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Root system architecture in a barley RIL population: Agronomic effects of seedling and adult root traits
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-18 DOI: 10.1016/j.fcr.2025.109806
Alejandra Cabeza , Ana M. Casas , Antonio Pérez-Torres , Francisco J. Ciudad , Ernesto Igartua
Drought tolerance has always been one of the main breeding targets of breeding programs for dryland agriculture in the Mediterranean region. This target has become even more urgent, given the current trends of decline and unpredictability of rainfall in the region. Historically overlooked, focus on roots has recently become a critical component in plant research aimed at improving drought tolerance. Recent advancements in root phenotyping methods have enabled more comprehensive investigations. The objective of this study was to assess the genetic control of root system architecture (RSA) of barley evaluated at an early stage, and its potential as a predictor of adult RSA and agronomic performance. We evaluated the RSA in seedlings of an elite recombinant inbred line population, Orria x Plaisant, using rhizoslides, and found genetic diversity and QTL for most traits. The extreme lines for root opening angle (RoA) were further tested for adult root structure under field conditions, through a shovelomics approach. A multifactorial analysis combining previously available agronomic traits with the two root analyses found a negative correlation between RoA at seedling stage and thousand kernel weight (TKW) in all years and locations tested. Some QTL were detected for root traits at seedling stage and some of them co-located with yield or related harvest traits. For adult plants, we found that a narrow RSA, compact, with profuse root growth was advantageous for yield in the field trials that suffered more drought. Overall, we found weak relationships of seedling RSA traits with agronomic performance and adult RSA traits. However, these relationships can still be useful to help selecting plants for good performance under drought in plant breeding programs.
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引用次数: 0
Minimum tillage reduces variability and economic risks in cotton-maize rotations in Northern Benin
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-17 DOI: 10.1016/j.fcr.2025.109795
Tobi Moriaque Akplo , Pierrot Lionel Yemadje , Lucien Imorou , Bettina Sanni , Stéphane Boulakia , Emmanuel Sekloka , Pablo Tittonell

Context

In sub-Saharan Africa, farmers are still perceiving minimum or no tillage to come at the expense of short-term economic profits.

Objective

The study aimed to evaluate the effect of strip-till one-pass (ST) and direct seeding (DS) on crop yield and profitability within a cotton-maize rotation system, in comparison with conventional tillage (CT) and strip till plus hoeing and ridging (STHR), as a farmer adaptation of minimum tillage.

Methods

An experiment was conducted in a split-plot design in 2022 and 2023 in northern Benin. Agronomic performance and economical profitability of cotton and maize were measured.

Results

Yield penalties were observed in both years with ST and DS while STHR resulted in a 4–9 % increase in cotton yield with respect to CT. The highest number of bolls per cotton plant was observed with ST and DS. Compared to CT, STHR led to a 3–8 % increase in gross income and a 20–70 % increase in gross margin for cotton. Regarding maize, the STHR resulted in an increase in gross income and margin by 13 % and 27 %, respectively, in comparison to CT in 2022. In 2023, the later exhibited the highest gross income and margin.

Conclusions

In our case, STHR appears to be reasonable compromise to minimize yield penalties while increasing profitability in an early transition to Conservation Agriculture.

Implications or significance

Although STHR led to improved performance, it resulted in extensive soil disturbance in the subsequent year. Continued research efforts are needed to refine farmer-targeted CA practices in cotton-based cropping systems of Benin.
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引用次数: 0
Deficit drip irrigation combined with nitrogen application improves cotton yield and nitrogen use efficiency by promoting plant 15N uptake and remobilization
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-17 DOI: 10.1016/j.fcr.2025.109792
Huan Liao, Hengyu Liu, Qingyang Tian, Bohan Zhou, Honglong Yang, Zhenan Hou
<div><h3>Context</h3><div>Deficit irrigation has been widely investigated as a valuable crop production strategy to reduce irrigation water use in arid regions. The nitrogen (N) remobilization from vegetative organs to reproductive organs is vital for enhancing crop yield and N use efficiency (NUE). However, the effect of deficit irrigation on plant N remobilization remain unclear.</div></div><div><h3>Research question</h3><div>We hypothesized that deficit irrigation combined with reasonable N application can promote cotton N uptake and N remobilization from vegetative organs (stems and leaves) to bolls, thereby increasing cotton yield and NUE.</div></div><div><h3>Methods</h3><div>A three-year (2020–2022) field-plot experiment was conducted to investigate the impact of different irrigation levels (including full irrigation (FI) and two deficit irrigation treatments (DI1 and DI2, DI1 and DI2 corresponding to 80 and 60 % of FI, respectively) and N application levels (225 (N225), 300 (N300), and 375 (N375) kg ha<sup>−1</sup>) on the cotton N uptake and yield. In order to further clarify the effects of deficit irrigation on fertilizer N (<sup>15</sup>N) uptake of cotton and its remobilization from vegetative organs (stems and leaves) to reproductive organs (bolls), a <sup>15</sup>N-traced micro-plot experiment was established in 2022 based on the field-plot experiment.</div></div><div><h3>Results</h3><div>Compared with FI, DI1 significantly increased cotton N uptake and yield, while DI2 treatment significantly reduced cotton N uptake and yield. The cotton yield of DI1 treatment was 8.78 %, 9.76 %, and 7.67 % higher than that of FI treatment in 2020, 2021, and 2022, respectively. The three-year experiment (2020–2022) showed that the DI1 +N300 treatment had the highest N uptake and yield of cotton. The <sup>15</sup>N-traced micro-plot experiment revealed that during the pre-bolling stage, the total <sup>15</sup>N uptake of cotton plants increased with increasing irrigation and N application. During the post-bolling stage, DI1 greatly increased the bolls <sup>15</sup>N uptake, resulting in the total <sup>15</sup>N uptake of cotton plants was 5.57–8.72 % and 24.03–33.06 % higher than that of FI and DI2, respectively. The total <sup>15</sup>N uptake of cotton plants peaked at the DI1 +N300 treatment. Moreover, compared with FI, DI1 and DI2 significantly increased the remobilization of <sup>15</sup>N from vegetative organs (leaves and stems) to bolls (NR<sub>T</sub>), especially the remobilization from leaves to bolls (NR<sub>L</sub>), with NR<sub>T</sub> increasing by 32.24 % and 18.77 %, and NR<sub>L</sub> increasing by 53.14 % and 43.48 %, respectively. Under FI and DI1 conditions, NR<sub>T</sub> reached its maximum at N300. However, under DI2 conditions, NR<sub>T</sub> increased with increasing N application, although there was no significant difference between N300 and N375. The cotton plant <sup>15</sup>N recovery under DI1 was 7.84 and 32.15 % highe
{"title":"Deficit drip irrigation combined with nitrogen application improves cotton yield and nitrogen use efficiency by promoting plant 15N uptake and remobilization","authors":"Huan Liao,&nbsp;Hengyu Liu,&nbsp;Qingyang Tian,&nbsp;Bohan Zhou,&nbsp;Honglong Yang,&nbsp;Zhenan Hou","doi":"10.1016/j.fcr.2025.109792","DOIUrl":"10.1016/j.fcr.2025.109792","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Context&lt;/h3&gt;&lt;div&gt;Deficit irrigation has been widely investigated as a valuable crop production strategy to reduce irrigation water use in arid regions. The nitrogen (N) remobilization from vegetative organs to reproductive organs is vital for enhancing crop yield and N use efficiency (NUE). However, the effect of deficit irrigation on plant N remobilization remain unclear.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Research question&lt;/h3&gt;&lt;div&gt;We hypothesized that deficit irrigation combined with reasonable N application can promote cotton N uptake and N remobilization from vegetative organs (stems and leaves) to bolls, thereby increasing cotton yield and NUE.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;A three-year (2020–2022) field-plot experiment was conducted to investigate the impact of different irrigation levels (including full irrigation (FI) and two deficit irrigation treatments (DI1 and DI2, DI1 and DI2 corresponding to 80 and 60 % of FI, respectively) and N application levels (225 (N225), 300 (N300), and 375 (N375) kg ha&lt;sup&gt;−1&lt;/sup&gt;) on the cotton N uptake and yield. In order to further clarify the effects of deficit irrigation on fertilizer N (&lt;sup&gt;15&lt;/sup&gt;N) uptake of cotton and its remobilization from vegetative organs (stems and leaves) to reproductive organs (bolls), a &lt;sup&gt;15&lt;/sup&gt;N-traced micro-plot experiment was established in 2022 based on the field-plot experiment.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Compared with FI, DI1 significantly increased cotton N uptake and yield, while DI2 treatment significantly reduced cotton N uptake and yield. The cotton yield of DI1 treatment was 8.78 %, 9.76 %, and 7.67 % higher than that of FI treatment in 2020, 2021, and 2022, respectively. The three-year experiment (2020–2022) showed that the DI1 +N300 treatment had the highest N uptake and yield of cotton. The &lt;sup&gt;15&lt;/sup&gt;N-traced micro-plot experiment revealed that during the pre-bolling stage, the total &lt;sup&gt;15&lt;/sup&gt;N uptake of cotton plants increased with increasing irrigation and N application. During the post-bolling stage, DI1 greatly increased the bolls &lt;sup&gt;15&lt;/sup&gt;N uptake, resulting in the total &lt;sup&gt;15&lt;/sup&gt;N uptake of cotton plants was 5.57–8.72 % and 24.03–33.06 % higher than that of FI and DI2, respectively. The total &lt;sup&gt;15&lt;/sup&gt;N uptake of cotton plants peaked at the DI1 +N300 treatment. Moreover, compared with FI, DI1 and DI2 significantly increased the remobilization of &lt;sup&gt;15&lt;/sup&gt;N from vegetative organs (leaves and stems) to bolls (NR&lt;sub&gt;T&lt;/sub&gt;), especially the remobilization from leaves to bolls (NR&lt;sub&gt;L&lt;/sub&gt;), with NR&lt;sub&gt;T&lt;/sub&gt; increasing by 32.24 % and 18.77 %, and NR&lt;sub&gt;L&lt;/sub&gt; increasing by 53.14 % and 43.48 %, respectively. Under FI and DI1 conditions, NR&lt;sub&gt;T&lt;/sub&gt; reached its maximum at N300. However, under DI2 conditions, NR&lt;sub&gt;T&lt;/sub&gt; increased with increasing N application, although there was no significant difference between N300 and N375. The cotton plant &lt;sup&gt;15&lt;/sup&gt;N recovery under DI1 was 7.84 and 32.15 % highe","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"324 ","pages":"Article 109792"},"PeriodicalIF":5.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Yield gains and resource use advantages driven by legume choice and row ratio in cotton/legume intercropping under arid-irrigated conditions 干旱灌溉条件下棉花/豆科植物间作中豆科植物的选择和行比带来的增产和资源利用优势
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-17 DOI: 10.1016/j.fcr.2025.109789
Muhammad Ali Raza , Atta Mohi Ud Din , Hassan Shehryar Yasin , Hina Gul , Amjad Saeed , Aqib Mehmood , Sana Ur Rehman , Zafar Iqbal , Rashid Iqbal , Noorah Al Kubaisi , Mohamed S. Elshikh , Ghulam Abbas Shah , Wang Zhiqi , Muhammad Habib Ur Rahman , Muhammad Hayder Bin Khalid , Imran Haider , Ma Zhongming
<div><h3>Context</h3><div>Intercropping ensures stable yields and aboveground productivity through efficient resource consumption by exploiting species complementarities. Tthe wide space between cotton rows and inefficient resources utilization presents an opportunity to leverage intercropping to optimize resource use.</div></div><div><h3>Objective</h3><div>We hypothesized that cotton/legume intercropping could (i) achieve higher land and nutrient productivity than sole cotton and (ii) produce additional legume (soybean/mungbean) yield while maintaining cotton cultivation area and yield with reduced land and anthropogenic inputs (nitrogen; N, and phosphorus; P).</div></div><div><h3>Methods</h3><div>This three-year field study (2022–2024) on cotton/legume intercropping, with varying legume row ratios (two (2LRs) or three (3LRs) rows of legumes planted between every two rows of cotton), was conducted in arid-irrigated conditions. Growth indices (leaf area index and dry matter accumulation), N and P uptake, seed cotton/seed yield, system level land- and nutrient-use advantages, measured as land equivalent ratios (LER) for land (LER<sub>L</sub>), N (LER<sub>N</sub>), and P (LER<sub>P</sub>), and economic returns were compared between sole cotton and cotton/legume intercropping systems.</div></div><div><h3>Results</h3><div>Intercropping with 2LRs achieved higher growth indices, nutrient uptake, and yields than with 3LRs. With 2LRs, intercropped mungbean and soybean achieved 64 % and 79 % of their sole yield; intercropped cotton produced 87 % and 83 % of their sole yield in cotton/mungbean and cotton/soybean intercropping, respectively. Similarly, with 2LRs, the total N and P uptake, calculated as cotton N/P uptake + legume N/P uptake, was 31 %-36 % higher for N and 9 %-15 % higher for P in cotton/legume systems compared to the corresponding values in sole cotton. Overall, the LER<sub>L</sub>, LER<sub>N</sub>, and LER<sub>P</sub>, ranged from 1.34 to 1.63, 1.44–1.70, and 1.22–1.54, respectively, in cotton/legume intercropping, which increased the net economic profit of cotton/mungbean intercropping with 2LRs (USD 472 ha<sup>−1</sup>) and 3LRs (USD 290 ha<sup>−1</sup>) by 122 % and 37 %, and cotton/soybean intercropping with 2LRs (USD 692 ha<sup>−1</sup>) and 3LRs (USD 444 ha<sup>−1</sup>) by 226 % and 109 %, respectively, than sole cotton (USD 213 ha<sup>−1</sup>). This improvement in economic returns was primarily due to the additional legume yield obtained from the efficient resource utilization between intercrops, which was not fully utilized by cotton in sole cropping— notably, without extra expenditure on land preparation, irrigation, or fertilizers.</div></div><div><h3>Significance</h3><div>Our study suggests that cotton/legume intercropping could be adopted as a productive strategy to achieve higher and stable yields with less land and fewer nutrient inputs, promoting economic sustainability for resource-poor cotton farmers while reducing enviro
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引用次数: 0
Analysis of factors affecting the nutritional composition of roughage using existing data: A case study on China and Africa
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-16 DOI: 10.1016/j.fcr.2025.109796
Guanghui Hu , Mengjiao Guo , Yanfen Cheng , Weiyun Zhu , James Ombiro Ondiek , Raphael Githaiga Wahome , Adugna Tolera , Varijakshapanicker Padmakumar
<div><h3>Context or problem</h3><div>Most studies suggested that as the concentration of atmospheric carbon dioxide increases, straw seemed to be becoming more difficult to digest, but this was not absolute. Due to various factors, there has been no consensus on the changes in straw composition and digestibility.</div></div><div><h3>Objective or research question</h3><div>The purpose of this study is to investigate the differences in straw composition between China and Africa, as well as the influencing factors, and to establish a predictive model for the <em>in vitro</em> dry matter digestibility.</div></div><div><h3>Methods</h3><div>A total of 14574 articles were retrieved from China National Knowledge Infrastructure, PubMed, Web of Science, and Google Scholar, and the articles were screened and data was extracted. A total of 709 articles were relevant to our research. The Z-score (a standard score <3 was considered acceptable) function was used to constrain the obtained data. The obtained data was used to analyze the differences in straw composition between China and Africa, the main factors affecting straw composition, and changes in <em>in vitro</em> digestibility. Similarly, articles on the <em>in vitro</em> dry matter digestibility of straw had been collected. After evaluating the quality of the articles and filtering the data, an <em>in vitro</em> dry matter digestibility model had been constructed.</div></div><div><h3>Results</h3><div>The research results indicated that there was a significant difference in the composition of rice straw and corn straw between Africa and China, with African straw having a higher Neutral detergent fiber (NDF) than Chinese straw, and the difference between corn straw was extremely significant (<em>P</em> < 0.01). The crude protein (CP) content of Chinese straw was significantly higher than that of African straw (<em>P</em> < 0.05). In terms of time, the contents of crude protein (CP) and ligin (LIG) in straw,except for corn straw in China, also showed an increasing trend over time. On the latitude, the CP of rice and corn showed a decreasing trend with increasing latitude, while the LIG content showed an increasing trend except for wheat straw in China. A model for <em>in vitro</em> digestibility was constructed based on the relationship between straw composition and <em>in vitro</em> digestibility: IVDMD = 155.26 + 1.446–0.083CP<sup>2</sup> + 3.652EE - 1.147EE<sup>2</sup> - 2.77Ash + 0.137Ash<sup>2</sup> - 3.091NDF + 0.023NDF<sup>2</sup> + 1.016ADF - 0.019ADF<sup>2</sup>.</div></div><div><h3>Conclusions</h3><div>The results indicated that there were significant differences in straw composition between China and Africa. And the composition of straw was influenced by various factors, especially atmospheric carbon dioxide concentration. It was expected that, under the continuous increase in atmospheric CO<sub>2</sub> concentrations, although the CP content of straw would rise, the <em>in vitro</em> d
{"title":"Analysis of factors affecting the nutritional composition of roughage using existing data: A case study on China and Africa","authors":"Guanghui Hu ,&nbsp;Mengjiao Guo ,&nbsp;Yanfen Cheng ,&nbsp;Weiyun Zhu ,&nbsp;James Ombiro Ondiek ,&nbsp;Raphael Githaiga Wahome ,&nbsp;Adugna Tolera ,&nbsp;Varijakshapanicker Padmakumar","doi":"10.1016/j.fcr.2025.109796","DOIUrl":"10.1016/j.fcr.2025.109796","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Context or problem&lt;/h3&gt;&lt;div&gt;Most studies suggested that as the concentration of atmospheric carbon dioxide increases, straw seemed to be becoming more difficult to digest, but this was not absolute. Due to various factors, there has been no consensus on the changes in straw composition and digestibility.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Objective or research question&lt;/h3&gt;&lt;div&gt;The purpose of this study is to investigate the differences in straw composition between China and Africa, as well as the influencing factors, and to establish a predictive model for the &lt;em&gt;in vitro&lt;/em&gt; dry matter digestibility.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;A total of 14574 articles were retrieved from China National Knowledge Infrastructure, PubMed, Web of Science, and Google Scholar, and the articles were screened and data was extracted. A total of 709 articles were relevant to our research. The Z-score (a standard score &lt;3 was considered acceptable) function was used to constrain the obtained data. The obtained data was used to analyze the differences in straw composition between China and Africa, the main factors affecting straw composition, and changes in &lt;em&gt;in vitro&lt;/em&gt; digestibility. Similarly, articles on the &lt;em&gt;in vitro&lt;/em&gt; dry matter digestibility of straw had been collected. After evaluating the quality of the articles and filtering the data, an &lt;em&gt;in vitro&lt;/em&gt; dry matter digestibility model had been constructed.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;The research results indicated that there was a significant difference in the composition of rice straw and corn straw between Africa and China, with African straw having a higher Neutral detergent fiber (NDF) than Chinese straw, and the difference between corn straw was extremely significant (&lt;em&gt;P&lt;/em&gt; &lt; 0.01). The crude protein (CP) content of Chinese straw was significantly higher than that of African straw (&lt;em&gt;P&lt;/em&gt; &lt; 0.05). In terms of time, the contents of crude protein (CP) and ligin (LIG) in straw,except for corn straw in China, also showed an increasing trend over time. On the latitude, the CP of rice and corn showed a decreasing trend with increasing latitude, while the LIG content showed an increasing trend except for wheat straw in China. A model for &lt;em&gt;in vitro&lt;/em&gt; digestibility was constructed based on the relationship between straw composition and &lt;em&gt;in vitro&lt;/em&gt; digestibility: IVDMD = 155.26 + 1.446–0.083CP&lt;sup&gt;2&lt;/sup&gt; + 3.652EE - 1.147EE&lt;sup&gt;2&lt;/sup&gt; - 2.77Ash + 0.137Ash&lt;sup&gt;2&lt;/sup&gt; - 3.091NDF + 0.023NDF&lt;sup&gt;2&lt;/sup&gt; + 1.016ADF - 0.019ADF&lt;sup&gt;2&lt;/sup&gt;.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusions&lt;/h3&gt;&lt;div&gt;The results indicated that there were significant differences in straw composition between China and Africa. And the composition of straw was influenced by various factors, especially atmospheric carbon dioxide concentration. It was expected that, under the continuous increase in atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentrations, although the CP content of straw would rise, the &lt;em&gt;in vitro&lt;/em&gt; d","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"324 ","pages":"Article 109796"},"PeriodicalIF":5.6,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
In-season nitrogen status and pre-harvest potato yield assessment using air-spaceborne imagery with AI techniques
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-14 DOI: 10.1016/j.fcr.2025.109794
Bilal Javed , Athyna N. Cambouris , Louis Longchamps , Parminder S. Basran , Marc Duchemin , Noura Ziadi , Stephanie Arnold , Adam Fenech , Antoine Karam
<div><h3>Context</h3><div>In modern agriculture, timely and precise nitrogen monitoring and pre-harvest tuber yield assessment for potato (<em>Solanum tuberosum</em> L.) crop is essential to optimize resource management, in-time decision-making and trade benefits. Traditional nitrogen assessment methods are labor-intensive and time consuming. Utilizing multispectral data from unmanned aerial vehicles (UAV) and satellite imagery integrated with artificial intelligence (AI) modeling offers high resolution solution for efficient field monitoring throughout the growing season.</div></div><div><h3>Objective</h3><div>The aim of this study was to use AI algorithms trained and validated solely on high-resolution multispectral UAV and Sentinel-2 satellite data to evaluate their potential in estimating in-season plant nitrogen status and pre-harvest tuber yield assessment in commercial potato production fields.</div></div><div><h3>Methods</h3><div>A study was conducted on four commercial potato fields located in Prince Edward Island, Canada. UAV and Sentinel-2 images were used at the early flowering (S1) and pre-harvest (H) stages of potato to extract multispectral bands and vegetative indices. Extracted multispectral bands and vegetative indices were used to assess ground truth data (petiole nitrate concentration as crop N status and tuber yield) at S1 and H phenological stages using five different machine learning algorithms.</div></div><div><h3>Results</h3><div>Results indicated that the bagged tree machine learning algorithm trained on UAV S1 images revealed a relative root mean square error (RRMSE) of 12.7 % and a relative mean absolute error (RMAE) of 9.6 %. In contrast, the random forest model trained on Sentinel-2 S1 data showed an RRMSE of 15.5 % and an RMAE of 12.6 %. The random forest models trained on UAV H and Sentinel-2H data demonstrated an RRMSE of 16.1 % and 13.8 %, and an RMAE of 12.5 % and 11.3 %, respectively. These models revealed the best estimation results when compared with the rest of the machine learning models.</div></div><div><h3>Conclusion</h3><div>The fitted models effectively estimated petiole nitrate concentration and pre-harvest tuber yield in commercial potato fields, demonstrating their practical utility. Key features, such as the Canopy Chlorophyll Content Index via UAV and the red edge band via Sentinel-2, were crucial in the prediction process. These findings underscore the potential of AI algorithms to enhance agricultural productivity and precision in crop management.</div></div><div><h3>Implications</h3><div>The use of AI algorithms trained on high-resolution air-borne data can significantly improve the accuracy of estimating the petiole nitrate concentration and pre-harvest tuber yield. By leveraging key important features with the robust feature engineering techniques, farmers and researchers can make more informed decisions regarding crop management. This approach provides a valuable tool for advancing sustainabl
{"title":"In-season nitrogen status and pre-harvest potato yield assessment using air-spaceborne imagery with AI techniques","authors":"Bilal Javed ,&nbsp;Athyna N. Cambouris ,&nbsp;Louis Longchamps ,&nbsp;Parminder S. Basran ,&nbsp;Marc Duchemin ,&nbsp;Noura Ziadi ,&nbsp;Stephanie Arnold ,&nbsp;Adam Fenech ,&nbsp;Antoine Karam","doi":"10.1016/j.fcr.2025.109794","DOIUrl":"10.1016/j.fcr.2025.109794","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Context&lt;/h3&gt;&lt;div&gt;In modern agriculture, timely and precise nitrogen monitoring and pre-harvest tuber yield assessment for potato (&lt;em&gt;Solanum tuberosum&lt;/em&gt; L.) crop is essential to optimize resource management, in-time decision-making and trade benefits. Traditional nitrogen assessment methods are labor-intensive and time consuming. Utilizing multispectral data from unmanned aerial vehicles (UAV) and satellite imagery integrated with artificial intelligence (AI) modeling offers high resolution solution for efficient field monitoring throughout the growing season.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Objective&lt;/h3&gt;&lt;div&gt;The aim of this study was to use AI algorithms trained and validated solely on high-resolution multispectral UAV and Sentinel-2 satellite data to evaluate their potential in estimating in-season plant nitrogen status and pre-harvest tuber yield assessment in commercial potato production fields.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;A study was conducted on four commercial potato fields located in Prince Edward Island, Canada. UAV and Sentinel-2 images were used at the early flowering (S1) and pre-harvest (H) stages of potato to extract multispectral bands and vegetative indices. Extracted multispectral bands and vegetative indices were used to assess ground truth data (petiole nitrate concentration as crop N status and tuber yield) at S1 and H phenological stages using five different machine learning algorithms.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Results indicated that the bagged tree machine learning algorithm trained on UAV S1 images revealed a relative root mean square error (RRMSE) of 12.7 % and a relative mean absolute error (RMAE) of 9.6 %. In contrast, the random forest model trained on Sentinel-2 S1 data showed an RRMSE of 15.5 % and an RMAE of 12.6 %. The random forest models trained on UAV H and Sentinel-2H data demonstrated an RRMSE of 16.1 % and 13.8 %, and an RMAE of 12.5 % and 11.3 %, respectively. These models revealed the best estimation results when compared with the rest of the machine learning models.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;The fitted models effectively estimated petiole nitrate concentration and pre-harvest tuber yield in commercial potato fields, demonstrating their practical utility. Key features, such as the Canopy Chlorophyll Content Index via UAV and the red edge band via Sentinel-2, were crucial in the prediction process. These findings underscore the potential of AI algorithms to enhance agricultural productivity and precision in crop management.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Implications&lt;/h3&gt;&lt;div&gt;The use of AI algorithms trained on high-resolution air-borne data can significantly improve the accuracy of estimating the petiole nitrate concentration and pre-harvest tuber yield. By leveraging key important features with the robust feature engineering techniques, farmers and researchers can make more informed decisions regarding crop management. This approach provides a valuable tool for advancing sustainabl","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"324 ","pages":"Article 109794"},"PeriodicalIF":5.6,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Late sowing with reduced nitrogen rate promotes relative maturation and nitrogen use efficiency without compromising yield in cotton
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-14 DOI: 10.1016/j.fcr.2025.109790
Peng Zhang , Mingyu Hou , Yongjiang Zhang , Hongchun Sun , Lingxiao Zhu , Ke Zhang , Zhiying Bai , Liantao Liu , Hezhong Dong , Cundong Li

Context

High production costs and difficulties in mechanized harvesting in the Yellow River Valley cotton-growing region of China are primarily attributed to excessive fertilizer application and poor relative maturation. Sowing date significantly affects relative maturation, while nitrogen (N) application directly impacts the production costs. This study aims to explore how late sowing and reduced N rate enhance relative maturation, nitrogen use efficiency (NUE), and cost reduction without compromising seed cotton yield.

Method

A two-year (2019–2020) field experiment was conducted across the two sites using a split-plot design to investigate the effects of sowing date (mid-April and early May) and N rate (0 kg ha⁻¹, reduced to 180 kg ha⁻¹, and typical at 240 kg ha⁻¹) on seed cotton yield, earliness, relative maturation, and NUE.

Results

Under normal sowing, reducing nitrogen rate to 180 kg N ha⁻¹ led to a decrease in seed cotton yield compared to typical N rate. However, this reduced N rate under late sowing did not reduce yield; instead, it increased nitrogen use efficiency (NUE) and achieved a higher net return. Furthermore, applying 180 kg N ha⁻¹ under late sowing improved grouped flowering and boll formation, achieving a greater proportion of mid-season bolls and fewer rotten bolls, ultimately enhancing cotton relative maturation. This combined strategy also shortened the duration of rapid N accumulation and improved the average N accumulation rate, particularly by 7.0–9.0 % in reproductive organs, contributing to more efficient nitrogen allocation to cotton bolls. In contrast, the typical N rate under late sowing promoted excessive vegetative growth, decreasing earliness, relative maturation, and NUE, ultimately compromising yield stability. The entropy-TOPSIS comprehensive evaluation of seed cotton yield, earliness, relative maturation, NUE, and net return indicated that reducing N rate to 180 kg ha⁻¹ under late sowing achieved the highest relative proximity, surpassing the typical N rate under normal sowing.

Conclusion

Overall, late sowing with reduced N input shows promise for light-simplified and cost-effective cotton production in the Yellow River Valley and similar regions. This study highlights how optimizing sowing date and N rate can enhance relative maturation and reduce N inputs without compromising yield, supporting the safe, stable and sustainable development of the cotton industry.
{"title":"Late sowing with reduced nitrogen rate promotes relative maturation and nitrogen use efficiency without compromising yield in cotton","authors":"Peng Zhang ,&nbsp;Mingyu Hou ,&nbsp;Yongjiang Zhang ,&nbsp;Hongchun Sun ,&nbsp;Lingxiao Zhu ,&nbsp;Ke Zhang ,&nbsp;Zhiying Bai ,&nbsp;Liantao Liu ,&nbsp;Hezhong Dong ,&nbsp;Cundong Li","doi":"10.1016/j.fcr.2025.109790","DOIUrl":"10.1016/j.fcr.2025.109790","url":null,"abstract":"<div><h3>Context</h3><div>High production costs and difficulties in mechanized harvesting in the Yellow River Valley cotton-growing region of China are primarily attributed to excessive fertilizer application and poor relative maturation. Sowing date significantly affects relative maturation, while nitrogen (N) application directly impacts the production costs. This study aims to explore how late sowing and reduced N rate enhance relative maturation, nitrogen use efficiency (NUE), and cost reduction without compromising seed cotton yield.</div></div><div><h3>Method</h3><div>A two-year (2019–2020) field experiment was conducted across the two sites using a split-plot design to investigate the effects of sowing date (mid-April and early May) and N rate (0 kg ha⁻¹, reduced to 180 kg ha⁻¹, and typical at 240 kg ha⁻¹) on seed cotton yield, earliness, relative maturation, and NUE.</div></div><div><h3>Results</h3><div>Under normal sowing, reducing nitrogen rate to 180 kg N ha⁻¹ led to a decrease in seed cotton yield compared to typical N rate. However, this reduced N rate under late sowing did not reduce yield; instead, it increased nitrogen use efficiency (NUE) and achieved a higher net return. Furthermore, applying 180 kg N ha⁻¹ under late sowing improved grouped flowering and boll formation, achieving a greater proportion of mid-season bolls and fewer rotten bolls, ultimately enhancing cotton relative maturation. This combined strategy also shortened the duration of rapid N accumulation and improved the average N accumulation rate, particularly by 7.0–9.0 % in reproductive organs, contributing to more efficient nitrogen allocation to cotton bolls. In contrast, the typical N rate under late sowing promoted excessive vegetative growth, decreasing earliness, relative maturation, and NUE, ultimately compromising yield stability. The entropy-TOPSIS comprehensive evaluation of seed cotton yield, earliness, relative maturation, NUE, and net return indicated that reducing N rate to 180 kg ha⁻¹ under late sowing achieved the highest relative proximity, surpassing the typical N rate under normal sowing.</div></div><div><h3>Conclusion</h3><div>Overall, late sowing with reduced N input shows promise for light-simplified and cost-effective cotton production in the Yellow River Valley and similar regions. This study highlights how optimizing sowing date and N rate can enhance relative maturation and reduce N inputs without compromising yield, supporting the safe, stable and sustainable development of the cotton industry.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"324 ","pages":"Article 109790"},"PeriodicalIF":5.6,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Grazing optimizes forage production and soil GHG emissions of mixed perennial pasture in an inland arid area
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-11 DOI: 10.1016/j.fcr.2025.109788
Jiao Ning , Yarong Guo , Shanning Lou , Cheng Zhang , Wanhe Zhu , Charles P. West , Xiong Z. He , Fujiang Hou

Context

In the context of global warming and increasing demands for forage production, optimizing greenhouse gas (GHG) emissions and forage production is crucial to sustainable pasture management in arid areas.

Objective

A 4-year experiment was conducted to compare the impacts of grazing versus haying on GHG emissions and forage yields in a mixed perennial pasture of alfalfa (Medicago sativa) and tall fescue (Lolium arundinaceum) on a saline cropland.

Methods

Static box method was used to measure the monthly dynamics of soil CO2, CH4, and N2O fluxes. We measured the forage dry matter (DM) and crude protein (CP) yields, and soil properties, and calculated the GHG intensity (GHGI) to assess the balance between forage yields and GHG emissions.

Results

We found that grazing reduced total GHG emissions by 17.2 % compared to haying in the second year; however, the reduction was later offset by nutrient enrichment from livestock manure. Grazing produced 17.6 % more forage DM and 14.8 % more CP compared to haying over the last two years. Root mass, SOC, and air temperature were key factors influencing soil CO2 and CH4 fluxes, while soil nitrate-nitrogen mainly affected soil N2O emissions. Compared to haying, grazing resulted in 22.6 % and 20.4 % lower GHGI for DM and CP yield, respectively.

Conclusions

Grazing offers an effective strategy for optimizing forage production and environmental performance in mixed perennial pastures in continental arid regions.

Implications

Our findings deliver insights into mitigating agricultural GHG emissions and enhancing food security.
{"title":"Grazing optimizes forage production and soil GHG emissions of mixed perennial pasture in an inland arid area","authors":"Jiao Ning ,&nbsp;Yarong Guo ,&nbsp;Shanning Lou ,&nbsp;Cheng Zhang ,&nbsp;Wanhe Zhu ,&nbsp;Charles P. West ,&nbsp;Xiong Z. He ,&nbsp;Fujiang Hou","doi":"10.1016/j.fcr.2025.109788","DOIUrl":"10.1016/j.fcr.2025.109788","url":null,"abstract":"<div><h3>Context</h3><div>In the context of global warming and increasing demands for forage production, optimizing greenhouse gas (GHG) emissions and forage production is crucial to sustainable pasture management in arid areas.</div></div><div><h3>Objective</h3><div>A 4-year experiment was conducted to compare the impacts of grazing versus haying on GHG emissions and forage yields in a mixed perennial pasture of alfalfa (<em>Medicago sativa</em>) and tall fescue (<em>Lolium arundinaceum</em>) on a saline cropland.</div></div><div><h3>Methods</h3><div>Static box method was used to measure the monthly dynamics of soil CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O fluxes. We measured the forage dry matter (DM) and crude protein (CP) yields, and soil properties, and calculated the GHG intensity (GHGI) to assess the balance between forage yields and GHG emissions.</div></div><div><h3>Results</h3><div>We found that grazing reduced total GHG emissions by 17.2 % compared to haying in the second year; however, the reduction was later offset by nutrient enrichment from livestock manure. Grazing produced 17.6 % more forage DM and 14.8 % more CP compared to haying over the last two years. Root mass, SOC, and air temperature were key factors influencing soil CO<sub>2</sub> and CH<sub>4</sub> fluxes, while soil nitrate-nitrogen mainly affected soil N<sub>2</sub>O emissions. Compared to haying, grazing resulted in 22.6 % and 20.4 % lower GHGI for DM and CP yield, respectively.</div></div><div><h3>Conclusions</h3><div>Grazing offers an effective strategy for optimizing forage production and environmental performance in mixed perennial pastures in continental arid regions.</div></div><div><h3>Implications</h3><div>Our findings deliver insights into mitigating agricultural GHG emissions and enhancing food security.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"323 ","pages":"Article 109788"},"PeriodicalIF":5.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Auxin regulates leaf senescence and nitrogen assimilation to promote grain filling in maize (Zea mays L.)
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-06 DOI: 10.1016/j.fcr.2025.109787
Na Jiang , Peng Wang , Zhiqi Yang , Changwei Li , Yixiang Xia , Xiangmin Rong , Yongliang Han , Lan Yang

Context

Leaf senescence is the final stage of leaf development, which is often accompanied by nitrogen remobilization. And also, leaf senescence can be modulated by auxin.

Objective

The objective was to advance in the knowledge of the auxin-mediated mechanisms of leaf senescence and nitrogen assimilation that regulated grain yield.

Methods

Using maize variety Zhengdan 958 (ZD958) as material, a two-year field experiment was conducted to assess the leaf senescence and nitrogen assimilation-related physiological process regulated by Naphthalene acetic acid (NAA) (H2O, 0.1 mmol/L NAA) and nitrogen levels (N0: No N application, N240: Normal N).

Results

The results showed that NAA significantly increased grain yield under low N conditions, which increased by 55.0 % in 2022 and 29.7 % in 2023, respectively. Auxin promotes grain filling mainly by extending the duration of filling days and increasing the average filling rate. In addition, auxin reduced nitrogen output from leaves, and significantly increased nitrogen accumulation in other organs. The total N accumulation of auxin treatment was increased by 34.7 % under low N condition, and increased by 17.5 % under normal N condition. Furthermore, NAA significantly increased the activities of NR (Nitrate Reductase), GS (Glutamine Synthetase) and GOGAT (Glutamate synthase), thus promoting the nitrogen assimilation ability of leaves. Conversely, auxin application reduced the content of abscisic acid and ethylene, increased the activity of antioxidant enzymes, and decreased the expression of senescence-related genes. This delayed leaf senescence, which was conducive to extending the grain-filling duration and the accumulation of grain starch and protein, subsequently improved the maize yield.

Conclusions

Auxin increased nitrogen assimilation ability and delayed leaf senescence, increase protein and carbohydrate accumulation in the grain, and thus increased the maize yield by 9.3 % and 42.4 %, under normal and nitrogen-deficiency condition.

Implications

This study highlights the impact of externally auxin application on N assimilation and senescence and its regulatory function in grain development.
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引用次数: 0
Enhancing maize yield and water productivity through coordinated root-shoot growth under mild water stress in dense planting
IF 5.6 1区 农林科学 Q1 AGRONOMY Pub Date : 2025-02-05 DOI: 10.1016/j.fcr.2025.109786
Yining Ma , Jiawei Ren , Shengju Yang , Risheng Ding , Taisheng Du , Shaozhong Kang , Ling Tong

Context

For a long time, the ultimate objective in arid and semi-arid agricultural production areas has been to optimize yield while ensuring efficient utilization of agricultural water resources. This objective can be realized through a judicious integration of dense planting and regulated deficit irrigation (RDI). Currently, it is not clear how these two agronomic measures regulate maize yield by affecting root-shoot coordination.

Objective

This study aimed to examine the impacts of planting density (PD) and RDI on leaf area index (LAI), fractional interception of photosynthetically active radiation (FIPAR), radiation use efficiency (RUE), root growth, dry matter distribution, root-shoot ratio (RSR), water productivity (WP), nitrogen partial factor productivity (PFPN), and maize yield. Elucidated the relationship between soil water content (SWC) and root development within different soil layers and to quantify how root characteristics correlate with WUE and yield. Methods: A two-year field trial (2020–2021) was conducted on Xianyu 335 for this study. Set two PD treatments (D1: 70,000 plants/ha, D2: 90,000 plants/ha) and three water treatments, (W1: full irrigation, W2: mild water deficit 2/3W1, W3: moderate water deficit 1/2W1).

Results

Dense planting significantly increased the LAI of the population. The FIPAR and RUE of the middle canopy were enhanced, optimizing the canopy structure. Under the D2 treatment, a greater distribution of roots occurred in the topsoil (0–20 cm). Sufficient water availability augmented both the proportion of root mass and the absorption area in deeper soil, thereby promoting the accumulation of dry matter above ground. The RSR decreased with increasing water stress. Under the D2W2 treatment, a positive correlation was observed between SWC and root characteristics across all soil layers, particularly at depths of 60–100 cm. This suggests that moderate water stress application improves water utilization by roots in the deeper soil. Over the two growing seasons, D2W1 resulted in the highest yield and PFPN. Although the yield under the D2W2 treatment decreased marginally by approximately 2.43–3.90 % compared to D2W1, this treatment significantly enhanced WUE (2020: 11.80 %, 2021: 14.29 %) and middle canopy RUE (2020: 13.85 %, 2021: 17.07 %).

Conclusions and implications

D2W2 is a planting pattern suitable for maize production in Northwest China (NWC). This approach promotes root-shoot coordination and enhances the use of soil moisture by the root system.
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引用次数: 0
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Field Crops Research
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