Latitude, Planting Density, and Soil Available Potassium Are the Key Driving Factors of the Cotton Harvest Index in Arid Regions

The harvest index (HI), a crucial agronomic trait that measures the ratio of grain yield to aboveground biomass, serves not only as a vital indicator for assessing wheat yield but also as a core parameter for predicting straw resource. It reflects the "source-sink" relationship and biomass allocation strategies in crops. However, the spatial distribution patterns of wheat HI and their key driving factors in arid regions remain unclear. This study was conducted in Xinjiang, a typical arid region of China, during 2022-2023, involving two years of large-scale systematic sampling. By integrating multidimensional factors such as geographical and climatic conditions, agronomic management practices, and soil nutrient status, methods including correlation analysis, random forest models, structural equation modeling, and linear regression analysis were employed to systematically investigate the spatial distribution characteristics and driving mechanisms of wheat HI under different irrigation regimes in arid regions. The results revealed that: (1) Wheat HI in arid regions exhibited significant spatial heterogeneity (0.43-0.67), with an overall distribution pattern of "central high, peripheral low" and "northern high, southern low." (2) The importance rankings of influencing factors differed between irrigation regimes. For irrigated wheat, the order of importance was: Geographic-climatic factors, soil nutrient factors, agronomic management factors. Comprehensive analysis identified longitude (lon), plant height (H), latitude (lat), and bulk density (BD) as the key drivers of the Harvest Index (HI) in irrigated wheat. In contrast, for rainfed wheat, the order was: soil nutrient factors, Geographic-climatic factors, agronomic management factors, with total nitrogen (TN), available phosphorus(AP), total potassium(TK), and total phosphorus (TP) emerging as critical drivers of HI. Irrigation significantly enhanced wheat HI (p < 0.01), and irrigated wheat demonstrated significantly higher HI, yield, and aboveground biomass (AGB) compared to rainfed wheat (p < 0.01). Optimizing phosphorus management could enhance HI in both systems, while irrigation infrastructure development remains vital for yield stability. This study provides a theoretical basis and practical guidance for the synergistic multi-objective approach of "yield increase-irrigation-sustainability" in arid regions wheat production.

This comparative study was aimed at estimating analytical behavior of methods for determination of plant available potassium applied to Bulgarian arable soils and to reveal the relationship between the amount of extractable K. Twenty-four samples from two traditional agricultural regions in Bulgaria were studied. Soil potassium was extracted by NH4OAc/HOAc pH 4.5 (AA), diluted double acid (Mehlich 1), CaCl2, BaCl2 and a modified acetate/lactate method (ALM) and determined by Flame AES. The factors influencing the methods accuracy were identified and uncertainty was estimated. The expanded uncertainty was (in mg K2O (100 g dry soil)-1): 0.10 (ALM), 0.64 (Mehlich 1), 0.17 (CaCl2) and 1.1 (AA). The study revealed that the factor which mainly influence the uncertainty of the applied analytical methods for plant available potassium in soil was the calibration of Flame AES determination. The obtained results showed that extractable potassium lowered in the following order . Soil potassium extracted by ALM procedure correlated with AA, BaCl2-K, CaCl2 –K and Mehlich 1 - K at 0.05 level of significance. ALM extracted between 1.2 to 5.8 times more soil K than other methods did. The obtained results provided a base for further study on correlation between extractable K and soil fertility indices for particular soil types and climatic regions in Bulgaria.

Biochar has wide application prospects as a good soil conditioner, leguminous plants can fix nitrogen and improve soil available nutrients. However, it is not clear how adding biochar when planting leguminous plants affects soil bacterial community and soil available nutrients. This study investigates the effects of biochar addition on the content of ammonia nitrogen, Olsen-P, and available potassium in northeastern farmland soils under the plantation of Trifolium repens and then compared with the application of organic fertilizer. A 90-day incubation experiment was conducted to compare the changes in the structure and relative abundance of soil microflora under varied biochar additions. It was found that the addition of biochar could affect the structure of the microflora and the available nutrients in the soil. When compared with soil planted with T. repens without the addition of biochar, with the application of 3% biochar increased the content of ammonia nitrogen, Olsen-P, and available potassium in the soil by 31.71%, 21.40%, and 11.51%, respectively. High throughput sequencing revealed that the relative abundance of functional bacteria such as azotobacter, rhizobacteria, and phosphorus solubilizing bacteria in the soil increased with the addition of biochar. Furthermore, the effect was more obvious with the addition of organic fertilizers. The addition of biochar improved the microbial community structure and increased the relative abundance of functional bacteria and the content of available nutrients in the soil. This is expected to reduce the application of chemical fertilizers, thereby protecting the environment and conserving natural resources.

به‌منظور تعیین تراکم کاشت و تداخل علف هرز بر خصوصیات زراعی گیاه شنبلیله، آزمایشی در بهار سال زراعی 90-1389 در مزرعه تحقیقاتی دانشکده کشاورزی دانشگاه آزاد اسلامی بیرجند به‌صورت فاکتوریل در قالب بلوک‌های کامل تصادفی با سه تکرار اجرا گردید. فاکتورهای آزمایشی شامل تراکم بوته شنبلیله در سه سطح 10، 20 و 40 بوته در متر مربع و دوره تداخل علف هرز در پنج سطح شامل تمام وجین، 20، 40 و 60 روز تداخل پس از سبز شدن و عدم وجین بودند. نتایج آزمایش نشان داد که بیشترین و کمترین عملکرد دانه (با مقادیر 81/56 و 120/43 گرم در متر مربع) به‌ترتیب مربوط به تیمارهای تراکم 40 و 10 بوته در متر مربع بود. همچنین کاهش تراکم سبب کاهش معنی‌دار ارتفاع بوته و عملکرد دانه گردید. افزایش دوره‌های طولانی مدت تداخل علف هرز مانع از رشد اندام‌های رویشی و تسریع در ورود به فاز زایشی گردیده در نهایت باعث افزایش شاخص برداشت و کاهش عملکرد شد به‌طوری‌که میانگین عملکرد دانه در تیمار عدم وجین (76/42 گرم در متر مربع)، 5/28 درصد نسبت به تیمار تمام وجین کاهش یافت. افزایش تراکم موجب کاهش وزن خشک علف هرز گردید، کمترین وزن خشک علف هرز (7/2057 گرم در متر مربع) از تیمار 40 بوته در متر مربع به‌دست آمد. اثر متقابل تراکم و تداخل علف هرز بر عملکرد دانه در سطح 5 درصد معنی‌دار شد. براساس نتایج به‌دست آمده از این آزمایش می‌توان بیان کرد در بین تراکم‌های مختلف، تراکم 40 بوته در متر مربع در شرایط وجین کامل بیشترین عملکرد دانه را تولید کرد.

SUMMARYTo support tropical maize (Zea maysL.) breeding efforts, the current work aimed to assess harvest index (HI) in modern hybrids and determine the effect of different planting densities on grain yield and HI under well-fertilized (HN) and nitrogen (N) deficient conditions. Harvest index and grain yield of 34 hybrids on average reached 0·42 and 7·06 t/ha (five environments), indicating a large potential for improvement in HI relative to temperate hybrids. Ear weight (r= 0·88), HI (r= 0·78) and shoot dry weight (r= 0·68) were strongly associated with grain yield. In the second experiment, seven hybrids were evaluated at planting densities of 5, 7, 9 and 11 plants/m2under HN (six environments) and N deficient (LN) conditions (four environments) to assess the effect of planting density on grain yield and HI. Grain yield increased by 40·4 and 21·8% under HN and LN conditions when planting density was increased relative to the lowest planting density. Harvest index increased from 0·42 at 5 plants/m2to 0·45 at 11 plants/m2under HN conditions and decreased from 0·44 at 5 plants/m2to 0·42 at 9 plants/m2under LN conditions. Harvest index was maximized at planting densities of 8·33 plants/m2and 5·30 plants/m2under HN and LN conditions, respectively, while grain yield was maximized at 9·93 plants/m2and 7·89/m2. Optimal planting density maximizing both HI and grain yield were higher than planting densities currently used in tropical germplasm. It can be concluded that productivity in tropical maize could be increased both under intensive (+40·4%) and lower-input management (+21·8%) by increasing planting densities above those currently used in smallholder agriculture in Latin America and Sub-Saharan Africa, in environments targeted by the International Maize and Wheat Improvement Center.

Harvest index (HI) is the ratio of grain to total shoot dry matter and is as a measure of reproductive efficiency. HI is determined by interactions between genotypes (G), environment (E), and crop management (M). Historic genetic yield gains due to breeding in wheat have largely been achieved by increasing HI. Environmental factors are important for HI and include seasonal pattern of water supply and extreme temperatures during crop reproductive development. Wheat production in Australia has been dominated by fast-developing spring cultivars that when sown in late-autumn will flower at an optimal time in early spring. Water limited potential yield can be increased by sowing slower developing wheats with a vernalization requirement (winter wheat) earlier than currently practiced such that their development is matched to environment and they flower at the optimal time. This means a longer vegetative phase which increases rooting depth, proportion of water-use transpired, and transpiration efficiency by allowing more growth during winter when vapour pressure deficit is low. All these factors can increase biomass accumulation, grain number and thus grain yield potential. However higher yields are not always realized due to a lower HI of early sown slow developing wheats compared to fast developing wheats sown later. Here, we evaluate genotype × management practices to improve HI and yield in early sown slow developing wheat crops using 6 field experiments conducted across south eastern Australia from 2014 to 2018 in yield environments ranging from ~1 to ~4.7 t/ha. Practices included low plant densities (30–50 plants/m²), mechanical defoliation, and deferred application of nitrogen fertilizer. Lower plant densities had similar yield and HI to higher plant densities. Defoliation tended to increase HI but reduce yield except when there was severe stem frost damage. Deferring nitrogen had a variable effect depending on starting soil N and in crop rainfall. All management strategies evaluated gave variable HI and yield responses with small effect sizes, and we conclude that none of them can reliably increase HI in early sown wheat. We propose that genetic improvement is the most promising avenue for increasing HI and yield in early sown wheat, and postulate that this could be achieved more rapidly through early generation screening for HI in slow developing genotypes than by crop management.

Modern maize (Zea mays L.) hybrids are generally regarded as strongly population dependent because maximum grain yields (GYs) per area are achieved primarily in high‐density populations. This study was conducted to analyze changes in density independence with plant density based on the response of GY, dry matter (DM) accumulation, and the harvest index (HI) to changes in plant density. Two modern cultivars, ZhengDan958 and ZhongDan909, were planted at 12 densities ranging from 1.5 to 18 plants m−2. The experiment was conducted for 3 yr, with drip irrigation and plastic mulching, at the 71 Group and Qitai Farms located in Xinjiang, China. With increased plant density, DM accumulation per area increased logarithmically, the HI decreased according to a cubic curve, and GY per area increased quadratically; the optimum density was 10.57 plants m−2. Further analysis showed that the response of GY per area, DM per area, and the HI to changes in plant density could be divided into four density ranges: Range I (≤4.7 plants m−2), in which DM per area, the HI, and GY per area were significantly affected by density; Range II (4.7–8.3 plants m−2), in which the HI was unaffected by density but DM per area and GY per area were significantly affected; Range III (8.3–10.75 plants m−2), in which GY per area was unaffected by density but DM per area and the HI were significantly affected; and Range IV (≥10.7 plants m−2), in which DM per area was unaffected by density but the HI and GY per area were significantly affected. These results indicated that Range II is a density‐independent range and Range III is a GY‐stable range.

The response of cotton to constant salinity has been well documented under controlled conditions, but its response to changing salinity under field conditions is poorly understood. Using a split‐plot design, we conducted a 2‐year field experiment to determine the effects of soil salinity and plant density on plant biomass, boll load, harvest index and leaf senescence in relation to cotton yield in three fields with similar fertility but varying salinity. The main plots were assigned to weak (electrical conductivity of soil saturated paste extract, ECe = 5.5 dS m−1), moderate (ECe = 10.1 dS m−1) and strong (ECe = 15.0 dS m−1) soil salinity levels, while plant density (3.0, 4.5 and 7.5 plants m−2) was assigned to the subplots. Soil salinity had a negative effect on seedcotton yield, but the negative effect was compensated for by increased plant density under strong‐salinity conditions. Seedcotton yield under weak salinity changed little with varying plant density, but the medium plant density yielded better than the low or high plant density under moderate salinity. Plants accumulated 49 and 112 % more Na+ in leaves under moderate and strong salinity than under weak salinity. Strong salinity also led to higher boll load and early leaf senescence. Plant density had no effect on Na+ accumulation in leaves, but greatly reduced boll load and delayed leaf senescence. Plant biomass, maximum leaf area index and harvest index were greatly affected by salinity, plant density and their interaction. Accelerated leaf senescence under strong salinity was attributed to the high boll load and increased accumulation of toxic ions like Na+ in leaves, while delayed leaf senescence with increased plant density was attributed to the reduced boll load. Optimal yield can only be obtained with proper coordination of total biomass and harvest index by modification of plant density based on salinity levels.

A comprehensive study of plant density consequences on nitrogen uptake dynamics of maize plants from vegetative to reproductive stages

Quantifying historical changes in maize harvest index (HI), the fraction of above-ground biomass allocated to grain yield, can enhance our ability to explain grain yield trends and estimate stover carbon inputs for sustainability assessments. However, the HI genetic gain has not been the primary focus of previous era studies. The aim of this study is to enhance our knowledge of maize HI genetic gain. Our first objective is to quantify HI genetic gain in Bayer Crop Science Legacy hybrids and investigate the contribution of breeding and agronomic management. Our second objective is to develop a general-use model to describe the temporal evolution of maize HI. We studied 54 commercial hybrids (103-day and 111-day relative maturities) released from 1983 to 2020 across 13 environments, including plant density (current and historical increasing rate) and N-fertilizer (low and sufficient N rates) treatments. The HI was estimated at physiological maturity by destructively sampling plants. Then we synthesize new experimental data with literature findings (n = 16) to provide a robust HI genetic gain estimate. Results showed that HI has increased over the years from 0.516 to 0.571 in 103-day hybrids and from 0.537 to 0.584 in 111-day hybrids. The genetic gains were similar across environments and management treatments within the studied range, indicating that this increase is attributed to maize breeding. The N-fertilizer treatments affected the magnitude of the HI, but plant density did not. Our results, combined with 16 literature datasets, revealed a 0.26% year−1 relative increase in HI since 1964. We estimated that the increase in HI accounts for ca. 15% of the historical maize yield increase in the US Corn Belt over the past 50 years. The maize HI has increased over the last 50 years, and this increase was attributed to breeding, not to management. Our findings enhance our knowledge of maize HI, will support robust estimations of carbon inputs in sustainability studies, and inform crop models to better capture historical yield increases.

Reliable estimates of crop nitrogen (N) uptake and offtake are critical in estimating N balances, N use efficiencies and potential losses to the environment. Calculation of crop N uptake and offtake requires estimates of yield of crop product (e.g. grain or beans) and crop residues (e.g. straw or stover) and the N concentration of both components. Yields of crop products are often reasonably well known, but those of crop residues are not. While the harvest index (HI) can be used to interpolate the quantity of crop residue from available data on crop product yields, harvest indices are known to vary across locations, as do N concentrations of residues and crop products. The increasing availability of crop data and advanced statistical and machine learning methods present us with an opportunity to move towards more locally relevant estimates of crop harvest index and N concentrations using more readily available data. The aim of this study was to investigate whether improved estimates of maize crop HI and N concentrations of crop products and crop residues can be based on crop data available at the global scale, such as crop yield, fertilizer application rates and estimates of yield potential. Experiments from 1487 different locations conducted across 31 countries were used to test various prediction models. Predictions from mixed-effects models and random forest machine learning models provided reasonable levels of prediction accuracy (R 2 of between 0.33 and 0.68), with the random forest method having greater accuracy. Although the mixed-effects prediction models had lower prediction accuracy than random forest, they did provide better interpretability. Selection of which method to use will depend on the objective of the user. Here, the random forest and mixed-effects methods were applied to N in maize, but could equally be applied to other crops and other nutrients, if data becomes available. This will enable obtaining more locally relevant estimates of crop nutrient offtake to improve estimates of nutrient balances and nutrient use efficiency at national, regional or global levels, as part of strategies towards more sustainable nutrient management. • Predictions of crop nitrogen (N) removal at national to sub-national scales will improve global nutrient budgeting. • Maize harvest index (HI), crop product N concentration (CPN) and crop residue N concentrations (CRN) were analyzed. • Predictor variables included crop product yield, fertilizer nitrogen application rates and yield potential. • Random forest (RF) models had greater prediction accuracy of HI, CPN and CRN compared with mixed-effects (ME) models. • Both methods could predict HI, CPN and CRN, but ME models were easier to interpret and extrapolate than RF models.

Terminal removal at first square enhances vegetative branching to increase seedcotton yield at low plant density

With November the objectives of to determine the optimum plant density levels of bread wheat by identifying the most cost-effective variety, a field experiment was conducted at Kulumsa Agricultural Research Center from June to 2018 cropping season, Three bread wheat varieties (Hidassie, Dendea and Shorima) representing different seed sizes of large, medium, small, respectively and four plant density levels of 250, 300, 350 and 400 plants m-2 were tested. The main effect of the varieties seed size on days to 50% of heading, days to 90% of maturity, thousand kernel weight and hecto liter weight showed significant (p&lt;0.01) variations, while number of tillers and spike length indicated statistically significant (p&lt;0.05) variations. The use of 300 plants m-2 plant density for the variety Hidassie /large seed size/ resulted in highest seedling number (26.30), of tillers (7.50), days to 50% of heading (63.00), days to 50% of maturity, (116.00), spike length, (7.50 cm), thousand kernel weight (48.22 gm.), hecto liter weight (78.30 kg/hL). The main effect of plant population on number of seedlings and harvest index showed significant (p&lt;0.01) variations. Number of seedlings and harvest index resulted in (25.31) and (44.05) respectively. The interaction effects of variety and plant density on harvest index, indicated significant (p&lt;0.001) variation, while grain yield showed statistically significant (p&lt;0.01) variation, likewise biomass yield and straw yield indicated significant (p&lt;0.05) variations. The harvest index, resulted in (43.63%), while grain yield is (4.309 Ton ha-1), similarly biomass yield and straw yield are (11.00 Ton ha-1) and (5.28 Ton ha-1) respectively, and it suggests that these traits are generally enhanced by the genetic makeups of the variety Hidassie /large seed size/. Economic analysis using partial budget procedure was performed on grain yields to determine the treatment with most profitable returns. The beneficial marginal rate of return (8.50) and benefit cost ratio (8.07) was obtained from the variety Hidassie /large seed size/ at a plant density of 300 seeds m-2 followed by a marginal rate of return (9.55) and benefit cost ratio (8.05) were also recorded again from the variety Hidassie /large seed size/ at plant density of 250 plants m-2. So the most cost-effective variety and plant density level for farmers with low cost of production and higher benefits were identified to be the variety Hidassie /large seed size/ at the plant density level of 300 plants m-2 in the rain fed cropping season is identified as low cost of production with highest benefit and can be recommended for the producers of wheat crop. The plant density level of 250 plants m-2 for variety Hidassie /large seed size/ was also cost-effective with highest net-benefit and can be recommended as another possible choice. But, as this study was conducted at one experimental site, it is required to repeat the experiment across locations, soil type, and over-seasons to make agronomically consistent recommendations and economically feasible levels of plant density for bread wheat. Keywords: Bread Wheat Yield, Economic Benefit, Plant Density, Grain Quality, Varieties Seed Size. DOI: 10.7176/JNSR/11-15-01 Publication date: August 31 st 2020

In order to get the formation about the content of alkali-hydrolyzable nitrogen in soil, available phosphorus and available potassium, and the input of chemical fertilizer in apple orchard, we survey 25 peasant households' input of chemical fertilizer in apple orchard, and collect soil samples for measuring and analysis. The results show that the average input of nitrogen, phosphorus and potassium nutrient is 839.6 kg / hm2, 520.4 kg / hm2, and 899 .7 kg / hm2, respectively; the input proportion of nitrogen to phosphorus to potassium nutrient is 1i¼s0.62i¼s1.07; in 0-60cm soil, the average content of alkali-hydrolyzable nitrogen is 53.49 mg/kg, the average content of available phosphorus in soil is 70.73 kg /mg, and the average content of available potassium in soil is 180.1 mg/kg (the proportion of alkali-hydrolyzable nitrogen to available phosphorus to available potassium in soil is 1: 1.32: 3.37). It indicates that the overall level of input of chemical fertilizer in apple orchard is relatively high; the content of alkali-hydrolyzable nitrogen in soil is very low on the whole, the content of available phosphorus in soil is very high, and the content of available potassium in soil is high.

Taro (Colocasia esculenta (L.) Schott) is one of the most underutilized crops in sub-Saharan Africa and an important staple food in the tropics. Understanding its growth response under selected watering regimes and planting densities underpins this research. A study was conducted at the Kenya Agricultural and Livestock Research Organization (KALRO), Embu Research Centre, during the long rains (LR) in 2021 and the short rains (SR) in 2021–2022. A factorial experiment with a split-plot layout arranged in a completely randomized block design was used. The main factor was the irrigation levels, while the subfactor was the planting density, with three replications. The three irrigation levels were at 100%, 60%, and 30% based on the field capacity (FC). The planting densities used were 0.5 m × 0.5 m (40,000 plants ha−1), 1 m × 0.5 m (20,000 plants ha−1), and 1 m × 1 m (10,000 plants ha−1), representative of high, medium, and low planting densities, respectively. Time and season ( P &lt; 0.05 ) significantly influenced taro growth components (plant height, leaf area, leaf area index, and vegetative growth index) and yield components (corm length, corm diameter, corm mass, yield, and total biomass). Planting density influenced the leaf area and the leaf area index ( P &lt; 0.05 ). The watering regime did not affect taro growth or yield components. Corm mass (0.59 kg), total biomass (49.8 t/ha), and yield (13.38 t/ha) were all the highest in the 30% FC. The 1 m × 0.5 m spacing produced the highest corm mass (0.62 kg). The high planting density (0.5 m × 0.5 m) resulted in the highest total biomass (70.2 t/ha), yield (20.84 t/ha), and harvest index (30.44%). As a result, the 0.5 m × 0.5 m planting density and 30% FC watering regime are recommended to farmers in the area for increased yields and food security.