analysis were performed with 364 WUE comparisons, aiming to explore the effects of fertilization on the WUE of spring maize and to clarify the optimal conditions for WUE under fertilizer management. The results showed that fertilization significantly increased the WUE of spring maize by 56.72% (P < 0.01) when compared with non-fertilization. The WUE effect under the organic–inorganic fertilizer combination (MNPK) was approximately twice as high as that under inorganic fertilizer (NPK) or organic fertilizer (M). The greatest increase in WUE occurred at 0–100 kg ha−1 of nitrogen application (NA). Under environmental conditions including 7 ≤ mean annual temperature in the test year (T) ≤ 10 °C, 400 ≤ mean annual precipitation in the test year (P) ≤ 600 mm, and mean altitude (A) > 1500 m, and soil conditions including 10 ≤ soil organic matter content (SOM) ≤ 14 g kg−1 and available phosphorus (AP) < 5 mg kg−1, the fertilization optimally enhanced the WUE of spring maize when the agronomic measures of ridge–furrow planting (RFP) and mulching film (MF) were used. The random forest model analysis indicated that the influence factors (i.e., fertilizer regimes, environmental factors, soil factors, and agronomic measures) caused 65.62% of the variation in spring maize WUE effects, while in all influence factors, fertilizer types related to fertilizer regimes caused the most variation. The initial available potassium (AK) and available nitrogen (AN) of the soil were negatively correlated to the WUE effect, indicating that fertilization imposed a better effect on the WUE of spring maize when the soil was infertile. Fertilization significantly increased the WUE of spring maize, and organic and inorganic fertilizer application provided an effective measure for the sustainable development of spring maize in northern China. After clarifying the required conditions for fertilization increasing WUE, high-efficiency water use may be achieved. [ABSTRACT FROM AUTHOR]

Global climate change is a serious threat to food and energy security. Crop growth modelling is an important tool for simulating crop food production and assisting in decision making. Planting date is one of the important model parameters. Larger-scale spatial distribution with high accuracy for planting dates is essential for the widespread application of crop growth models. In this study, a planting date prediction method based on environmental similarity was developed in accordance with the third law of geography. Spring maize planting date observations from 124 agricultural meteorological experiment stations in China over the years 1992–2010 were used as the data source. Samples spanning from 1992 to 2009 were allocated as training data, while samples from 2010 constituted the independent validation set. The results indicated that the root mean square error (RMSE) for spring maize planting date based on environmental similarity was 10 days, which is better than that of multiple regression analysis (RMSE = 13 days) in 2010. Additionally, when applied at varying scales, the accuracy of national-scale prediction was better than that of regional-scale prediction in areas with large differences in planting dates. Consequently, the method based on environmental similarity can effectively and accurately estimate planting date parameters at multiple scales and provide reasonable parameter support for large-scale crop growth modelling. [ABSTRACT FROM AUTHOR]

Simple Summary: The Asian corn borer (ACB), Ostrinia furnacalis, is a devastating corn pest widely distributed in China. Depending on the climate, ACB may have one or up to seven generations each year, from north to south, respectively. Previous investigations suggested co-existence of the uni- and multivoltine patterns in northeast regions (45°38′ N). Efforts have been conducted to isolate uni-voltinism (with obligate diapause), multi-voltinism (with facultative diapause), and a non-diapausing strain using recurrent selections under various simulated temperature and photoperiod environments. The univoltine (Lu) strain has evolved a stable univoltinism under a diapause suppressing condition (16 h daylength at 28 °C). The multivoltine strain (Lm) was shown to have a typical facultative diapause induced by a range of short-day lengths (11–13.5 h). The majority (94.4%) of the developed Ln strain still maintained the non-diapausing nature under a diapause enhancing condition, i.e., a short (13 h) daylength at a low temperature (22 °C). The study suggests that ACB has evolutionary intra-population variation in voltinism. Under the climate change scenario warmer spring and summer will affect the proportion of sympatric voltine biotype populations that evolve toward being multivoltine. The Asian corn borer (ACB) Ostrinia furnacalis (Guenée) can occur in one to seven generations annually from cool (48°00′ N) to warm (18°10′ N) region of corn cultivation in China. Although ACB is commonly known as a facultative larval diapause insect, the co-existence of various voltinism suggests that intra-population variation may have evolved for the nature of diapause, i.e., voltinism plasticity. Here, we conducted recurrent selection efforts to establish three strains of, respectively, univoltine (with obligate diapause), multivoltine (with facultative diapause), and non-diapausing ACB under various temperature and photoperiod environments. The univoltine (Lu) strain has evolved a stable univoltinism under a diapause suppressing condition (16 h daylength at 28 °C), with the diapause incidence constantly over 80% after three generations of selection. The multivoltine strain (Lm) under the high temperature (28 °C) was shown to have a typical facultative diapause induced by a range of short-day lengths (11–13.5 h). Diapause incidence was constantly <2.6% under the long day length (16 h) when the temperature was from 18 to 28 °C, i.e., low temperature could not enhance the diapause response in the Lm strain. However, the development was prolonged from 14.2 ± 0.3 d to 46.0 ± 0.8 d when the temperature was reduced from 28 °C to 18 °C. The majority (94.4%) of the developed Ln strain still maintained the non-diapausing nature under a diapause enhancing condition, i.e., a short (13 h) daylength at a low temperature (22 °C). Lm and Ln were able to complete their second generation in Heihe (50°14′ N) if the first-generation moth oviposits before 18 June. The study suggests that ACB has evolutionary intra-population variation in voltinism. Under the climate change scenario warmer spring and summer might affect the proportion of sympatric voltine biotype populations that evolve toward being multivoltine. [ABSTRACT FROM AUTHOR]

Spring wheat–summer maize (SWSM) annual crop systems were formed to satisfy the maize grain mechanized harvest thermal requirement in the thermal–resource–limited region of the North China Plain. However, the nitrogen (N) application rate effect on SWSM annual yield formation, N accumulation and utilization were barely evaluated. Two–year field experiments were conducted to evaluate the effects of the N application rate on the annual yield of SWSM, observe N accumulation and utilization, and identify the optimized N application. The experiments were conducted under 5 N levels of 0 (N0), 180 (N180), 240 (N240), 300 (N300), and 360 (N360) kg ha−1. The results showed that spring wheat, summer maize and annual cereal yield under the N240 and N480 treatments obtained the highest grain yield (GY) of 5038, 1282 and 16,320 kg ha−1, respectively, and the optimal N application rate was estimated using a linear–plateau model to be 231–307, 222–337 and 463–571 kg ha−1 with maximum GY of 4654–5317, 11,727–12,003 and 16,349–16,658 kg ha−1, respectively. With the increase in the N application rate, the dry matter accumulation (DM) were significantly increased by 16.9–173.5% for spring wheat and 11.1≈–76.8% for summer maize, respectively; and the annual cereal DM was 15.1–179.7% greater than that with N0 treatment, respectively. Spring wheat, summer maize and the annual cereal total N accumulation (TN) under N360 and N720 treatments were significantly increased by 5.4–19.1%, 16.6–32.3% and 11.5–26.2%, respectively, compared to the other treatments; however, N use efficiency for biomass and grain production (NUEbms and NUEg) were decreased significantly by 10.9–13.6% and 8.9–20.7%, 6.8–13.8% and 12.2–15.6%, and 5.5–11.7% and 10.0–16.0%, respectively. Meanwhile, the N partial factor productivity (PFPN), N agronomy use efficiency (ANUE), N recovery efficiency (NRE) and N uptake efficiency (NEupk) under the N240 treatment for spring wheat and summer maize obtained high levels of 20.99 and 47.01 kg−1, 9.27 and 16.35 kg−1, 32.53% and 32.44%, and 0.85 and 0.72 kg−1, respectively. Correlation analysis showed that the N application rate, TN and NEupk played significantly positive roles on GY, spring wheat spilke grain number, summer maize ear grain number and 1000–grain weight, DM LAImax and SPADmax, while NUEbms, NUEg, PFPN and ANUE always played negative effects. These results demonstrate that spring wheat, summer maize and annual cereal obtained the highest GY being 4654–5317, 11,727–12,003 and 16,349–16,658 kg ha−1 with the optimal N application rate 231–307, 222–337 and 463–571 kg ha−1, respectively, which provide N application guidance to farmer for spring wheat–summer maize crop systems to achieve annual mechanical harvesting in the thermal–resource–limited region of the North China Plain. [ABSTRACT FROM AUTHOR]