Key Laboratory for Farmland Quality

Beijing, China

Key Laboratory for Farmland Quality

Beijing, China
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Zhang B.,China Agricultural University | Zhang B.,Key Laboratory for Farmland Quality | Feng G.,U.S. Department of Agriculture | Kong X.,China Agricultural University | And 5 more authors.
Agricultural Water Management | Year: 2016

Soybean is generally grown under rainfed conditions in a humid region, Mississippi, USA. In order to determine how much maximum yield could be increased by irrigation, it is crucial to investigate the yield potential (Yp) without any drought stress and yield gap (Yg, between Yp and rainfed yield (Yw)). Further, it is also important to determine the amount of irrigation water needed to alleviate any drought stress during the entire growing season, and conduct cost-return analysis for irrigated soybean. Therefore, the objectives of this study were to: (1) simulate Yp, analyze Yg and determine the irrigation timing and amount needed to achieve Yp for soybean using the Agricultural Policy/Environmental eXtender (APEX) model; and (2) compute water use efficiency (WUE), irrigation water use efficiency (IWUE) and conduct the cost-return analysis on irrigation events. Simulated Yp of soybean without water stress for nine soil types from 2002 to 2014 ranged from 4.47 to 6.51 Mg ha−1, and was strongly correlated with accumulative solar radiation during the growing season (R2 = 0.71, P ≤ 0.01). The Yg in dry years was much higher than that in normal and wet years, with average Yg of 1.58, 0.60 and 0.71 Mg ha−1 for dry, normal and wet years, respectively. Griffith, Sumter and Demopolis soils had the highest average Yg over 13 years, ranging from 1.37 to 1.60 Mg ha−1. The average irrigation amount was 308, 192 and 157 mm in dry, normal and wet years, respectively. The average irrigation amount was 75 mm from R1 to R8 stages. The WUE of nine soil types from 2002 to 2014, under non-limiting water conditions, ranged from 9.5 to 13.8 kg ha−1 mm−1. The magnitude of Yg was the principle factor affecting IWUE among nine soil types. The average IWUE over 13 years ranged from 1.8 to 7.8 kg ha−1 mm−1 for nine soil types. Compared with a rainfed condition, average net return of irrigated soybean increased by 93 $ ha−1 (dollar per hectare) among nine soil types from 2002 to 2014. The average net return increased by 195, 58 and 70 $ ha−1 for dry, normal and wet years, respectively. © 2016 Elsevier B.V.


Zhang B.,China Agricultural University | Zhang B.,Key Laboratory for Farmland Quality | Feng G.,U.S. Department of Agriculture | Read J.J.,U.S. Department of Agriculture | And 5 more authors.
Agricultural Water Management | Year: 2016

Knowledge of soybean yield constraints under rainfed conditions on major soil types in East Central Mississippi would assist growers in the region to effectively utilize the benefits of water/irrigation management. The objectives of this study were to use the Agricultural Policy/Environmental eXtender (APEX) agro-ecosystem model to simulate rainfed soybean grain yield (GY) for nine major soils during 14 years (2002–2015) and then to evaluate selected model inputs/outputs in relation to irrigation management that may decrease difference in simulated GY among the different soils. Values for GY ranged broadly from 2.24 to 6.14 Mg ha−1 across soils and years, giving a maximum yield difference of 3.90 Mg ha−1. For the average GY of nine soils, the range was from 3.52 to 5.42 Mg ha−1 over 14 years. Averaged across 14 years, GY ranged from 3.66 to 4.90 Mg ha−1 across the nine soils and was affected by difference in soil texture (clay and sand percentages) and soil available water content (AWC). Simulations revealed relatively high water stress during the R4, R5 and R6 stages of plant development (early- to mid-fruit development), suggesting great potential to enhance soybean yield if some irrigation is provided during these critical water stress periods; whereas, the potential was accordingly less in the normal and wet years. Results indicated installing irrigation on Griffith, Sumter or Demopolis soils would have a large impact through increased crop productivity and yield stability. © 2016 Elsevier B.V.


Xiang H.,China Agricultural University | Kong X.,China Agricultural University | Kong X.,Key Laboratory for Farmland Quality | Wu Z.,China Agricultural University | And 2 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2012

Such characteristics of arable land quality as method of calculating crop yield and productivity, yield gaps, distribution of crop productivity, are critical to regulate policymaking for constriction of the high quality farmland and measurement for closing yield gaps of arable land in the main crop production in China. Based on the detail data including field survey at village level, theoretical and realizable yields for different crops by agronomy expert at national and provincial level, statistics yearbook at county level in the main crop production area (Heilongjiang, Jilin, Liaoning, Hebei, Shandong and Jiangsu province) in China were collected, all the data for arable land potential productivity were collated and synthesized. The results indicated as follows:(1) The theoretical productivity potential was 5.12×108t, the realizable productivity potential was 4.03×108t and the actual production was 3.28×108t in the main crop production area of China. (2) The three-level yields including theoretical, realizable and actual level were the highest in Jianghuai Plain in Jiangsu province, however, the theoretical yield was the lowest in Daxing'an Mountain and Xiaoxing'an Mountain. (3) The realizable yield and actual yield in Houshan Bashang Plateau in Hebei province were the lowest among the main crop production zone. (4) The theoretical productivity potential in Hebei plain and Shandong province was higher than the other areas. (5) The large gap between theoretical and realizable yield in the whole area shows that the arable land production can be realized by improving construction of high standard of arable land, however, the small gap between realizable and actual yield shows that there were no room for policymaking. The results provide the basis for policymaking on arable land utilization in the main crop production area in China.


Yu S.,China Agricultural University | Zhang B.,China Agricultural University | Zhang B.,Key Laboratory for Farmland Quality | Xiang H.,State Oceanic Administration | And 2 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2014

With the stability of arable land's quantity, monitoring land quality has become a high priority research for understanding the effects of the dynamic change of arable land on food security in China, as well as the layout method on monitoring arable land quality change. However, there are integrated factors such as climate, terrain, soil, access to irrigation, rural road, trade-off between input and output, which affect arable land quality change over time and space. We propose a new monitoring framework titled factors' combination, which includes such factors affecting arable land quality as natural conditions (e.g., climate, soil, geomorphology), the utilization of level (e.g., farmland infrastructure, land management, land use coefficient), income level (e.g., land use structure and mode, the input and output of arable land, land economic coefficient), and reference cropping system to form a monitoring reference arable land unit. We illustrate this new method using the Dianqian plateau mountain area as a case study. Spatial overlay analysis of main factors and geostatistics method using GIS were employed to test this method. Specific steps of factors' combination method are as follows: 1) we preliminarily determine the number of monitoring reference samples according to the type of factors' combination; 2) on the basis of the proportion of arable land area at each grade accounting for the total area, we then revise the number of monitoring samples and supplement monitoring samples for those gradations which have relatively few monitoring samples; 3) based on GIS analysis results, if the same factors' combination distributes in the different space positions of second zone and meets the requirements of monitoring sample, multiple figure spots of the factors' combination will be kept at the same time, and eventually figure spot of the grading unit will be determined; 4) given overlay the map spot of grading unit and the national standard sample and the provincial standard sample respectively, we take the national standard sample or provincial standard sample as the monitoring sample for those overlaying parts; then convert the remaining figure spots of grading into a point as the monitoring sample, and determine the final number of monitoring samples, spatial location and its source; 5) we build up model on representative index of area of monitoring sample and adopt the geo-statistical method to carry on the representative test for monitoring sample to optimize the monitoring sample. The results show that 144 monitoring reference sample units include 7 from the national standard sample, 44 from provincial standard sample and 93 from arable land grading unit, and they were selected as a whole for monitoring arable land quality in Dianqian plateau mountain area using our new method of factors' combination. The distribution of the selected monitoring reference land units not only provide samples to monitor the arable land quality change in the second zone of national scale, but also meet the requirements of statistical science and representative of area. Layout method for monitoring sample point of arable land quality level using factors' combination, can provide reference for building up the whole country's dynamic monitoring systems, and offer technical support to achieve comprehensive management of quantity and quality of arable land at national level in China. ©, 2014, Chinese Society of Agricultural Engineering. All right reserved.


Zhang B.,China Agricultural University | Zhang B.,Key Laboratory for Farmland Quality | Kong X.,China Agricultural University | Kong X.,Key Laboratory for Farmland Quality | And 2 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2014

To deeply understand the quantity, quality, spatial distribution characteristics and the representative of cultivated land of national standard farmland in western China at macro scale, it is very important to set up and improve the monitoring system of cultivated land quality in the whole country. This paper, based on the database of farmland classification and national standard farmland in western China (12 provinces, municipalities and autonomous regions), gives a analysis of the quantitative distribution characteristic of national standard farmland of the western region in gradation (quality) and on a secondary zone of the standard farming system. The paper then analyzes the spatial distribution features of standard farmland based on GIS and conducts inspection, definition and statistical tests for the representative of national standard farmland. Results show that: (1) In the view of quantitative distribution characteristics, national standard farmlands of the western China were distributed across all the gradations 4-15, but exhibited great differences in each gradation, such as more than half of them concentrated in 8-12 gradation. The distribution of national standard farmland in the 4, 5, 14, and 15 grades was less. Furthermore, national standard farmlands of the western China are unevenly distributed in the secondary zone and have not covered 28 secondary zones of the standard farming system. Therefore, there exists cultivated land but no national standard farmland in five secondary zones such as Daxing'an Mountains region and so on. (2) From the spatial distribution characteristics, national standard farmland is uniformly distributed on the whole, but there is a significant spatial difference and there exist excessive concentration phenomena in six secondary zones. Thus, the data presented suggest that we should adjust and optimize the monitoring sample plot layout of national standard farmland in western China, according to a comprehensive analysis of the testing results and the distribution characteristics.

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